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The number and variety of proteins that have been shown to bind to RPA is large and growing ( 10 ) ( Table 1 ). Despite the variety of its binding partners, RPA appears to have only a limited number of regions available for protein interactions: three domains in RPA70 and one in RPA32 . This raises the question of whether these interactions are specific, and if so, how the specificity for a given protein partner is generated. The contact surfaces in RPA have been elucidated for several of its binding partners, as discussed below, and these results are beginning to suggest that proteins from distinct processing pathways may use a small number of common patterns to bind RPA and remodel its DNA-binding mode .
|
16935876_p7
|
16935876
|
PROTEIN-MEDIATED CONFORMATION CHANGES OF RPA
| 4.201986 |
biomedical
|
Study
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en
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Protein interactions with the C-terminal winged helix domain in RPA32 (RPA32C) have been relatively well characterized structurally. RPA32C binds to the DNA recombination protein Rad52, the base excision repair protein uracil DNA glycosylase 2 and the nucleotide excision repair protein XPA [( 20 ) and references therein]. These interactions are weak ( K d ∼5–10 μM) but specific. Remarkably, all three of these proteins target the same surface of RPA32C and contain an alpha helix that interacts with RPA32C ( 20 ). The conserved nature of these interactions suggests that RPA32C may serve a common function in at least three different DNA processing pathways. Consistent with biological functions for RPA32C in DNA repair pathways, an RPA32C truncation mutant in budding yeast displays mutator and hyper-recombination phenotypes ( 39 ).
|
16935876_p8
|
16935876
|
RPA32C interactions
| 4.425988 |
biomedical
|
Study
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en
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Whether DNA replication proteins interact with RPA32C has been controversial. Multiple lines of evidence in the literature implicate RPA32 in SV40 DNA replication. Antibodies against RPA32 specifically inhibit SV40 replication in vitro ( 40 , 41 ). In the context of trimeric RPA, RPA32 can be directly cross-linked to nascent RNA–DNA primers ( 42 ) and the RPA trimerization core alone (RPA70C–RPA32D–RPA14) was shown recently to bind to a primer–template junction ( 38 ) . Binding of human RPA32 to the viral replicative helicase T antigen has been reported previously ( 43 , 44 ), but not confirmed by others ( 45 – 47 ). Similarly, RPA mutants with deletions in the C-terminal domain of RPA32 supported SV40 replication poorly in one study, but displayed nearly wild-type activity in another investigation ( 44 , 45 ).
|
16935876_p9
|
16935876
|
RPA32C interactions
| 4.254291 |
biomedical
|
Study
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[
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[
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en
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To resolve the controversy, the physical interaction of RPA32C with SV40 T antigen was re-examined recently in detail ( 48 ). NMR studies of RPA32C interaction with the origin DNA-binding domain of T antigen (residues 131–259) revealed that T antigen binds to virtually the same surface of RPA32C bound by DNA repair and recombination proteins ( 20 ). However, the T antigen surface involved in the interaction is composed primarily of two loops rather than the alpha helix used by the repair and recombination proteins. RPA32C-T antigen binding is weak ( K d ∼ 60 μM) and relies in part on electrostatic interactions between acidic residues in RPA32C and basic residues in T antigen. Charge reverse mutations in either protein reduced the binding affinity by an order of magnitude. Interestingly, the charge reverse mutations in RPA32C also strongly reduced the ability of T antigen to stimulate primer synthesis on RPA-coated ssDNA, but did not inhibit primer extension. Taken together, the data confirm that RPA32C interaction with T antigen is important for primosome activity in SV40 DNA replication, provide insight into the structural interaction and suggest that T antigen may play a role in displacing RPA from ssDNA with a 3′ → 5′ polarity, permitting DNA polymerase-primase to begin replication.
|
16935876_p10
|
16935876
|
RPA32C interactions
| 4.591006 |
biomedical
|
Study
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[
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0.0002294231962878257
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en
| 0.999996 |
RPA bound to ssDNA ahead of an elongating DNA polymerase on a primed template must also be displaced, but the mechanism is not known. It seems likely that the binding mode of RPA at a primer–template junction may be one that utilizes primarily the trimerization core of RPA, with RPA70C and RPA32D contacting the 3′OH of the primer and the ssDNA template ( 38 ). The RPA14 subunit plays a crucial role in stabilizing the trimerization core for interaction with the partial duplex, as a mutant RPA lacking the 14 kDa subunit did not properly recognize the 3′ end of the primer at the primer–template junction or support primer extension in the SV40 replication system ( 49 ). Notably, the mutant RPA also failed to support primer synthesis, implying that T antigen-mediated RPA displacement or polymerase-primase loading requires the intact trimerization core, as well as interaction between RPA32C and T antigen. Although the detailed role of the trimerization core in these events remains to be determined, it seems reasonable to speculate that it is important to form or stabilize the compact conformation of RPA .
|
16935876_p11
|
16935876
|
RPA32C interactions
| 4.569215 |
biomedical
|
Study
|
[
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0.0005107609322294593,
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[
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0.00020718461018987
] |
en
| 0.999996 |
These studies raise the question of whether RPA32C binding to other proteins ( Table 1 ) may facilitate similar RPA displacement from ssDNA, coupled with loading of an incoming processing protein. One example of RPA involvement in displacing a DNA-bound protein and loading subsequent proteins is in nucleotide excision repair. RPA is required for global genome nucleotide excision repair ( 50 ) and cannot be substituted by other ssDNA-binding proteins, consistent with the specific interactions of RPA with excision repair proteins XPA, XPG and XPF-ERCC1 ( Table 1 ). XPA and RPA bind and stabilize the open complex after damage-recognition by XPC-hHR23B and controlled local separation of the two strands by TFIIH ( 51 ). The joint recognition of a damage site by XPA and RPA has been suggested to serve as a ‘double-check’ before the assembly of excision endonucleases at the site ( 52 ). XPA binding to RPA at the DNA lesion is also crucial for the ability of XPA–RPA to displace XPC–hHR23B from DNA before the assembly of XPG and XPF-ERCC1 endonucleases ( 53 , 54 ). The polarity of RPA bound to the undamaged strand appears to spatially coordinate the assembly of XPG on the 3′ end of the damaged strand and XPF–ERCC1 on the 5′ end ( 22 ). Excision of the damaged strand leads to RPA bound to a gapped DNA, positioned such that it would interact through RPA70C and RPA32D with the 3′OH at the gap and the undamaged strand to coordinate assembly of RFC, PCNA and DNA polymerase delta to repair the gap ( 16 ).
|
16935876_p12
|
16935876
|
RPA32C interactions
| 4.643672 |
biomedical
|
Study
|
[
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en
| 0.999998 |
Mapping of protein interaction sites in RPA70 has been challenging due to its complex domain structure and the multiple linkers . Three protein interaction modules have been identified so far: the N-terminal domain RPA70N (residues 1–120), RPA70A and residues 168–308/327, which span domain 70A (181–290), part of domain 70B, and the short linker between them ( Table 1 ). The 70N and 70A interacting regions are connected by a long, apparently unstructured linker (residues 120–180) ( 55 , 56 ), but functional interaction of the linker with other proteins has, to our knowledge, not been observed.
|
16935876_p13
|
16935876
|
RPA70 interactions
| 4.254529 |
biomedical
|
Study
|
[
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[
0.9992959499359131,
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en
| 0.999997 |
The 70N domain (residues 1–120) assumes an OB-fold, as determined by NMR ( 55 ) and X-ray crystallography ( 32 ). Although it binds weakly to ssDNA ( 30 , 32 ), it lacks the conserved aromatic residues that confer high-affinity ssDNA binding. However, RPA70N interacts physically with the tumor suppressor p53 ( 57 – 59 ). The structural basis of this interaction has been characterized recently in detail ( 32 ). RPA70N binds to the transactivation domain of p53 (residues 38–57), inducing the formation of two amphipathic helices. Hydrophobic residues in helix 2 of the p53 peptide bind to 70N, while the acidic residues on the opposite face of the helix are exposed to solvent. This interaction mimics those described previously for weak binding of RPA70N to ssDNA and a pseudo-phosphorylated mutant RPA32N peptide ( 30 – 32 ). Interestingly, these ligands compete directly with p53 for binding to 70N, leading Bochkareva et al . ( 32 ) to speculate that this competition may be one component of a threshold-sensitive response to DNA damage. Exposure of p53–RPA complex to either damage-activated protein kinases that hyperphosphorylate RPA32N or to large amounts of ssDNA would stimulate release of active p53.
|
16935876_p14
|
16935876
|
RPA70 interactions
| 4.642868 |
biomedical
|
Study
|
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0.0002478431269992143
] |
en
| 0.999997 |
RPA70N was also shown recently to interact with the nucleosome remodeling complex FACT (facilitates chromatin transcription) ( 60 ). This phylogenetically conserved complex is required for both transcription and replication of nucleosomal DNA. Genetic analysis in yeast indicates that the requirement for FACT in transcription is genetically separable from that in chromatin replication. The Pob3 subunit of yeast FACT binds specifically to the basic cleft of RPA70N based on detailed structural models, genetic and biochemical analysis. FACT interaction with RPA appears to be important in vivo for deposition of acetylated histones H3 and H4 in nucleosomes on newly replicated DNA, but the details of this process and the role that RPA plays in it remain unknown.
|
16935876_p15
|
16935876
|
RPA70 interactions
| 4.406322 |
biomedical
|
Study
|
[
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[
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] |
en
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RPA70A alone has been reported to be sufficient to bind papillomavirus E1 helicase ( 47 ), SV40 T antigen ( 47 , 61 ), XPA ( 62 ) and human Rad51 recombinase ( 63 ). Binding of RPA70A to an acidic N-terminal peptide of human Rad51 (residues 1–93) has been investigated structurally in detail ( 63 ). The Rad51 peptide binds in the basic ssDNA-binding cleft of RPA70A, mimicking its interaction with ssDNA and suggesting a potential competition. Mutational analysis of Rad51 indicated that this interaction contributes to the ability of Rad51 to displace RPA from ssDNA to form a presynaptic Rad51–ssDNA filament. Mechanistically, Rad51N is proposed to capture an RPA molecule that dissociates from an overhanging 3′ ssDNA, spontaneously or mediated by another protein, thereby preventing its reassociation with ssDNA and positioning the bound Rad51 molecule to bind to the ssDNA through a separate domain. Once a few Rad51 molecules are loaded on the ssDNA, Rad51 filament formation driven by ATP hydrolysis leads to RPA displacement ( 63 ).
|
16935876_p16
|
16935876
|
RPA70 interactions
| 4.563111 |
biomedical
|
Study
|
[
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0.0004921193467453122,
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0.00020408298587426543
] |
en
| 0.999996 |
The largest protein interaction module of RPA70 spans domains 70A and B (residues 168–308/327) and is reported to interact with the primase subunits of DNA polymerase alpha-primase, the SV40 T antigen helicase and the RecQ family Werner and Bloom Syndrome helicases ( Table 1 ) ( 45 , 64 – 67 ). There is evidence that these interactions have physiological importance. For example, RPA stimulated the DNA unwinding activity of Werner helicase fragments capable of binding to RPA ( 66 ). However, the RPA70 fragment 168–308/327 encompasses disordered peptides at both the N- and C-termini, raising the question of whether its physical interactions with other proteins are mediated through the structured portion of the RPA fragment, or whether physical interactions with a partner protein may structure the disordered regions of the RPA fragment.
|
16935876_p17
|
16935876
|
RPA70 interactions
| 4.311061 |
biomedical
|
Study
|
[
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[
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0.0000671049565426074
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en
| 0.999997 |
RPA70 interactions with the primase subunits of DNA polymerase alpha-primase ( 45 , 64 , 67 ) are thought to aid polymerase-primase in primer–template binding or primer extension. Interestingly RPA enhances both the processivity and fidelity of primer extension by polymerase-primase ( 45 , 68 ). Since other ssDNA-binding proteins do not display this enhancement, specific RPA–primase interactions, the 3′primer–template junction-binding mode of RPA or both may be involved. RPA has thus been suggested to serve as a ‘fidelity clamp’ for polymerase-primase. The ability of RPA to facilitate primer extension by other DNA polymerases (lambda, delta) suggests that this function of RPA may be more general ( 16 , 40 , 69 ). Additional work will be required to elucidate the structural basis of RPA70 interaction with these binding partners and clarify its functional roles.
|
16935876_p18
|
16935876
|
RPA70 interactions
| 4.411973 |
biomedical
|
Study
|
[
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[
0.9933257102966309,
0.000594753073528409,
0.005944219417870045,
0.0001352447725366801
] |
en
| 0.999997 |
A number of other DNA damage signaling and processing proteins have been shown recently to interact directly or indirectly with RPA ( Table 1 ): Rad17 clamp loading complex ( 70 , 71 ), Rad9 clamp subunit ( 72 ), ATRIP ( 14 , 73 , 74 ), 53BP1 ( 75 ), BRCA2 ( 76 ), Mre11–Rad50–Nbs1 ( 77 ) and nucleolin ( 78 , 79 ). Future characterization of these binding interactions with RPA and their mechanistic role in DNA processing should yield deeper understanding of DNA damage responses.
|
16935876_p19
|
16935876
|
RPA70 interactions
| 4.129478 |
biomedical
|
Study
|
[
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[
0.9409137964248657,
0.0015278487699106336,
0.05734262987971306,
0.00021567119983956218
] |
en
| 0.999997 |
Interestingly, a number of DNA processing proteins bind to both RPA70 and RPA32C (XPA, Rad52, SV40 T antigen) ( Table 1 ). In Rad52 and T antigen, the same surface that binds to RPA32C also binds to RPA70. These observations raise new questions about the functional role of the dual interaction. Do these proteins interact with both RPA sites simultaneously to strengthen the complex, or do they interact with one site at a time, possibly with different functional consequences? How does ssDNA influence protein interaction with the two RPA sites?
|
16935876_p20
|
16935876
|
Competition and coordination among RPA-binding partners
| 4.232841 |
biomedical
|
Study
|
[
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0.00014626407937612385,
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0.99184650182724,
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0.004152151755988598,
0.00013404562196228653
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en
| 0.999997 |
The interaction of Rad52 with RPA in homologous recombination has been investigated in detail [for a review see ( 80 )]. In yeast and in vertebrates, RPA assembles at double-strand breaks, preceding the association of Rad51 recombinase ( 81 , 82 ). Although it is not clear how the DNA at the break is resected to create 3′ ssDNA ends, RPA must be quickly loaded on the ssDNA, either through diffusion or a protein-mediated mechanism, preventing formation of secondary structures ( 83 ). Rad51 must then displace RPA to generate a recombinogenic Rad51–ssDNA filament. In yeast, Rad52 association with RPA plays an important role in mediating Rad51 assembly on RPA-coated ssDNA ( 84 – 86 ). The Rad52-mediated RPA–Rad51 exchange mechanism involves Rad52 binding to RPA–ssDNA to form a ternary complex ( 85 ). Since a separate domain of Rad52 binds to Rad51, it is possible that Rad52-mediated remodeling of RPA–ssDNA complexes from an extended binding mode into a compact one may facilitate Rad51 loading on the newly accessible ssDNA . Whether Rad52 binding to RPA32C or RPA70AB or both is required for Rad51 filament formation is not known. Once the Rad51–ssDNA complexes are formed, Rad51 interactions with RPA70A may accelerate filament formation as discussed above. In addition, the basic region of yeast RPA70N is essential for Rad51-mediated RPA displacement and strand invasion, perhaps by facilitating RPA remodeling ( 83 , 87 ). Vertebrate Rad52 also binds to RPA and can mediate Rad51 loading on RPA–ssDNA in vitro , but is not essential for Rad51 filament formation in vivo ; instead, Rad51 paralogs appear to mediate Rad51 filament assembly through an unknown mechanism ( 80 , 84 , 85 , 88 – 90 ).
|
16935876_p21
|
16935876
|
Competition and coordination among RPA-binding partners
| 4.67157 |
biomedical
|
Review
|
[
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en
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In addition to mediating RPA displacement from ssDNA and loading of incoming proteins, DNA processing proteins may be capable of stimulating RPA binding to ssDNA. It has been speculated that RPA interaction with some DNA helicases may enable them to actively place RPA on ssDNA as it emerges from the helicase complex. Interaction of the Werner and Bloom syndrome helicases with RPA70 stimulates their unwinding activity on long duplexes, perhaps by facilitating RPA binding to ssDNA ( 65 , 66 ). If helicases do load RPA on ssDNA, the spatial orientation of RPA bound to the helicase, the polarity of helicase movement during strand displacement, and the structure or perhaps sequence of the DNA may govern whether RPA is loaded on ssDNA, the strand on which it loads, or the binding mode in which it is loaded . Whether these helicases can also displace RPA from ssDNA to mediate loading of an incoming DNA processing protein is not known. If so, one or more features of the protein–ssDNA complex must determine whether RPA is loaded or displaced.
|
16935876_p22
|
16935876
|
Competition and coordination among RPA-binding partners
| 4.43419 |
biomedical
|
Study
|
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en
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The complexity of DNA processing pathways raises questions about how the individual reaction steps are ordered, and how rapid progression through the processing pathway is achieved. In the SV40 replication pathway, RPA has been proposed to coordinate the activities of the replication proteins through competition-based switches, in which proteins ‘trade places’ on ssDNA through specific RPA-binding sites ( 16 ). In each exchange, the next protein to enter into processing has a greater affinity for RPA than the preceding one, which allows it to compete for RPA on the ssDNA when the preceding protein dissociates. This successive exchange of replication proteins, known as the hand-off mechanism, is proposed to be a general mechanism in replication, repair and recombination pathways ( 17 , 20 ). However, the in vivo abundance of certain incoming proteins may not be sufficient to compete with the preceding protein in the pathway. Moreover, successively increasing the affinity of protein–protein interactions as pathway progresses could limit the rapid protein exchanges necessary to complete the pathway.
|
16935876_p23
|
16935876
|
A mechanistic model for protein-mediated RPA dissociation from DNA
| 4.444973 |
biomedical
|
Study
|
[
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[
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0.0006040140287950635,
0.004169676452875137,
0.00014006035053171217
] |
en
| 0.999997 |
An alternative model for the protein hand-off mechanism would depend on the ability of RPA-interacting proteins to remodel the conformation of RPA from an extended, stable binding mode to a more compact form with lower affinity for ssDNA . Table 1 reveals a general pattern of interactions in which some processing proteins contact both RPA32C and RPA70A or AB. This common pattern suggests that these RPA-binding partners may remodel RPA conformation in a similar manner. The protein-mediated remodeling of RPA could thus be coupled to its different ssDNA-binding modes . The incoming protein that binds and induces RPA to shift from an extended to a compact conformation on ssDNA could then, in concert, gain access to the ssDNA. Since the C and D domains of RPA bound to the 3′ end of ssDNA have lower affinity for ssDNA, an incoming protein that binds to RPA32C might gain access to ssDNA at the 3′ end. Binding of RPA70AB to the same incoming protein could induce a compact weaker ssDNA-binding mode, allowing the incoming protein displace RPA and load either itself or a piggy-backed protein on to the ssDNA made accessible by the partially dissociated RPA.
|
16935876_p24
|
16935876
|
A mechanistic model for protein-mediated RPA dissociation from DNA
| 4.577449 |
biomedical
|
Study
|
[
0.9992408752441406,
0.0004858839965891093,
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[
0.9973205924034119,
0.001209536218084395,
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0.00018474938406143337
] |
en
| 0.999998 |
In the case of SV40 T antigen-mediated primer synthesis on RPA-coated ssDNA, T antigen must bind to RPA to allow primer synthesis [( 48 ) and references therein]. We suggest a model in which T antigen binds transiently to RPA, inducing a conformation change on ssDNA, and concurrently loads DNA polymerase-alpha-primase ( 48 ). RPA domains C and D bound to the 3′ end of ssDNA undergo rapid association and dissociation. In the absence of T antigen, RPA rapidly reassociates with ssDNA, preventing DNA polymerase-alpha-primase from binding to the template ( 29 ). In the presence of hexameric T antigen helicase, polymerase-primase binds to the helicase domain of T antigen ( 91 ) and RPA32C binds to the origin DNA-binding domain of T antigen . We suggest that RPA32C and RPA70AB interaction with the T antigen hexamer remodels the conformation of RPA to a compact, weaker DNA-binding mode, causing the release of a short stretch of ssDNA. In concert, the polymerase-primase bound to T antigen binds to the free ssDNA and begins primer synthesis . Dissociation of the weakly bound RPA and T antigen facilitates primer extension by the polymerase-primase . Although this model is still tentative, it is consistent with the data available in the literature, provides a plausible mechanistic explanation for hand-off and is amenable to further experimental testing.
|
16935876_p25
|
16935876
|
A mechanistic model for protein-mediated RPA dissociation from DNA
| 4.658372 |
biomedical
|
Study
|
[
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[
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en
| 0.999996 |
It has been known for more than a decade that RPA becomes phosphorylated, primarily in the N-terminus of RPA32 , in response to cell cycle progression or DNA damaging agents, but the structural and functional significance of the modifications is still not well understood [reviewed by ( 9 , 92 )].
|
16935876_p26
|
16935876
|
Regulation of RPA structure and function by phosphorylation
| 3.64945 |
biomedical
|
Review
|
[
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en
| 0.999996 |
The N-terminal 33 residues of human RPA32 contain at least 7 sites that can be modified in vivo and in vitro and give rise to 4 differentially phosphorylated forms separable by denaturing gel electrophoresis ( 93 , 94 ). Cyclin-dependent kinases modify serine residues 23 and 29 in mitotic cells, reducing the ability of the phosphorylated RPA to interact with purified DNA polymerase alpha-primase, ATM and DNA-PK ( 93 , 95 ). DNA-PK, ATM and ATR are involved in modifying threonine 21 and serine 33 in response to various DNA damaging agents in vivo , leading to hyperphosphorylated forms of RPA ( 96 , 97 ). The hyperphosphorylated forms of RPA also contain phosphorylated serines 4 and 8, as well as at least one phosphoserine in residues 11–13, but the kinases that modify these sites in vivo are not yet known ( 98 ). Interestingly, the kinases required and the time course of RPA phosphorylation varied depending upon the damaging agent ( 97 ). Focus formation of RPA and gammaH2AX was ATR-dependent and occurred rapidly after camptothecin exposure, but RPA32 hyperphosphorylation occurred later and required DNA-PK activity. DNA-PK was also required for RPA hyperphosphorylation in UV-treated cells ( 99 ). Both ATR-dependent RPA focus formation and hyperphosphorylation occurred more slowly after hydroxyurea exposure, but hyperphosphorylation did not require DNA-PK ( 97 ). Rad51, Rad52 and ATR were reported to preferentially co-immunoprecipitate with hyperphosphorylated RPA from extracts of UV or camptothecin-treated human cells, but it is not clear whether these interactions with phospho-RPA are direct or indirect ( 72 ).
|
16935876_p27
|
16935876
|
Regulation of RPA structure and function by phosphorylation
| 4.632324 |
biomedical
|
Study
|
[
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[
0.9902908205986023,
0.0005855277413502336,
0.008863436989486217,
0.0002602272143121809
] |
en
| 0.999997 |
Whether the specific sites phosphorylated in RPA correlate with specific changes in RPA structure or function is an important open question. For instance, mutation of RPA32 Thr21, Ser33 or both had little effect on camptothecin-induced RPA32 hyperphosphorylation ( 97 ). It is conceivable that mere induction of massive negative charge in RPA32N is sufficient to alter RPA structure and function. Based on this rationale, some efforts to elucidate the structural and functional significance of RPA hyperphosphorylation have employed mutant forms of RPA designed to mimic the hyperphosphorylated protein, with substitution of aspartate for phosphorylatable residues in RPA32N, or of alanine as a control ( 31 , 100 , 101 ). Negatively charged mutant RPA32N was excluded from chromosomal replication centers in human in a manner proportional to the negative charge, and the alanine-substituted mutant used as a control was not excluded ( 101,102 ). Moreover, hyperphosphorylated wild-type RPA also failed to co-localize with replication centers. These results are consistent with the reduced affinity of hyperphosphorylated RPA for DNA polymerase alpha-primase ( 93 , 95 ).
|
16935876_p28
|
16935876
|
Regulation of RPA structure and function by phosphorylation
| 4.358834 |
biomedical
|
Study
|
[
0.9994646906852722,
0.000285067071672529,
0.00025024975184351206
] |
[
0.9988335967063904,
0.00021649908740073442,
0.0008665929199196398,
0.00008326597890118137
] |
en
| 0.999995 |
Does the negatively charged RPA32N also alter RPA structurally and if so, how? Early work on the ssDNA-binding modes of purified human RPA using scanning transmission electron microscopy established that RPA32N in the extended 30 nt binding mode on ssDNA was preferentially hyperphosphorylated by purified DNA-PK ( 33 ), implying that RPA32N might be more accessible in the extended binding mode and sequestered in the compact mode . Given the uncharged nature of unmodified RPA32N, it is easy to imagine that gross introduction of negative charge might make it difficult to reverse the extended binding mode and re-sequester RPA32N. Hyperphosphorylation would thus be expected to shift the equilibrium distribution of RPA conformations to favor the extended binding mode, which binds to ssDNA with higher affinity than the compact modes . Lower levels of hyperphosphorylated RPA in the compact binding mode could explain its exclusion from replicating chromatin, since the 8–10 nt and the primer-junction-binding modes are thought to play a central role in rapidly cycling RPA on and off ssDNA during replication . Moreover, the greater binding affinity of the extended conformation would ensure that ssDNA in cells exposed to DNA damaging agents remains shielded from hairpin formation or nucleases until completion of repair. Counter to these predictions, binding of hyperphosphorylated RPA to 8–30 nt ssDNA and primer–junction templates in vitro was either reduced or equal to that of unmodified RPA ( 31 , 93 – 95 ). This paradox remains unresolved. Similarly, recent in vitro studies have suggested that hyperphosphorylated RPA32N may compete with ssDNA, binding to the basic cleft in RPA70N ( 31 , 32 ) or in RPA70B ( 94 ). These findings are consistent with the interpretation that hyperphosphorylated RPA does not localize in chromosomal replication centers ( 101,102 ), but do not explain how ssDNA remains protected in cells that have suffered DNA damage. Thus, much important work remains to understand the effects of RPA32N hyperphosphorylation on the quaternary structure of RPA.
|
16935876_p29
|
16935876
|
Regulation of RPA structure and function by phosphorylation
| 4.875045 |
biomedical
|
Study
|
[
0.9981732368469238,
0.0010212260531261563,
0.000805520627181977
] |
[
0.9591707587242126,
0.0011779085034504533,
0.0389900840818882,
0.0006613312289118767
] |
en
| 0.999998 |
RPA is the common denominator in many DNA processing pathways and is found on ssDNA from the time it is created by a DNA helicase or nuclease until the duplex DNA is restored upon completion of each processing pathway. The dynamic nature of these pathways has favored the evolution of modular proteins with multiple domains capable of interacting with multi-valent ligands. The modular interaction mechanism allows these proteins to associate and dissociate readily from each other. RPA is a prime example of such a modular protein. Its ability to adopt at least three different conformations on ssDNA and shift from one to another under the guidance of DNA processing proteins that interact with it suggests that RPA remodeling plays a major role in guaranteeing the integrity of ssDNA and its orderly processing. Future studies of RPA will need to explore the quaternary structure of the protein, the intramolecular interactions between domains and the regulation of RPA interactions by protein phosphorylation. This work may reveal in greater detail how this RPA remodeling takes place and whether general patterns of RPA remodeling may be conserved from one pathway to another.
|
16935876_p30
|
16935876
|
SUMMARY AND PERSPECTIVE
| 4.539838 |
biomedical
|
Study
|
[
0.9991188645362854,
0.0005288797547109425,
0.0003523502964526415
] |
[
0.9664695858955383,
0.0014831838198006153,
0.0316869355738163,
0.000360305915819481
] |
en
| 0.999998 |
Homologous recombination (HR) is a high fidelity and template-dependent DNA repair pathway found in all organisms studied. HR serves in the non-mutagenic tolerance of DNA damage, in the repair of complex DNA damage, such as single-stranded DNA (ssDNA) gaps, double-stranded DNA breaks (DSBs) and interstrand crosslinks, as well as in the recovery of stalled and collapsed replication forks ( 1 , 2 ). Historically prominent is the role of HR during prophase of the first meiotic division, where it contributes to high fidelity segregation of the homologs and to the generation of genetic diversity among the meiotic products.
|
16935872_p0
|
16935872
|
INTRODUCTION
| 4.43769 |
biomedical
|
Review
|
[
0.9980612397193909,
0.0008378600468859076,
0.0011009424924850464
] |
[
0.31044071912765503,
0.017056839540600777,
0.6712942719459534,
0.0012082310859113932
] |
en
| 0.999997 |
RAD54 is a core constituent of the RAD52 epistasis group that encodes the proteins that are essential for HR in eukaryotes. Rad54 protein is a member of the Snf2-family of SF2 helicases that contains many prominent chromatin-remodeling proteins including Snf2, ISWI and others. This group of proteins shares a common core that includes seven motifs proposed to identify helicases ( 3 ). However, rather than operating like DNA helicases, which are capable of separating the strands of duplex DNA, the Snf2-related proteins are viewed as motor proteins that translocate on duplex DNA and remodel specific protein–duplex DNA complexes ( 4 ). The particular functions of these proteins appear to involve specific protein interactions mediated by domains outside the core motor domain. The budding yeast Saccharomyces cerevisiae genome encodes 17 Snf2-related proteins ( Table 1 ). Interestingly, at least seven of them, Rad54, Rdh54/Tid1, Rad5, Rad16, Rad26/CS-B, as well as the Ino80 and Swr1 complex, have specific functions during DNA repair.
|
16935872_p1
|
16935872
|
INTRODUCTION
| 4.513556 |
biomedical
|
Study
|
[
0.9993676543235779,
0.0002967816253658384,
0.0003355926019139588
] |
[
0.9975898265838623,
0.0006786598823964596,
0.00162394845392555,
0.00010752541129477322
] |
en
| 0.999997 |
Previous reviews provide excellent overall outlines of HR and the RAD52 group proteins ( 1 , 5 – 8 ), as well as detailed discussions of the Snf2-related chromatin remodeling factors ( 9 – 11 ). In this review, we focus on the Rad54 protein. Versatile like the proverbial Swiss Army knife, Rad54 has been postulated to function at multiple stages during HR. Biochemical analyses of complex in vitro recombination assays led to a number of mutually non-exclusive models, as reviewed previously ( 12 ). We will discuss results from genetic, biochemical and cytological experiments, as well as insights from the recently accomplished determinations of the Rad54 protein structure to highlight the mechanistic models for the function of Rad54 during HR.
|
16935872_p2
|
16935872
|
INTRODUCTION
| 4.163552 |
biomedical
|
Review
|
[
0.9891380667686462,
0.0052347383461892605,
0.005627189762890339
] |
[
0.004610765725374222,
0.0015218392945826054,
0.9932771325111389,
0.0005901880213059485
] |
en
| 0.999996 |
HR can be divided conceptually into three stages . First, in pre-synapsis a recombination-proficient DNA substrate (tailed DSB or gap) is generated either by specific enzymatic action or as a consequence of genotoxic stress (e.g. replication problems). Second, synapsis generates a physical connection (D-loop) between the recombinogenic substrate and an intact homologous duplex DNA template leading to the formation of heteroduplex (or hybrid) DNA. Third, in post-synapsis contiguous DNA strands are restored by priming DNA synthesis from the invading 3′ end on the template DNA and resolving the ensuing junction intermediates. These basic features of HR are often studied and mostly schematized in the context of initiation by a DSB , but initiation from a ssDNA gap is highly relevant in the context of spontaneous DNA damage and in the recovery of stalled replication forks. HR comprises a number of interrelated pathways that share basic mechanistic aspects ( 1 ). The original double-strand break repair model involves a double-Holliday junction intermediate, whose resolution leads to crossover and non-crossover outcomes ( 13 ). Later work identified an asymmetry between the two ends of the DSB, leading to the synthesis-dependent strand annealing model , where the invading strand retreats after DNA synthesis and anneals with the second end [reviewed in ( 1 )]. In addition, break-induced replication was proposed to copy an entire chromosome arm by a replication fork assembled at the D-loop, skipping the involvement of the second end of the DSB ( 14 ).
|
16935872_p3
|
16935872
|
Overview
| 4.684733 |
biomedical
|
Review
|
[
0.9902933835983276,
0.004890022333711386,
0.004816528409719467
] |
[
0.07544056326150894,
0.002398937474936247,
0.9208845496177673,
0.0012759403325617313
] |
en
| 0.999996 |
The proteins encoded by the RAD52 group of genes form the core of the HR machinery ( 5 – 7 ). The Rad50-Mre11-Xrs2/Nbs1 complex, Exo1 and some unidentified nuclease(s) are involved in processing breaks to generate recombinogenic tailed substrates. The ssDNA binding protein, RPA, binds the ssDNA tails at the break site, to eliminate any possible secondary structure and likely to recruit other proteins to ssDNA. The mediator proteins, Rad52 and the Rad51 paralogs (Rad55-Rad57 in budding yeast and Rad51B, Rad51C, Rad51D, Xrcc2, Xrcc3 in humans), orchestrate the formation of the pre-synaptic RAD51 filament on RPA-coated ssDNA. The human breast cancer tumor suppressor protein Brca2 is thought to function at this step in pre-synapsis as well ( 15 ). During synapsis, the Rad51 filament performs homology search and DNA strand invasion. While the enzymatic steps and proteins involved in pre-synapsis and synapsis are comparably well understood from in vivo and in vitro studies ( 5 – 7 , 16 ), the enzymatic requirements for the later recombination steps in post-synapsis, including DNA synthesis, branch migration and junction resolution are less well defined. The potential roles of Rad54 protein are discussed later.
|
16935872_p4
|
16935872
|
Overview
| 4.771077 |
biomedical
|
Study
|
[
0.998654842376709,
0.0007689710473641753,
0.0005761397769674659
] |
[
0.9354990720748901,
0.0015843420987948775,
0.06235850229859352,
0.0005580424331128597
] |
en
| 0.999997 |
The RAD54 gene was originally identified in three parallel S.cerevisiae mutant screens for ionizing radiation (IR) sensitive mutants that showed little sensitivity to ultraviolet (UV) radiation ( 17 – 19 ). Together with rad51 and rad52 mutants, rad54 mutants are the most IR-sensitive single mutants in budding yeast, also exhibiting extraordinary sensitivity to alkylating agents (e.g. methyl methanesulfonate), crosslinking agents ( cis -platinum and mitomycin C), the topoisomerase I inhibitor camptothecin and a host of other agents inducing DSBs. Most Rad54-deficient cells cannot survive a single DSB introduced by the HO endonuclease at the MAT locus ( 20 ), but rad54 mutants grow almost as well as wild-type cells in the absence of induced DNA damage. These results indicate that DSBs occur only rarely during normal mitotic growth in budding yeast, suggesting that single-stranded gaps may act as initiating DNA lesion for spontaneous recombination.
|
16935872_p5
|
16935872
|
The RAD54 gene
| 4.334841 |
biomedical
|
Study
|
[
0.9995121955871582,
0.0002429899905109778,
0.0002449065214022994
] |
[
0.9989811778068542,
0.0003396258398424834,
0.0005990638164803386,
0.00008011452155187726
] |
en
| 0.999998 |
RAD54 is required for spontaneous and induced mitotic recombination, and rad54 mutants show a reduction to the same extent as rad51 or rad52 mutants in recombination assays that require DNA strand invasion ( 21 – 23 ). While rad51 and rad54 mutants display highly similar phenotypes with respect to their damage sensitivities, recombination, chromosome loss and mutator phenotypes in mitotic cells, their meiotic phenotypes differ ( 1 , 6 , 7 ). Unlike rad51 cells that essentially do not generate viable meiotic products (spores), 25–65% of the spores of a rad54 meiosis are viable ( 21 , 24 ). Return-to-growth experiments and analysis of the meiotic products identified only relatively subtle meiotic recombination-defects in rad54 cells. This is likely the result of partial redundancy between Rad54 and the related Rdh54/Tid1 protein (see below) in meiosis ( 21 ). In the rad54 rdh54 double mutant, spore viability is reduced to the level of rad51 mutants ( 21 ). The redundancy between Rad54 and Rdh54/Tid1 is primarily noted during meiosis, where it may reflect a specific role of Rdh54/Tid1 in engaging in recombination between homologs, whereas Rad54 may play a more dominant role in sister chromatid interaction during meiosis ( 21 , 25 , 26 ). This functional specialization during meiosis of these two Snf2-related recombination factors may hold a key to understanding how cells direct meiotic recombination between homologs and suppress non-productive sister chromatid interactions.
|
16935872_p6
|
16935872
|
The RAD54 gene
| 4.680061 |
biomedical
|
Study
|
[
0.9991089701652527,
0.0005362253286875784,
0.0003547946398612112
] |
[
0.9948114156723022,
0.0007547349669039249,
0.004178254399448633,
0.0002555962710175663
] |
en
| 0.999995 |
Bona fide Rad54 homologs appear to be present in all eukaryotes studied. The proteins not only share extensive sequence homology in the motor core domain but also significant similarity in the Rad54-specific N-terminal extension. Compared to other eukaryotic Rad54 proteins, budding yeast Rad54 shows two insertions in the N-terminal domain . There are no Rad54 homologs in bacteria. A putative homolog has been identified in the archeaon Sulfolobus solfataricus but not other archaea ( 27 ). Genetic and biochemical evidence will be needed to support this notion, because due to the multitude of Snf2-related proteins it is difficult to assign homologous function based on sequence comparison.
|
16935872_p7
|
16935872
|
The RAD54 gene
| 4.258117 |
biomedical
|
Study
|
[
0.999444305896759,
0.0001722972810966894,
0.0003834283852484077
] |
[
0.9982447624206543,
0.0007888730033300817,
0.0008904706919565797,
0.00007592528709210455
] |
en
| 0.999996 |
Genetic analyses of the RAD54 gene in mouse and chicken confirm the importance of Rad54 for HR and provide valuable insights into the cellular and organismic consequences of a recombination defect in vertebrates ( 28 , 29 ). Disruption of the mouse RAD51 gene causes embryonic lethality ( 30 , 31 ), whereas disruption of the mouse RAD52 gene does not cause DNA damage sensitivity ( 32 ). RAD54 knockout mice are viable and provide a critical tool for the analysis of HR in mammals ( 28 , 33 ). The discrepancy between the vertebrate and yeast system with regards to the viability of rad51 mutants and the phenotypes of the rad52 mutants is presently not well understood. At the cellular level, Rad54-deficiency causes sensitivity to IR and interstrand crosslinking agents (e.g. mitomycin C) in mice, whereas at the organismic level Rad54-deficient mice are not overtly IR-sensitive but display sensitivity to mitomycin C ( 28 ). This is likely a reflection of the more significant contribution of the NHEJ-pathway to DSB repair in mammals, because double mutants affecting both the HR and NHEJ pathways ( rad54 scid, rad54 lig4 ) display synergistic sensitivities ( 34 , 35 ). HR, as assayed by gene targeting and DNA damage-induced sister chromatid exchange, is reduced but not eliminated in rad54 mouse ES cells ( 28 , 36 ). Rad54-deficient mice do not exhibit an overt meiotic recombination defect ( 28 ), similar to the situation in budding yeast. In summary, the genetic data in yeast and vertebrates identify a critical role of Rad54 protein in HR in eukaryotyes.
|
16935872_p8
|
16935872
|
The RAD54 gene
| 4.655334 |
biomedical
|
Study
|
[
0.9987969398498535,
0.0006878087297081947,
0.0005151807563379407
] |
[
0.9023014307022095,
0.0011405880795791745,
0.09599437564611435,
0.0005636453279294074
] |
en
| 0.999997 |
Rad54 protein is a member of the Snf2-family of DNA-stimulated/dependent ATPases in the SF2 family of DNA helicases. In their core domain, all Rad54 proteins have the seven conserved Snf2-specific motifs that were proposed to be diagnostic of DNA helicases ( 3 ) . However, Rad54 (and all other Snf2-related proteins) fail to catalyze strand displacement reactions typical for DNA helicases. Rad54 protein displays dsDNA-specific ATPase activity with a turnover of 600–1000 ATP molecules per Rad54 molecule per minute on protein-free duplex DNA ( 37 – 39 ). Typical DNA helicases display ssDNA-dependent/enhanced ATPase activity and use the energy of ATP hydrolysis to translocate on ssDNA ( 40 ). Instead, Rad54 protein uses the energy of ATP hydrolysis to translocate on dsDNA inducing topological changes. On circular duplex DNA, Rad54 introduces unconstrained positive and negative supercoils and displaces a triplex-forming oligonucleotide, typical for a translocating motor protein ( 41 – 44 ). Direct imaging of Rad54–dsDNA complexes by scanning force microscopy identified supercoiled domains anchored by Rad54 protein, providing further evidence for a translocation model ( 45 ). Single-molecule experiments directly visualized Rad54 translocation on dsDNA, demonstrating highly processive movement at 300 bp/s ( 46 ). The basic biochemical activities of Rad54 protein, ATP hydrolysis and induction of topological change, are significantly stimulated in the presence of the Rad51-ssDNA/dsDNA filaments ( 37 , 42 , 43 ), suggesting that Rad54 functions in concert with Rad51 in vivo .
|
16935872_p9
|
16935872
|
The Rad54 protein
| 4.771012 |
biomedical
|
Study
|
[
0.9989598989486694,
0.0006464064354076982,
0.0003937137662433088
] |
[
0.9958223104476929,
0.0010378204751759768,
0.002767604310065508,
0.00037217492354102433
] |
en
| 0.999997 |
The X-ray crystallographic structures of the core domain of the zebrafish Rad54 protein ( 47 ) and of the core domain of the putative Rad54 homolog of S.solfataricus , also as a co-crystal with duplex DNA ( 48 ), provide the first and exciting glimpses at Snf2-related proteins. Figure 2B shows a model of the human Rad54 protein based on the experimentally determined zebrafish Rad54 structure ( 47 ). The protein folds into a structure of two lobes, each consisting of a RecA-like α/β domain found in helicases ( 40 ), which is topologically and structurally similar to that of SF2 helicases [e.g. RecG ( 49 )]. The Rad54 lobes contain Snf2-specific insertions (HD1 and HD2) in each lobe. The bi-lobal helicase domain structure is typical for SF2 DNA helicases and related SF1 helicases ( 40 ). This structural homology suggests that Rad54 (and the other Snf2-related proteins) use a mechanism to translocate on duplex DNA analogous to the inchworm mechanism proposed for helicases to translocate on ssDNA ( 47 , 48 ). In the Sulfolobus structure the relative orientation of the two lobes varies from that in zebrafish Rad54 and in SF2 helicases, such that the C-terminal lobe of the Sulfolobus protein is rotated along the x - and y -axis by about 90 and −110° respectively, compared to zebrafish Rad54. The domain (lobe) orientation of the DNA-free and DNA-bound forms of the Sulfolobus protein was very similar ( 48 ), suggesting that this difference is unlikely related to changes between the DNA-bound and unbound form of the proteins. The reasons for this structural difference between the Sulfolobus and zebrafish proteins are currently not understood. While the Sulfolobus protein is a structural homolog to Rad54 and displays dsDNA-specific ATPase activity as well as topological activities ( 48 ), its recombination function and in vivo role still remain to be tested. There is some uncertainty about the native sequence of the Sulfolobus protein; the difference is a 20 amino acid insertion/deletion between motifs IV and V ( 27 , 48 ), whose significance and impact is unclear. In summary, the biochemical, single-molecule, electron microscopic and X-ray structure data provide compelling evidence for a model, in which Rad54 translocates along duplex DNA.
|
16935872_p10
|
16935872
|
The Rad54 protein
| 4.702161 |
biomedical
|
Study
|
[
0.9988967180252075,
0.0007937137852422893,
0.00030952179804444313
] |
[
0.9932860732078552,
0.0007281031575985253,
0.005566025152802467,
0.000419776130001992
] |
en
| 0.999996 |
Starting with the seminal discovery that Rad54 stimulates Rad51 protein in DNA pairing reactions ( 38 ), much attention has been focused on Rad54 biochemistry, in particular in reconstituted recombination reactions with Rad51 protein and RPA using mostly protein-free (i.e. non-chromatin) templates. The physical interaction of Rad54 with Rad51 protein ( 41 , 50 – 52 ) suggested immediately a role of Rad54 either in the assembly or function of the Rad51-ssDNA filament, which performs the central homology search and strand invasion step in HR. The biochemical work identified functions of Rad54 at all three stages of recombination, pre-synapsis, synapsis and post-synapsis ( 12 ) , and is discussed below together with pertinent genetic, molecular and cytological data.
|
16935872_p11
|
16935872
|
MODELS FOR RAD54 FUNCTION
| 4.359915 |
biomedical
|
Study
|
[
0.9991987347602844,
0.00039210388786159456,
0.0004092145536560565
] |
[
0.8797668814659119,
0.0010455847950652242,
0.11879302561283112,
0.00039449549512937665
] |
en
| 0.999996 |
During pre-synapsis, mediator proteins function in the replacement of RPA with Rad51 on the single-stranded tails of the processed DSB . Rad54 was found to promote nucleation of Rad51 on RPA-coated ssDNA ( 53 ), as was previously reported for the Rad52 and Rad55-Rad57 proteins ( 7 , 54 ). This may be a reflection of Rad54 stabilizing the Rad51 filament by forming a co-complex with the Rad51-ssDNA filament ( 55 , 56 ). This pre-synaptic function of Rad54 is independent of its ATPase activity ( 57 ), as the Rad54-K341R mutant that is defective in ATP hydrolysis ( 58 ) functions as well as wild-type Rad54 protein in Rad51 filament stabilization ( 55 ). Genetic studies have demonstrated that the ATPase activity is crucial for in vivo Rad54 function and that the rad54-K341R mutant displays DNA damage sensitivities equivalent to the deletion mutant ( 58 , 59 ). Cytological studies in yeast, chicken DT40 cells, and mouse ES cells suggest that Rad54 is not necessary for the formation of Rad51 foci, which likely represent Rad51-ssDNA filaments and later recombination intermediates ( 16 , 60 – 63 ). Studies in mouse ES cells showed that the Rad51 foci formed in rad54 −/− cells were not as stable as in wild-type ES cells, leading to loss of Rad51 foci using methanol/acetone fixation instead of para-formaldehyde ( 41 , 63 ). Together these data suggest that a pre-synaptic role of Rad54 is not sufficient to reflect the critical ATPase-dependent function of Rad54 in recombination. Yet the pre-synaptic function may be necessary and important to target Rad54 to the pairing site, where it can engage its ATPase activity on duplex DNA ( 42 ). A test of this model will require specific Rad54 mutants that are defective in their association with the Rad51-ssDNA filament.
|
16935872_p12
|
16935872
|
Pre-synaptic models
| 4.679896 |
biomedical
|
Study
|
[
0.9988232254981995,
0.0007642654818482697,
0.0004124676634091884
] |
[
0.997703492641449,
0.0007562216487713158,
0.0012543504126369953,
0.0002860056411009282
] |
en
| 0.999998 |
During synapsis, the Rad51 nucleoprotein filament searches for homology on duplex target DNA and promotes DNA strand invasion forming a D-loop intermediate . Stimulation of Rad51-mediated joint molecule formation by Rad54 has been observed in in vitro recombination reactions including the D-loop assay (ssDNA or tailed DNA and supercoiled circular duplex DNA) and DNA strand exchange reaction (circular ssDNA and linear duplex DNA) ( 38 , 42 , 43 , 55 , 58 , 64 – 67 ). The stimulation requires the ATPase activity of Rad54 protein and involves species-specific contacts between both proteins, because it is only observed when Rad51 and Rad54 from cognate species are used. This suggests that the observed stimulation bears biological significance. ATP-dependent translocation of Rad54 on duplex DNA is likely the critical biochemical activity, but this motor activity can be employed in different modes ( 12 ) . Rad54 targeted to the duplex by the Rad51 filament may clear the donor DNA of nucleosomes (see below) or other duplex-bound proteins, including non-productively bound Rad51 protein. Moreover, Rad54 translocation on duplex DNA may aid the homology search process to efficiently sample target DNA. Alternatively, the topological activity of Rad54 on duplex DNA induces negative supercoiling, which favors unpairing of duplex DNA, possibly helping joint molecule formation by Rad51 protein. Although, duplex DNA has no inherent polarity, Rad54 is positioned on duplex DNA through the incoming Rad51-ssDNA filament, which might determine its direction of translocation. The exact architectural disposition of the interaction of Rad54 with the Rad51-ssDNA filament during pre-synapsis, synapsis and post-synapsis remains to be determined and will provide valuable insights into the mechanism of Rad54 function.
|
16935872_p13
|
16935872
|
Synaptic models
| 4.822589 |
biomedical
|
Study
|
[
0.9985319375991821,
0.0010561187518760562,
0.0004119637014809996
] |
[
0.9941569566726685,
0.0014653120888397098,
0.0037318323738873005,
0.0006459109135903418
] |
en
| 0.999996 |
Genetic analysis of the RAD52 epistasis group is consistent with a function of Rad54 at or after the Rad51 step, i.e. synapsis or post-synapsis ( 68 ). A particularly important synthetic lethal interaction of rad54 is the inviability of the rad54 srs2 double mutant ( 69 ). SRS2 encodes a 3′–5′ helicase that strips Rad51 from ssDNA ( 70 , 71 ), which provides a compelling mechanistic explanation for the anti-recombination function of Srs2 helicase ( 72 , 73 ). Importantly, only rad54 mutant cells, but not rad51, rad52, rad55 or rad57 mutants, are synthetically lethal with srs2 ( 69 ). The synthetic lethality of rad54 srs2 is suppressed by mutations in RAD51 , RAD52 , RAD55 or RAD57 ( 74 , 75 ). Such recombination-dependent lethality may be explained by a model, where the Rad51 filament itself or a joint molecule dependent on the Rad51 filament (D-loop) is a potentially lethal intermediate that can be reversed by Srs2 or alternatively requires Rad54 to move forward and complete recombination. Rad51, Rad52 and Rad55-Rad57 are critical for the assembly and structure of the Rad51 filament ( 1 , 5 – 7 ). Hence, these and other results from epistasis analysis of the RAD52 group ( 68 ) suggest that Rad54 may act after the assembly of the Rad51 filament during synapsis or post-synapsis. While these genetic data point to a critical role of Rad54 after pre-synapsis, the genetic analysis is unable to resolve synapsis and post-synapsis, and novel in vivo approaches are needed to resolve this question.
|
16935872_p14
|
16935872
|
Synaptic models
| 4.627859 |
biomedical
|
Study
|
[
0.9990848302841187,
0.0005458493833430111,
0.0003693592152558267
] |
[
0.9979349374771118,
0.0005604464095085859,
0.0013099734205752611,
0.0001946195843629539
] |
en
| 0.999997 |
Post-synapsis comprises the steps after D-loop formation and include priming of DNA synthesis from the invading 3′-OH end, branch migration, establishment and resolution of junction intermediates and the sealing of the strands by DNA ligase to restore two intact and contiguous duplex DNAs . Rad54 increases the rate of branch migration in an ATP-dependent fashion during the three-strand DNA strand exchange reaction ( 76 ). This activity requires species-specific protein interactions between the budding yeast Rad51 and Rad54 proteins, and is not observed when bacterial RecA protein or human Rad51 protein are used. It is unlikely that Rad54 acts like a junction motor analogous to the paradigmatic RuvB protein ( 8 ), as Rad54 does not display preference in binding DNA junctions (S. Kowalczykowski, personal communication).
|
16935872_p15
|
16935872
|
Post-synaptic models
| 4.461903 |
biomedical
|
Study
|
[
0.9994149208068848,
0.00033206361695192754,
0.0002530153433326632
] |
[
0.9973234534263611,
0.00177069753408432,
0.0007244325242936611,
0.00018142654153052717
] |
en
| 0.999996 |
Much attention has been focused on the assembly of protein complexes during recombination, in particular on the Rad51 filament, but these complexes also need to be disassembled to release their product DNA. In vitro this is often accomplished by treatment with proteinase K and detergent, which experimentally sidesteps this requirement. After DNA strand exchange, Rad51 is bound to the heteroduplex DNA product, and direct biochemical evidence shows that Rad51, unlike bacterial RecA protein, is extremely slow to turnover and release duplex DNA upon ATP hydrolysis ( 37 , 77 , 78 ). This is also reflected in the 200-fold lower dsDNA-dependent ATPase activity of Rad51 compared to RecA ( 79 ). Experiments with RecA have demonstrated the need for ATPase-dependent turnover of RecA to provide access of DNA polymerases to the invading 3′ end during post-synapsis ( 80 ). A role of Rad54 in the turnover of Rad51 from product heteroduplex DNA has been suggested, because Rad54 was found to dissociate Rad51 from duplex DNA in an ATP-dependent fashion ( 56 ). This activity of Rad54 was accompanied by a significant 6-fold stimulation of the Rad54 ATPase by partial Rad51–dsDNA filaments ( 37 , 56 ) and involved species-specific protein interactions. These observations are consistent with a model that Rad54 translocates on duplex DNA ( 46 ) towards the Rad51 filament terminus to dissociate the Rad51–dsDNA complex. Indeed, Rad54 could be directly visualized by electron microscopy at the terminus of Rad51 filaments formed on dsDNA under conditions where protein-free dsDNA flanked the filament ( 81 ). The post-synaptic model of Rad54 being a turnover factor for the Rad51 product complex also provides a explanation for the biochemical difference in the ATPase activity between RecA and Rad51, and a rationale to explain, why bacteria that employ RecA protein have no need for a Rad54-like activity and, in fact, do not have a Rad54 homolog.
|
16935872_p16
|
16935872
|
Post-synaptic models
| 4.886751 |
biomedical
|
Study
|
[
0.9982340335845947,
0.0010972413001582026,
0.0006686889682896435
] |
[
0.9894101619720459,
0.0013777815038338304,
0.008565187454223633,
0.0006469020736403763
] |
en
| 0.999997 |
While the genetic data are unable to resolve the synaptic and post-synaptic phases of recombination, as discussed above, other in vivo observations may bear on this distinction. Meiotic or DNA damage-induced Rad51 foci in mouse, chicken DT40 cells and budding yeast exhibit a longer half-life in rad54 mutants ( 60 – 62 , 82 ). Unfortunately, the exact nature of cytologically observable Rad51 foci has not been determined. They may represent pre-synaptic Rad51 filaments and later recombination intermediates in synapsis (D-loops) or post-synapsis. Hence, these cytological data suggest a function of Rad54 after pre-synapsis, but cannot distinguish between a function in synapsis or post-synapsis.
|
16935872_p17
|
16935872
|
Post-synaptic models
| 4.241526 |
biomedical
|
Study
|
[
0.999549925327301,
0.00021039071725681424,
0.0002396574564045295
] |
[
0.9984276294708252,
0.00039098705747164786,
0.0010943448869511485,
0.00008716832235222682
] |
en
| 0.999996 |
Chromatin immunoprecipitation (ChIP) experiments have been used to monitor the recruitment of Rad51 protein to an HO endonuclease-induced DSB at the MAT locus and the HML donor locus in wild-type and rad54 mutant cells ( 53 , 57 , 83 ). Initially, two studies arrived at opposite conclusions as to, whether Rad54 had a role in Rad51 localization to the DSB ( 53 , 83 ). It appears now that Rad54 may have an ATP-independent role of localizing Rad51 close to the terminus of the DSB, whereas Rad51 readily binds more distant from the DSB in a Rad54-independent fashion ( 57 , 83 ). This ATP-independent function of Rad54 in pre-synapsis might be a reflection of the stabilization of the Rad51-ssDNA filament found in vitro , which was also independent of the Rad54 ATPase activity ( 55 ). It is inferred from these experiments that Rad51 forms functional filaments in rad54 cells, because Rad51 was found targeted to the duplex donor locus ( HML ) by ChIP ( 57 , 83 ). The noted difference in Rad51 localization to the HML donor site between wild-type and rad54 cells ( 53 , 57 ) may be a function of defects in filament assembly during pre-synapsis or defects in synapsis/post-synapsis, which may affect Rad51–DNA complexes during these phases of recombination. Although Rad51 is targeted to the donor locus in rad54 cells, it is unclear if D-loops are formed and several studies were unable to detect DNA synthesis from an invading 3′ end at the donor locus ( 53 , 57 , 83 ). This deficiency in directing DNA synthesis from the invading strand in the D-loop may be a consequence of an inability to form D-loops in the first place (synapsis defect) or an inability to recruit DNA polymerase to the invading 3′ end of the D-loop (post-synapsis defect) or both. While some ChIP data support a possible ATP-independent function of Rad54 in pre-synapsis ( 53 , 57 ), the ChIP experiments are unable to resolve the question whether the critical ATP-dependent function of Rad54 is in synapsis or post-synapsis.
|
16935872_p18
|
16935872
|
Post-synaptic models
| 4.567835 |
biomedical
|
Study
|
[
0.9991037249565125,
0.0004989010049030185,
0.00039733541780151427
] |
[
0.9976218342781067,
0.00041758091538213193,
0.0017961636185646057,
0.00016443704953417182
] |
en
| 0.999996 |
Chromatin represents the natural environment of nuclear DNA metabolism in eukaryotes and was found to negatively interfere with transcription. A similar inhibition may be expected for recombination, and the similarity of Rad54 to known chromatin remodeling factors immediately suggested that Rad54 might be a chromatin remodeling factor for recombinational repair. This activity is potentially relevant at the break site prior to end-processing (pre-synapsis) and at the pairing site on the template DNA, where Rad54 may not only clear nucleosomes but also other proteins bound to duplex DNA that would inhibit D-loop formation (synapsis) . Biochemical experiments using reconstituted nucleosomal templates have confirmed this expectation and shown that S.cerevisiae and D.melanogaster Rad54 remodel chromatin in vitro ( 44 , 84 , 85 ). Rad54 enhances the accessibility of nucleosomal DNA by restriction enzymes and can slide a single nucleosome in an ATP-dependent fashion. The efficiency of chromatin remodeling by Rad54 was below that of established chromatin remodeling factors, and Rad54 was unable to affect nucleosomal positioning in a nucleosomal array. This may reflect a requirement for protein-free DNA that is longer than the linker DNA in such arrays. Rad51 requires Rad54 protein to promote efficient D-loop formation on nucleosomal substrates in vitro ( 44 , 85 ). Nucleosomal remodeling was greatly stimulated by Rad51-ssDNA nucleoprotein filaments without the need for homology between the two DNAs, suggesting that nucleosomal remodeling precedes synapsis ( 84 ). These biochemical studies suggest a role of Rad54 in chromatin remodeling at the pairing site just prior to synapsis, where it is targeted by its interaction with the Rad51 nucleoprotein filament. This model was tested in vivo using HO endonuclease-initiated DSB repair in budding yeast ( 57 ). However, monitoring a positioned nucleosome on the HML donor site with micrococcal nuclease showed no difference between wild-type and rad54 cells ( 57 ), suggesting that Rad54 does not act by moving or removing this positioned nucleosome at the HML donor site. However, an effect of Rad54 on the accessibility of the HML donor site by the HO endonuclease was identified ( 57 ). Access of HO to the HML target site required the Rad54 ATPase activity, but it is unclear if this effect reflects chromatin remodeling or is an indirect consequence of forming recombination intermediates at HML . The chromatin model needs further testing in vivo and a specific interaction between Rad54 and the core histones, as shown for known chromatin remodeling factors ( 9 – 11 ), remains to be demonstrated.
|
16935872_p19
|
16935872
|
Rad54 and chromatin remodeling
| 4.817572 |
biomedical
|
Study
|
[
0.9979971051216125,
0.0012525622732937336,
0.0007503939559683204
] |
[
0.9957962036132812,
0.0010587181895971298,
0.002568145515397191,
0.0005769742419943213
] |
en
| 0.999997 |
Physical analysis of DSB-induced recombination involving the budding yeast MAT locus identified recombination events independent of the Rad54 (and Rad51, Rad55, Rad57) proteins. This led to the suggestion that Rad54, Rad51, Rad55, Rad57 were required for recombination involving chromatin substrates ( 86 ). However, later work showed that a number of recombination events involving repeat substrates occurs independent of the Rad54, Rad51, Rad55 and Rad57 proteins ( 1 , 6 , 7 ). It is likely now that these events are mediated by the single-strand annealing (SSA) and possibly BIR pathways of recombination ( 87 ). These pathways either do not require Rad51 and Rad54 outright or have Rad51-Rad54-independent sub-pathways ( 6 , 7 ), an explanation that is independent of an involvement of chromatin. The observation that Rad54 significantly stimulates Rad51-dependent recombination in vitro on protein-free (non-chromatin) templates also suggests that Rad54 function is not confined to chromatin.
|
16935872_p20
|
16935872
|
Rad54 and chromatin remodeling
| 4.494041 |
biomedical
|
Study
|
[
0.999264657497406,
0.00039320209180004895,
0.00034209605655632913
] |
[
0.9923357367515564,
0.0004532872117124498,
0.007034251466393471,
0.00017673734691925347
] |
en
| 0.999997 |
The genome of the budding yeast S.cerevisiae predicts 17 Snf2-related proteins, belonging to various distinct subfamilies (A. Flaus and T. Owen-Hughes, manuscript in preparation). Seven of them, Rad54, Rdh54/Tid1, Rad5, Rad16 and Rad26/CS-B, as well as the Ino80 and Swr1 complexes, were identified to have specific functions during DNA repair ( Table 1 ). Among the Snf2 paralogs, Tid1/Rdh54 (Rad54B in mammals?) shows the highest similarity to Rad54 in sequence, genetic function and biochemical properties ( 21 , 25 , 88 , 89 ). Tid1/Rdh54 appears to augment the function of Rad54 during DNA repair in mitotic cells and functions primarily during meiotic recombination, likely through its interaction with the meiosis-specific RecA homolog Dmc1 ( 21 , 25 , 90 ). However, Tid1/Rdh54 also has a specific but poorly understood function in adaptation from DNA damage not shared by Rad54 ( 91 ), which may be related to its specific localization at the kinetochore in undamaged cells ( 16 ).
|
16935872_p21
|
16935872
|
OTHER SNF2-RELATED PROTEINS IN DNA REPAIR
| 4.472642 |
biomedical
|
Study
|
[
0.9994556307792664,
0.00028602415113709867,
0.0002582527231425047
] |
[
0.9984094500541687,
0.00042877477244473994,
0.0010524372337386012,
0.00010930050484603271
] |
en
| 0.999997 |
Rad5 protein functions in the error-free sub-pathway of post-replication repair ( RAD6 epistasis group) in budding yeast to bypass UV lesions, where it may be involved in remodeling protein complexes at stalled replication forks ( 92 ).
|
16935872_p22
|
16935872
|
OTHER SNF2-RELATED PROTEINS IN DNA REPAIR
| 3.937245 |
biomedical
|
Study
|
[
0.9986205101013184,
0.0003248171997256577,
0.0010546251432970166
] |
[
0.8867622017860413,
0.1101863831281662,
0.0024076353292912245,
0.0006437635747715831
] |
en
| 0.999997 |
Rad16 protein participates in nucleotide excision repair, specifically of the non-transcribed strand of transcribed genes or transcriptionally silenced genes, but its specific function remains unclear ( 93 ).
|
16935872_p23
|
16935872
|
OTHER SNF2-RELATED PROTEINS IN DNA REPAIR
| 3.729094 |
biomedical
|
Study
|
[
0.9987241625785828,
0.0002506098535377532,
0.0010252553038299084
] |
[
0.835330605506897,
0.15699344873428345,
0.0069578890688717365,
0.0007180768880061805
] |
en
| 0.999997 |
CS-B (budding yeast Rad26), one of two human genes involved in Cockayne's syndrome, plays a role in transcription-coupled repair ( 94 ). In analogy with the function of the bacterial homolog, TRCF, CS-B was thought to remodel stalled RNA polymerase II complexes to allow access of repair proteins to the lesion ( 95 ), but CS-B was also found capable of remodeling nucleosomes in vitro ( 96 ).
|
16935872_p24
|
16935872
|
OTHER SNF2-RELATED PROTEINS IN DNA REPAIR
| 4.240639 |
biomedical
|
Study
|
[
0.9995437264442444,
0.00015342514961957932,
0.0003027894999831915
] |
[
0.998316764831543,
0.001028547529131174,
0.0005736839957535267,
0.00008091123891063035
] |
en
| 0.999997 |
Ino80 and Swr1, the catalytic subunits of two known chromatin remodeling complexes, were found to be recruited to the DSB site through a specific interaction with C-terminally phosphorylated histone H2A (γH2AX) ( 97 – 99 ). Ino80 is part of a 12 protein complex and a transcriptional regulator that displays efficient chromatin remodeling activity by shifting nucleosomes through specific interactions with histones ( 100 , 101 ). Swr1 functions in a histone exchange complex that replaces histone H2A with the H2A variant H2AZ ( 102 ). The genetic relationship between the Ino80 and Swr1 complexes and individual DNA repair pathways has not been fully elucidated and their specific protein–DNA substrates largely remain to be determined. The surprisingly high number of Snf2-family members that appear to function specifically in distinct DNA repair pathways suggests a significant degree of functional diversification that may reflect different protein–DNA complexes as target substrates for the individual enzymes or enzyme complexes.
|
16935872_p25
|
16935872
|
OTHER SNF2-RELATED PROTEINS IN DNA REPAIR
| 4.427983 |
biomedical
|
Study
|
[
0.9994644522666931,
0.000296890182653442,
0.0002386963169556111
] |
[
0.9976297616958618,
0.00035846352693624794,
0.0019045345252379775,
0.00010722404840635136
] |
en
| 0.999996 |
Several biochemical models for the function of Rad54 protein during consecutive mechanistic stages in HR have been developed. While these models are not mutually exclusive, the biological significance of these putative individual roles of Rad54 needs to be tested in physical in vivo assays that can distinguish the various stages of recombination. While break formation and processing as well as the formation of the final repair product can be readily monitored, pairing intermediates during mitotic DSB repair (D-loops and Holliday junctions) have eluded detection so far. Such an assay has been successfully developed for the analysis of meiotic recombination ( 103 , 104 ) and will be critical to distinguish between the possible synaptic and post-synaptic roles of Rad54 in vivo . Likewise, the significance and function of the chromatin remodeling activity of Rad54 remain to be tested by in vivo analysis. What is the relationship of Rad54 with the confirmed chromatin remodeling factors Ino80 and Swr1 that are recruited to the break site; and are these factors also present at the target pairing site? Many of the Snf2-related proteins function in large multi-protein assemblies. It appears that Rad54 functions as a homo-multimeric assembly and no stable in vivo complex of Rad54 with other proteins has been reported. While the interaction of Rad54 with Rad51 has been analyzed in significant detail, its interaction with the structure-selective endonuclease Mus81-Mms4 ( 105 ) is poorly understood but may shed light on the function and in vivo substrates of Mus81-Mms4. Since the genetic identification of the RAD54 gene in the late 1960s, the cloning of the budding yeast gene in 1983 ( 106 ), the determination of its sequence in 1991 ( 107 ), the isolation of mammalian homologs in 1996 ( 108 ), the disruption of the mouse gene in 1997 ( 28 ) and the purification of the Rad54 protein in 1998 ( 38 ), much progress has been made to understand the function of the Rad54 gene and protein. Nevertheless, additional biochemical and in vivo analyses, including novel imaging techniques and physical recombination assays, will be needed to determine whether Rad54 really is the Swiss Army knife of HR.
|
16935872_p26
|
16935872
|
CONCLUSION
| 4.896108 |
biomedical
|
Study
|
[
0.9971388578414917,
0.0014357352629303932,
0.0014255217975005507
] |
[
0.7043056488037109,
0.0024657074827700853,
0.2919447422027588,
0.001283863908611238
] |
en
| 0.999998 |
RNA is more than a simple single-stranded sequence carrying genetic information as in the Central Dogma of Biology. For example, it can form tertiary structures that, such as proteins, can be catalytic. Natural and engineered RNA molecules are widely used as functional tools in enzymatic catalysis and genetic control ( 1 – 5 ). One current problem is how to predict the structures of functional RNA sequences.
|
16982646_p0
|
16982646
|
INTRODUCTION
| 3.799622 |
biomedical
|
Review
|
[
0.998694121837616,
0.00032874298631213605,
0.0009771334007382393
] |
[
0.3287533223628998,
0.31371328234672546,
0.3564200699329376,
0.0011133188381791115
] |
en
| 0.999996 |
Secondary structure, the sum of canonical base pairs, is stronger ( 6 – 9 ) and forms faster ( 10 ) than tertiary structure. Therefore, secondary structure can largely be determined without knowledge of tertiary structure. Comparative sequence analysis is a standard technique for determining the secondary structure of homologous RNA sequences ( 11 – 13 ). When only a few or even a single sequence is available, the secondary structure at 37°C can be predicted by free energy minimization algorithms ( 14 – 17 ) using a set of empirical free energy parameters, determined from optical melting experiments ( 17 – 21 ). Each parameter only depends on the sequence identity of nucleotides in the motif and in adjacent base pairs and the total free energy is the sum of nearest neighbor terms. The average sensitivity (the percentage of known base pairs that are correctly predicted) of free energy minimization prediction has been benchmarked as high as 72.8 ± 9.4% for a diverse database of sequences having fewer than 800 nt ( 17 ). Furthermore, experimentally determined constraints can improve this accuracy of prediction up to 84% ( 17 , 18 ) for sequences with <6% pseudoknotted (non-nested) base pairs ( 17 ). Partition function prediction of base pair probabilities can be used to identify base pairs in the predicted lowest free energy structure that are much more likely than average to be in the known secondary structure ( 22 , 23 ). For example, 91.0% of base pairs in the lowest free energy structure with pairing probability of 0.99 or higher are contained in the known structure, on average ( 22 ). The high accuracy of thermodynamic structure prediction ( 17 ) demonstrates that many RNA secondary structures can be determined from sequences, without knowledge of any tertiary contacts or protein interactions.
|
16982646_p1
|
16982646
|
INTRODUCTION
| 4.70778 |
biomedical
|
Study
|
[
0.9989176988601685,
0.0006487932405434549,
0.00043353959335945547
] |
[
0.9754747748374939,
0.0010213395580649376,
0.023110264912247658,
0.00039358745561912656
] |
en
| 0.999997 |
The current set of free energy nearest neighbor parameters for predicting the free energy of RNA secondary structure, however, is limited to application at 37°C. Many organisms, thermophiles and psychrophiles, live at temperatures far from 37°C and many experiments are conducted at other temperatures. The prediction of secondary structure of RNA at arbitrary temperature would expand our knowledge of structure and evolution in the RNA world. Moreover, it would facilitate studying and designing functional RNA molecules at temperatures other than 37°C. The enthalpy nearest neighbor parameters can be used in conjunction with available free energy nearest neighbor parameters for 37°C to determine free energy nearest neighbors at other temperatures. But the most recent enthalpy parameters were derived in 1995 using a simple model ( 24 ). At that time, no themes had emerged for the sequence-dependent stability of internal loops. Subsequently, the nearest neighbor model for free energy change at 37°C was significantly improved ( 17 ) using experimental results. Therefore, we applied the principles of the current free energy nearest neighbor model ( 17 , 18 ) to determine a complete set of enthalpy nearest neighbor parameters using the available optical melting data.
|
16982646_p2
|
16982646
|
INTRODUCTION
| 4.218622 |
biomedical
|
Study
|
[
0.9994093179702759,
0.00023657016572542489,
0.00035410834243521094
] |
[
0.9988986253738403,
0.00022315653041005135,
0.0008207079372368753,
0.00005750295895268209
] |
en
| 0.999995 |
The database of experimental data for derivation of enthalpy parameters is included in Supplementary Data. It includes 130 hairpin loops ( 25 – 31 ), 37 bulge loops ( 32 , 33 ), 337 internal loops ( 17 , 18 , 34 – 49 ) (99 of which are 2 × 2 internal loops), 74 multibranch loops ( 50 , 51 ) and 43 coaxial stacking models ( 52 – 55 ).
|
16982646_p3
|
16982646
|
Database of experiments
| 3.962819 |
biomedical
|
Study
|
[
0.999221682548523,
0.00013010550173930824,
0.0006481828750111163
] |
[
0.9953203797340393,
0.0037433954421430826,
0.0008553469087928534,
0.00008090754272416234
] |
en
| 0.999998 |
The enthalpies of Watson–Crick and GU base pairs were derived by Xia et al. ( 21 ) and Mathews et al. ( 18 ), respectively.
|
16982646_p4
|
16982646
|
Canonical base pairs
| 3.35952 |
biomedical
|
Study
|
[
0.9967748522758484,
0.0002755187451839447,
0.002949556102976203
] |
[
0.9690169095993042,
0.026616986840963364,
0.0040642134845256805,
0.00030194674036465585
] |
en
| 0.999996 |
Dangling ends are unpaired nucleotides adjacent to canonical pairs and their enthalpy parameters were compiled previously ( 24 ). Dangling ends on terminal GU pairs are treated similar to dangling ends on terminal AU pairs. Terminal mismatches are non-canonical pairs at the end of helixes. The enthalpy parameters of terminal mismatches are taken from another compilation ( 20 ), with the exception of mismatches on terminal GU pairs, which were measured recently ( 30 ).
|
16982646_p5
|
16982646
|
Dangling ends and terminal mismatches
| 4.071917 |
biomedical
|
Study
|
[
0.998765230178833,
0.00014175602700561285,
0.0010929437121376395
] |
[
0.99498450756073,
0.0041422476060688496,
0.0007965863333083689,
0.00007661685231141746
] |
en
| 0.999997 |
If a terminal mismatch has the potential to pair canonically, the values of A–C and C–A mismatches are used for the purine–pyrimidine mismatch and pyrimidine–purine mismatches, respectively. This is important for partition function calculations, where all possible secondary structures are considered.
|
16982646_p6
|
16982646
|
Dangling ends and terminal mismatches
| 3.784294 |
biomedical
|
Study
|
[
0.9953102469444275,
0.0005101598799228668,
0.004179586190730333
] |
[
0.5057438015937805,
0.4919726252555847,
0.0017138420371338725,
0.0005697126616723835
] |
en
| 0.999996 |
The experimental enthalpies of hairpin loop formation are calculated from published experimental data ( 25 – 31 ) with the following equation: Δ H loop o = Δ H stem − loop o − Δ H stem o , where Δ H stem − loop o is the experimental value for unfolding the hairpin loop with stem, Δ H stem o is calculated by the INN-HB parameters ( 18 , 21 ), without an intermolecular initiation term.
|
16982646_p7
|
16982646
|
Hairpin loops
| 4.186551 |
biomedical
|
Study
|
[
0.9994244575500488,
0.00024056868278421462,
0.0003350554034113884
] |
[
0.9990767240524292,
0.0005427940050140023,
0.00032110855681821704,
0.000059368925576563925
] |
en
| 0.999998 |
The hairpin loop enthalpy parameters are estimated by linear regression using the same model as free energy nearest neighbor parameters ( 17 ), except that the GG first mismatch bonus observed for free energy does not apply for enthalpy because the bonus was not statistically significant for enthalpy. The GG stability bonus is therefore entropic in nature, consistent with the observation that GG mismatches are dynamic ( 56 ), i.e. they sample more than one single microstate on short timescales.
|
16982646_p8
|
16982646
|
Hairpin loops
| 4.193913 |
biomedical
|
Study
|
[
0.9991899132728577,
0.00023225034237839282,
0.0005778211634606123
] |
[
0.9993122816085815,
0.0004020548949483782,
0.00023646104091312736,
0.00004919262937619351
] |
en
| 0.999995 |
The enthalpies of hairpin loops are estimated by the following equation: Δ H loop o ( n > 3 ) = Δ H initiation o ( n ) + Δ H o ( first mismatch stacking ) + Δ H bonus o ( UU or GA first mismatch but not AG ) + Δ H bonus o ( special G-U closure ) + Δ H penalty o ( oligo-C loops ) , where n is the number of unpaired nucleotides in the loop. Hairpins with fewer than 3 unpaired nucleotides are not allowed by the model. When n = 3, only the initiation term is considered without any bonus and penalty terms, except a penalty for hairpin loops with three Cs. When n > 3, the special GU closure bonus applies to GU closed hairpins in which a 5′ closing G is preceded by two G residues; and Δ H bonus o (UU or GA first mismatch but not AG) is applied to loops with first mismatches of UU or GA (G on the 5′ side and A on 3′ side of loop). The oligo-C penalty applies only to loops composed of all C residues and, if n > 3, is calculated with Δ H penalty o (oligo-C loops, n > 3) = A n + B. For hairpinloops composed entirely of 3 C residues, the Δ H penalty o (oligo-C loops, n = 3) is applied.
|
16982646_p9
|
16982646
|
Hairpin loops
| 4.379504 |
biomedical
|
Study
|
[
0.9992194175720215,
0.0003160891938023269,
0.00046438886784017086
] |
[
0.997108519077301,
0.002109599532559514,
0.0006800395203754306,
0.00010190354805672541
] |
en
| 0.999997 |
The enthalpy parameters are listed in Table 1 and the database of measured loop enthalpies is available as Supplementary Data. In the absence of data, for hairpin loops longer than 9 nt, the initiation enthalpy is approximated with the initiation term for a hairpin of 9 nt. This assumes that additional instability of hairpin loops as the loop lengthens derives from the entropy ( 57 ).
|
16982646_p10
|
16982646
|
Hairpin loops
| 4.098757 |
biomedical
|
Study
|
[
0.9992140531539917,
0.00021406628366094083,
0.0005719288601540029
] |
[
0.9989838004112244,
0.0007154058548621833,
0.00024193961871787906,
0.000058783592976396903
] |
en
| 0.999997 |
The measured free energies at 37°C of some special hairpin loops of 3, 4 or 6 unpaired nucleotides ( 30 , 31 , 34 – 36 ) are either more or less stable by 0.9 kcal/mol than the model predicts. The enthalpies for each of these sequences are listed in a separate lookup table ( Table 2 ), to be consistent with the free energy parameters.
|
16982646_p11
|
16982646
|
Hairpin loops
| 4.130705 |
biomedical
|
Study
|
[
0.9994010925292969,
0.00020152213983237743,
0.00039732633740641177
] |
[
0.9993804693222046,
0.0003230441943742335,
0.00024286714324261993,
0.00005351833897293545
] |
en
| 0.999997 |
RNA secondary structure is destabilized by bulge loops, which are an interruption of helical structure in one strand only ( 32 , 37 , 38 ). The initiation terms, Δ H bulge initiation ° ( n ) for bulge loops of 1–3 nt, are listed in Table 3 . They are the average values of experimental data ( 32 , 33 ), calculated using the following equation: Δ H bulge initiation o = Δ H o ( duplex with bulge ) − Δ H o ( duplex without bulge ) + Δ H bp stack o ( n > 1 ) , where the enthalpy of the duplex without bulge is the experimental value of the sequence of the duplex without the bulge or as calculated with INN-HB parameters ( 21 ) if the experimental values were not available. Δ H bp stack ° is the stacking enthalpy of the base pairs in the duplex without the bulge that flank the bulge loop in the duplex with the bulge. Because the difference of initiation enthalpies between 2 and 3 nt bulges is almost zero, it is assumed that the increasing instability for longer bulges ( n ≥ 4) comes from the entropy of the loop closure ( 39 , 57 ). Thus, the initiation enthalpy for bulges longer than 3 nt is approximated as the 3 nt bulge enthalpy.
|
16982646_p12
|
16982646
|
Bulge loops
| 4.329942 |
biomedical
|
Study
|
[
0.9993684887886047,
0.0003162846842315048,
0.0003152039716951549
] |
[
0.9990125894546509,
0.00030641877674497664,
0.0006082843756303191,
0.00007265301974257454
] |
en
| 0.999998 |
Assuming that helical stacking is continuous between the adjacent helices for single bulges, but is interrupted by longer bulges ( 39 , 40 ), the enthalpies of bulge loops are calculated with the following equation: Δ H bulge o ( n ) = Δ H bulge initiation o ( n ) + Δ H bp stack o ( only applied to 1 nt loops ) . The calculation of enthalpies for the adjacent helices would include the terminal AU/GU penalty ( 21 ) for AU/GU pairs adjacent to the bulge loops that are longer than 1 nt. Δ H bp stack ° is the canonical helix stacking enthalpy applied for the two closing base pairs as though the helix was not interrupted by the bulge loop.
|
16982646_p13
|
16982646
|
Bulge loops
| 4.276502 |
biomedical
|
Study
|
[
0.9992378950119019,
0.0002849697775673121,
0.0004771461244672537
] |
[
0.9987601041793823,
0.0008580234716646373,
0.0003077148285228759,
0.00007415998697979376
] |
en
| 0.999996 |
Internal loop enthalpies were calculated from experimental data ( 17 , 18 , 34 – 49 ) using the following equation: Δ H internal loop o = Δ H o ( entire sequence with internal loop ) − Δ H o ( reference sequence without internal loop ) + Δ H bp stack o . The range of measured enthalpies differs for internal loops of different size and symmetry; therefore, different enthalpy models are used to predict different loop types. The models are similar to those used to model free energies ( 17 ).
|
16982646_p14
|
16982646
|
Internal loops
| 4.136371 |
biomedical
|
Study
|
[
0.9991039633750916,
0.00019887941016349941,
0.0006970776594243944
] |
[
0.9991968274116516,
0.0005027722800150514,
0.0002526385069359094,
0.00004778728180099279
] |
en
| 0.999996 |
For single non-canonical pairs (1 × 1 internal loops), the loop enthalpies are approximated by the following equation: Δ H loop o ( 1 × 1 ) = Δ H loop initiation o ( n = 2 ) + Δ H AU / GU o ( per AU or GU closure ) + Δ H GG o ( 1 × ) 1 + Δ H 5 ′ RU / 3 ′ YU o ( 1 × 1 ) , where Δ H loop initiation ° ( n = 2 ) is the enthalpy of initiation for a single non-canonical pair; Δ H AU / GU ° is the penalty for each AU or GU closing base pair; Δ H GG ° ( 1 × 1 ) is a bonus for a GG pair in a 1 × 1 loop; and Δ H 5 ′ RU / 3 ′ YU o ( 1 × 1 ) is a bonus for a 5′RU/3′YU stack in a 1 × 1 loop, where R is a purine and Y is a pyrimidine.
|
16982646_p15
|
16982646
|
1 × 1 Internal loops (single mismatches)
| 4.294486 |
biomedical
|
Study
|
[
0.9989697933197021,
0.00031989780836738646,
0.0007103651878423989
] |
[
0.9925395846366882,
0.0066209821961820126,
0.0007025528466328979,
0.00013685265730600804
] |
en
| 0.999995 |
The 2 × 2 internal loops, also called tandem mismatches, interrupt helical RNA with two opposing unpaired nucleotides on each strand. Many of the sequence-symmetric 2 × 2 loops have been studied experimentally ( 17 , 18 , 34 – 49 ) and their enthalpies are assembled in a ‘periodic table’ ( Table 4 ). Symmetric sequences that have not been measured are approximated by averaging the most adjacent columns that have been measured. For asymmetric 2 × 2 loops, the enthalpies are approximated using the following equation: Δ H loop o ( 2 × 2 ) ( 5 ′ PXYS / 3 ′ QWZT ) = [ Δ H 37 o ( 5 ′ PXWQ / 3 ′ QWXP ) + Δ H 37 o ( 5 ′ TZYS / 3 ′ SYZT ) ] / 2 + Δ H GG o + Δ p , where Δ H GG o (12.5 ± 2.7 kcal/mol) is applied to loops with a GG pair adjacent to an AA or any non-canonical pair with a pyrimidine and Δ p (2.4 ± 3.1 kcal/mol) is applied to loops with an AG or GA pair adjacent to a UC, CU or CC pair or with a UU pair adjacent to an AA pair.
|
16982646_p16
|
16982646
|
2 × 2 Internal loops (tandem mismatches)
| 4.287514 |
biomedical
|
Study
|
[
0.9994733929634094,
0.00023868001881055534,
0.0002879544044844806
] |
[
0.9989100694656372,
0.0004102547245565802,
0.0006117081502452493,
0.00006795570516260341
] |
en
| 0.999996 |
The enthalpies of other internal loops are approximated using the following equation: Δ H loop o ( n ) = Δ H loop initiation o ( n ) + Δ H AU / GU + ∣ n 1 − n 2 ∣ Δ H asym o + Δ H first non-canonical pairs o × [ except for 1 × ( n − 1 ) for n > 3 ] , where Δ H loop ° ( n ) is the enthalpy of initiation for a loop of n nucleotides; Δ H asym ° is a penalty for loops with unequal numbers of nucleotides on each side, with n 1 and n 2 the number of nucleotides on each side; Δ H first non-canonical pairs ° is applied for each sequence-specific first mismatch ( Table 5 ), but it is not applied to loops of the form 1 × ( n − 1) with n > 3 ( n is the total number of unpaired bases). Special first mismatch bonuses were determined for 2 × 3 and 1 × 2 internal loops with separate linear regressions.
|
16982646_p17
|
16982646
|
Other internal loops
| 4.229039 |
biomedical
|
Study
|
[
0.9993261098861694,
0.00024064940225798637,
0.00043332509812898934
] |
[
0.9991008043289185,
0.0005960759008303285,
0.0002443774719722569,
0.00005880382013856433
] |
en
| 0.999996 |
Moreover, the free energy parameters ( Table 6 ) were updated for internal loops based on recent experimental measurements. The free energy parameters were obtained using the method of Mathews et al. ( 17 ). The recent data include the 3 × 3 loops from Chen et al. ( 41 ), but excluding the 3 × 3 loops with a middle GA pair. The middle GA pair is shown to enhance stability and this extra stability cannot be predicted by the nearest neighbor parameter set used in this work ( 41 ).
|
16982646_p18
|
16982646
|
Other internal loops
| 3.887408 |
biomedical
|
Study
|
[
0.9960426092147827,
0.00025120467762462795,
0.0037061984185129404
] |
[
0.9991752505302429,
0.0005416059284470975,
0.00023054267512634397,
0.000052497900469461456
] |
en
| 0.999995 |
Coaxial stacking, which is a favorable interaction of two helices stacked end to end, occurs in multibranch loops and exterior loops. Stability increments for coaxial stacking were measured with a structure composed of a short oligonucleotide bound to a single-stranded end of a stem–loop structure, creating a helical interface ( 52 – 55 ). The enthalpy of coaxial stacking is quantified as follows: Δ H coaxial o = Δ H o ( duplex in context of stem-loops structure ) − Δ H o ( duplex without stem-loop structure, predicted ) + Δ H o ( correction ) , where Δ H °(correction) is the enthalpy for displacing a 3′ dangling end on the stem–loop structure if one is present.
|
16982646_p19
|
16982646
|
Coaxial stacking
| 4.234249 |
biomedical
|
Study
|
[
0.9994198083877563,
0.00020348068210296333,
0.0003767804882954806
] |
[
0.9989147186279297,
0.000708443287294358,
0.0003211431612726301,
0.00005566842810367234
] |
en
| 0.999997 |
When the helixes have no intervening mismatches, the enthalpy bonus is approximated by the nearest neighbor parameter ( 21 ) of a base pair in a helix. The excess enthalpy above the helical stacking nearest neighbor from Xia et al. ( 21 ), Δ H coaxial ° − Δ H NN ° , for each measured interface was calculated. With flush interfaces, i.e. with no intervening mismatch, and no strand extensions beyond the interface, the average excess enthalpy is −1.53 ± 1.45 kcal/mol. For interfaces followed by strand extensions, the excess enthalpy is 1.82 ± 1.13 kcal/mol. As the excess enthalpy changes are not statistically significant, coaxial stacking of helices with no intervening nucleotides is modeled with the enthalpy parameter in a helix.
|
16982646_p20
|
16982646
|
Coaxial stacking
| 4.221257 |
biomedical
|
Study
|
[
0.9993355870246887,
0.00026186121976934373,
0.0004024887748528272
] |
[
0.9992994070053101,
0.00033667063689790666,
0.00030755059560760856,
0.000056329074141103774
] |
en
| 0.999996 |
With one intervening nucleotide from each strand, two helices can stack with an intervening mismatch between them. There are two stack increments: one is the mismatch stack at the end of one helix with continuous backbone, which is equal to the mismatch stacking parameter on a helix, and the other is the mismatch stack with discontinuous backbone, which is modeled as sequence independent. The average enthalpy of sequence independent stacks is −8.46 ± 2.75 kcal/mol. In addition to this, an enthalpy bonus of −0.4 or −0.2 kcal/mol are applied to intervening mismatches composed of nucleotides that could form a Watson–Crick or a GU base pair, respectively. These bonuses are identical to free energy increments that are used and are empirically found to improve structure prediction accuracy.
|
16982646_p21
|
16982646
|
Coaxial stacking
| 4.333947 |
biomedical
|
Study
|
[
0.999357283115387,
0.0002787205157801509,
0.00036398772499524057
] |
[
0.9977902173995972,
0.0015979105373844504,
0.0005086727906018496,
0.00010313383245375007
] |
en
| 0.999997 |
The parameters are determined by linear regression of experimental data for three- and four-way multibranch loops ( 50 , 51 ). In a nearest neighbor model, the bimolecular enthalpy ( Δ H bimol ° ) for the formation of the duplex with a multibranch loop is given by the following equation: Δ H bimol o = Δ H helix1 o + Δ H helix2 o + Δ H bimol init o + Δ H MBL o − Δ H product mm o , where helix 1 and helix 2 are the intermolecular paired helices with Δ H ° predicted from nearest neighbor parameters for Watson–Crick pairs (without including bimolecular initiation so that Δ H bimol init ° appears only once). The Δ H product mm o is a term that accounts for the stacking enthalpy increment of the nucleotides that can stack on the hairpin loop stems to form a modified motif after the two strands have dissociated. This is the most favorable configuration with coaxial stacking of helixes (in the case of four-way multibranch loops) or of the stacking of unpaired nucleotides. Δ H bimol ° is the experimental value which is taken from T M − 1 versus ln( C T /4) plots. The multibranch loop enthalpy initiation term ( Δ H MBL init ° ) can be calculated from the above equation. The enthalpy of multibranch loops ( Δ H MBL ° ) is then modeled as the sum of two terms, initiation and stacking: Δ H MBL o = Δ H MBL initiation o + Δ H MBL stacking o . The stacking term is the favorable enthalpy of coaxial stacking, terminal mismatch and/or dangling end stacking. It is determined from the stacking conformation that gives the lowest free energy, as determined by free energy nearest neighbors ( 50 ). The initiation term can be approximated by the following equation: Δ H MBL initiation o = a + b × asym + c × h + Δ H strain o ( three-way loops with fewer than two unpaired nucleotides ) , where a , b and c are parameters determined from linear regression ( Table 7 ) and h is the number of branching helices. Δ H strain ° is a strain enthalpy that only applies to three-way multibranch loops with fewer than two unpaired nucleotides. The asym term is the average asymmetry that reflects the distribution of unpaired nucleotides, which is defined by the following equation: asym = min [ 2.0 , ( ∑ 1 h ∣ unpaired nucleotides 5 ′ - unpaired nucleotides 3 ′ ∣ ) h ] .
|
16982646_p22
|
16982646
|
Multibranch loops
| 4.455537 |
biomedical
|
Study
|
[
0.9990403056144714,
0.00045120311551727355,
0.0005083754076622427
] |
[
0.9989332556724548,
0.0004266138712409884,
0.0005393212777562439,
0.00010080033825943246
] |
en
| 0.999997 |
The average asymmetry is limited to 2.0, following the rules suggested by free energy parameters. Asymmetry cannot be applied, however, by dynamic programming algorithms for secondary structure prediction ( 17 , 22 ). Thus, the b term was excluded for secondary structure prediction and the parameters a and c were optimized by finding the parameters that lead to the highest average sensitivity of secondary structure prediction by free energy minimization. The maximum sensitivity of prediction was found with a = 30.0 kcal/mol and c = −2.2 kcal/mol.
|
16982646_p23
|
16982646
|
Multibranch loops
| 4.107444 |
biomedical
|
Study
|
[
0.9992823004722595,
0.00019420738681219518,
0.0005236049182713032
] |
[
0.9994151592254639,
0.00033999152947217226,
0.00019981696095783263,
0.00004510829603532329
] |
en
| 0.999995 |
The revised enthalpy nearest neighbor model was tested with RNA sequences with known secondary structure from organisms with known optimal growth temperature. The structures were taken from comparative analysis databases ( 42 – 49 , 58 , 59 ). Small (16S) subunit rRNA sequences are divided into domains as defined by Jaeger et al. ( 39 ). Large (23S) subunit rRNA sequences are divided into domains of fewer than 700 nt each ( 18 ). The optimal growth temperatures of different organisms were taken from the Prokaryotic Growth Temperature Database ( ) and the DSMZ German Collection of Microorganisms and Cell Cultures website ( ). Only the RNA sequences of mesophiles (organisms living at temperatures between 10 and 60°C, but with organisms living at 37°C excluded) were chosen to test the sensitivity and positive predictive value (PPV) of secondary structure prediction. Considering that posttranscriptional modification ( 60 ) and high pressure ( 61 ) in the thermophiles and hyperthermophiles (organism living above 60°C) would change the thermodynamics of secondary structure formation, sequences from these organisms were excluded. A list of sequences and optimal growth temperatures used are available in Supplementary Data.
|
16982646_p24
|
16982646
|
Database of RNA secondary structures
| 4.147262 |
biomedical
|
Study
|
[
0.9994487166404724,
0.00025348112103529274,
0.0002977105905301869
] |
[
0.9994521737098694,
0.00016191331087611616,
0.000333025207510218,
0.00005290422632242553
] |
en
| 0.999997 |
The accuracy of structure prediction is determined by the sum of the canonical base pairs correctly predicted. A base pair is considered correctly predicted even if it is shifted by 1 nt on one side. For example a base pair between nucleotides i and j is considered to be correctly predicted if any of these base pairs is predicted: i to j , i to j − 1, i to j + 1, i − 1 to j or i + 1 to j . The predicted base pair between i − 1 and j + 1, however, is not considered to be correct. This scoring scheme reflects the uncertainty of exact base pair matches in comparative sequence analysis and the possibility for dynamics in base pairing. The values of sensitivity and PPV of this scoring scheme are ∼2–3% higher than when determined with exact base pairing only, where only the i to j base pair is considered to be correct. The prediction accuracies are shown in Supplementary Tables 11 and 12. Each table includes accuracies determined when pairs can be shifted and when pairs must be an exact match.
|
16982646_p25
|
16982646
|
Accuracy of secondary structure prediction
| 4.175148 |
biomedical
|
Study
|
[
0.9994840621948242,
0.00027820534887723625,
0.00023764527577441186
] |
[
0.9991447925567627,
0.00034713506465777755,
0.0004369883972685784,
0.0000710215899744071
] |
en
| 0.999998 |
Machine-readable tables of the enthalpy parameters are available on the Mathews lab website ( ).
|
16982646_p26
|
16982646
|
Availability of parameters
| 1.227702 |
biomedical
|
Other
|
[
0.8781592845916748,
0.0021567135117948055,
0.11968401819467545
] |
[
0.0723002701997757,
0.9229063987731934,
0.0035423666704446077,
0.0012510272208601236
] |
en
| 0.999998 |
In the nearest neighbor model of free energy ( 17 , 18 ), the parameters for Watson–Crick base pairs are well determined at 37°C with errors <10%, or ∼0.1–0.2 kcal/mol ( 21 ). For other motifs such as loops and GU base pairs, individual nearest neighbor free energy increments are often determined with an error <0.5 kcal/mol ( 17 , 18 ). In order to extend the current model to predict free energy at temperatures other than 37°C, enthalpy parameters consistent with the current nearest neighbor model are required. The free energy at arbitrary temperature for each parameter is then 1 Δ G o ( T ) = Δ H o − T Δ S o = Δ H o − T [ Δ H o − Δ G ( 37 ° C ) ] / 310.15 , where the enthalpy (Δ H °) and entropy (Δ S °) are assumed to be temperature independent. As described in Materials and Methods, parameters for enthalpy prediction, compatible with the free energy model, were determined using available experimental data from optical melting experiments.
|
16982646_p27
|
16982646
|
Nearest neighbor model parameters
| 4.256413 |
biomedical
|
Study
|
[
0.9993430972099304,
0.00022611617168877274,
0.0004307437629904598
] |
[
0.9992495179176331,
0.000277532497420907,
0.0004150710010435432,
0.000057862238463712856
] |
en
| 0.999995 |
Experimental studies consistently demonstrate that enthalpy and entropy measurements have considerably larger percent error than free energy measurements. Free energy at 37°C is determined with greater precision because of correlation between errors in enthalpy and entropy ( 21 ). The larger experimental errors in enthalpy result in larger percent errors for enthalpy nearest neighbor parameters than free energy parameters. The enthalpy of RNA secondary structure is known to be a function of temperature. A linear model for heat capacity change predicts the following: 2 Δ H o ( T ) = Δ H o ( T 0 ) + Δ C p o ( T − T 0 ) , 3 Δ S o ( T ) = Δ S o ( T 0 ) + Δ C p o ln ( T / T 0 ) , where Δ C p ° is a constant heat capacity change and T 0 is a chosen reference temperature. It is hypothesized that the heat capacity change arises from the extent of stacking increasing with decreasing temperature. Thus, Δ C p ° is negative because single strands are more organized at low rather than high temperature ( 62 – 67 ). The Δ C p ° can be estimated by linear fits of enthalpy and entropy changes as a function of melting temperature ( 50 , 51 , 62 ) or determined by isothermal titration calorimetry at multiple temperatures ( 68 , 69 ). However, the effects of heat capacity change on enthalpy and entropy are antagonistic in terms of free energy change: 4 Δ G o ( T ) = Δ H o ( T ) − T Δ S o ( T ) ,
|
16982646_p28
|
16982646
|
Nearest neighbor model parameters
| 4.416909 |
biomedical
|
Study
|
[
0.9993889331817627,
0.0002805492258630693,
0.0003304574347566813
] |
[
0.9966855645179749,
0.00040024067857302725,
0.002821660600602627,
0.00009252410382032394
] |
en
| 0.999997 |
Therefore, for certain Δ T (Δ T = T − T 0 ), Δ C p ° can be neglected because the effects are compensated in terms of free energy. To calculate the compensation for a set of RNA duplexes ( 62 ), the free energy, Δ G °, was derived directly from Equation 4 assuming that the entropy and enthalpy were independent of temperature. Then the temperature-dependent free energy, Δ G T ° , was calculated with the measured non-zero Δ C p ° from Equations 2 – 4 . The free energy difference, ΔΔ G ° = Δ G T ° − Δ G °, increases with the deviation of temperature from T 0 (37°C) . The exact ΔΔ G ° for each duplex is shown in Table 8 for different temperatures. The experimental error in individual loop free energy nearest neighbor parameters at 37°C is as large as 0.5 kcal/mol ( 17 ), which corresponds to roughly a factor of 2 in equilibrium constant. Thus, the small ΔΔ G ° for helices suggests that the approximation of Δ C p ° = 0 is reasonable for predictions from ∼10 to 60°C. Therefore, the enthalpy parameters derived here assume Δ C p ° = 0 and are most accurate at predicting free energy change close to 37°C.
|
16982646_p29
|
16982646
|
Nearest neighbor model parameters
| 4.27112 |
biomedical
|
Study
|
[
0.9994389414787292,
0.00027529860381036997,
0.0002856742648873478
] |
[
0.9991772770881653,
0.00025231915060430765,
0.0004994297050870955,
0.00007098456262610853
] |
en
| 0.999996 |
RNAstructure is a program for RNA secondary structure prediction and analysis. It includes prediction of secondary structure by free energy minimization ( 17 ), prediction of base pair probabilities using a partition function ( 22 ), the efn2 function for predicting the free energy change of folding given a sequence and secondary structure ( 18 ), and the Dynalign algorithm for finding the secondary structure common to two sequences ( 70 ). RNAstructure was revised to make predictions at user-defined temperature. Because large internal loops are more likely at high temperature, the previous limitation on internal loop size (fewer than 30 unpaired nucleotides) ( 17 , 18 , 22 ) was removed by implementing the method of Lyngsø et al. ( 71 ). This provides an O ( N 3 ) algorithm that can predict internal loops of arbitrary size. Benchmarks for calculation time and memory requirement with and without this revision are shown in Table 9 .
|
16982646_p30
|
16982646
|
Dynamic programming algorithm for RNA secondary structure prediction
| 4.205903 |
biomedical
|
Study
|
[
0.9993775486946106,
0.00021772150648757815,
0.0004047127440571785
] |
[
0.9538684487342834,
0.024285253137350082,
0.021434396505355835,
0.00041188349132426083
] |
en
| 0.999999 |
The enthalpy nearest neighbor parameters were compared with the previous parameters and model for enthalpy and free energy assembled by Serra and Turner ( 24 ) by predicting the secondary structures of RNA sequences with known secondary structures. Sensitivities, the percent of known base pairs that are correctly predicted, using both sets of parameters are shown in Figure 2 (detailed numbers are in Supplementary Table 11A) for different types of structural RNA sequences. The known structures of these sequences were taken from comparative analysis databases ( 42 – 49 , 58 , 59 ). The average sensitivity is improved from 65.2 to 68.9% using the new parameters assembled here. Sensitivities are improved for most types of the RNA. The exceptions are 5S rRNA and Group II introns.
|
16982646_p31
|
16982646
|
Sensitivities and PPVs of structure predictions
| 4.129759 |
biomedical
|
Study
|
[
0.9994010925292969,
0.00025272200582548976,
0.00034619448706507683
] |
[
0.9993155002593994,
0.00015068345237523317,
0.00048282346688210964,
0.00005100495400256477
] |
en
| 0.999997 |
To test the enthalpy parameters, the accuracy of secondary structure prediction at optimal growth temperature was compared to the accuracy of structure prediction at 37°C for organisms that do not grow optimally at 37°C for several types of RNAs ( Table 10 ). The comparison of predictions was shown in different groups divided by optimal growth temperature. The organisms in each group grow optimally in a certain range of temperatures. Compared to the prediction at 37°C, structure prediction at optimal growth temperature performs better for the organism living at temperatures between 22 and 37°C, but is worse at other optimal growth temperatures. This suggests that when enthalpy parameters are assumed to be temperature independent, their utility as a tool for deriving free energy parameters for use in predicting the lowest free energy structure is limited to a narrow temperature range. Small errors in enthalpy change parameters have a larger effect on free energy change parameter determination ( Equation 1 ), the farther the temperature is from 37°C.
|
16982646_p32
|
16982646
|
Sensitivities and PPVs of structure predictions
| 4.119372 |
biomedical
|
Study
|
[
0.9993738532066345,
0.0002963688166346401,
0.00032973341876640916
] |
[
0.9993822574615479,
0.00016525558021385223,
0.00040155593887902796,
0.00005085074735688977
] |
en
| 0.999999 |
Figure 3 shows the PPV for base pairs from the lowest free energy structure for base pairs with different pairing probabilities (see detailed numbers in Supplementary Table 12A). They are predicted using a partition function calculation at optimal growth temperature ( 22 ). PPV is the percentage of predicted base pairs that are found in the known structure. The average PPV of all pairs in the lowest free energy structures is only 62.0%, which is lower than the sensitivity (68.9%). This suggests that the model over-predicts base pairs and/or that the base pairs may not be annotated completely in the structures from comparative analysis ( 22 ). For example, if a base pair is completely conserved, then it is sometimes not annotated by comparative analysis ( 42 – 49 , 58 , 59 ). Base pair probabilities for all possible pairs are calculated with a partition function and grouped by different thresholds. The PPV is significantly higher for predicted base pairs in the lowest free energy structure with higher pairing probability. The average PPV is up to 90.4% for those known base pairs having probability of 0.99 or above. It has been demonstrated previously that base pair probabilities predicted at 37°C can be used to find pairs with high PPV ( 22 ). The fact that this holds true at other temperatures shows that the enthalpy parameters are robust for base pair probability prediction.
|
16982646_p33
|
16982646
|
Sensitivities and PPVs of structure predictions
| 4.173949 |
biomedical
|
Study
|
[
0.9993500113487244,
0.00035530509194359183,
0.00029477899079211056
] |
[
0.9994626641273499,
0.00015521753812208772,
0.00031821735319681466,
0.00006386319728335366
] |
en
| 0.999996 |
The fact that the accuracy of secondary structure prediction is sensitive to the accuracy of the nearest neighbor parameters, but the base pair probabilities remain a robust measure of confidence for a wide variety of temperatures is consistent with a previous work. Layton and Bundschuh ( 72 ) demonstrated that the predicted lowest free energy structure was often changed in repeated structure predictions after random adjustments of the nearest neighbor parameters within the limits of their error. Base pair probabilities, however, were less perturbed by changes in the parameters ( 72 ). With the extrapolation of nearest neighbor parameters to temperatures far from 37°C, the accuracy of the predicted lowest free energy structure is often reduced as compared to structure prediction at 37°C. The ability of the partition function predicted base pair probabilities to determine base pairs predicted with a higher confidence is unchanged with secondary structure prediction at temperatures far from 37°C. This is because the determination of base pair probabilities is not as perturbed by errors in the nearest neighbor parameters.
|
16982646_p34
|
16982646
|
Sensitivities and PPVs of structure predictions
| 4.162228 |
biomedical
|
Study
|
[
0.9993693232536316,
0.00027456364477984607,
0.0003560885670594871
] |
[
0.9992050528526306,
0.00018951328820548952,
0.0005508120520971715,
0.00005462231274577789
] |
en
| 0.999996 |
An example of secondary structure prediction at 37°C and at optimal growth temperature of 30°C is shown in Figure 4 for a tRNA sequence. The base pairs with higher predicted pairing probability are pairs predicted with greater confidence. For this sequence, secondary structure prediction is more accurate and the fidelity of structure prediction (as judged by the percent of high probability pairs) is improved at optimal growth temperature.
|
16982646_p35
|
16982646
|
Sensitivities and PPVs of structure predictions
| 4.157416 |
biomedical
|
Study
|
[
0.9995306730270386,
0.00022238303790800273,
0.0002469597675371915
] |
[
0.9984298348426819,
0.0010860527399927378,
0.0003867256746161729,
0.00009740406676428393
] |
en
| 0.999996 |
Melting temperature, T m , is defined as the temperature at which half of strands are unpaired. Assuming that an RNA melts with a two-state transition, the melting temperature (in Kelvins) of a single-stranded RNA structure can be predicted by T m = Δ H °/Δ S ° ( 73 ). For example, the predicted melting temperatures (°C) for all hairpins in the database of optically melted sequences (Supplementary Data) ( 25 – 31 ) are plotted in Figure 5 as a function of experimentally determined T m . This shows that the parameters adequately reflect the thermal stabilities of RNA sequences with known T m . Better correlation was found at higher temperatures. This is expected because most hairpins were measured with high melting temperatures in experiments ( 25 – 31 ).
|
16982646_p36
|
16982646
|
Correlation between melting temperature and optimal growth temperature
| 4.185445 |
biomedical
|
Study
|
[
0.999581515789032,
0.00021406004088930786,
0.00020450663578230888
] |
[
0.9991697072982788,
0.00023509313177783042,
0.0005311860586516559,
0.00006400243000825867
] |
en
| 0.999997 |
Melting temperature reflects the thermal stability of a structure. Therefore RNA structures in organisms living at higher temperature are expected to have higher melting temperatures. Figure 6A shows a plot of predicted melting temperatures of the lowest free energy structure versus organism optimal growth temperature (10–90°C). A strong correlation (linear correlation coefficient of 0.797) is found between the melting temperature and the optimal growth temperature for different types of RNA structures. On the other hand, there appears to be less correlation between nucleotide content and optimal growth temperature for diverse types of RNA, although uracil content of 16S rRNA of thermophiles and psychrophiles were found recently to correlate inversely with their optimal growth temperatures ( 74 ). Evidently, the thermal stability of RNA structure is not simply controlled by base content. Organisms that grow at high temperature have apparently evolved RNA secondary structures with a combination of motifs that provide thermal stability.
|
16982646_p37
|
16982646
|
Correlation between melting temperature and optimal growth temperature
| 4.202799 |
biomedical
|
Study
|
[
0.9995079040527344,
0.0002274126309202984,
0.0002646908105816692
] |
[
0.9989487528800964,
0.00021715291950386018,
0.0007787350914441049,
0.00005537813194678165
] |
en
| 0.999995 |
The nearest neighbor parameters for enthalpy were derived here using similar rules as for free energy nearest neighbor parameters at 37°C ( 17 ). This makes these parameters useful for determining free energy parameters at arbitrary temperature that are compatible with dynamic programming algorithms for secondary structure prediction. Some of the enthalpy parameters have large percent standard errors as compared with the parameters of free energy. This reflects the larger errors in the experimental results of enthalpy than free energy, but it also suggests that enthalpy may be more sequence dependent than free energy. This sequence dependence cannot be determined using the currently available database of optical melting experiments and suggests a need for further optical melting experiments on model RNA systems.
|
16982646_p38
|
16982646
|
DISCUSSION
| 4.1475 |
biomedical
|
Study
|
[
0.9993355870246887,
0.00019809651712421328,
0.00046632380690425634
] |
[
0.9990320205688477,
0.0004010509583167732,
0.0005138026317581534,
0.000053165818826528266
] |
en
| 0.999997 |
Another source of error comes from the assumption that the enthalpy and entropy are independent of the temperature in both the model and in the analysis of optical melting experiments. When the temperature is too far from 37°C, the sensitivity of prediction is expected to be worse than 68.9% on average because of the approximation of Δ C p ° = 0 . For example, experiments demonstrate cold denaturation of RNA ( 68 , 69 ), but the nearest neighbor model does not reproduce those results. Further experiments by isothermal titration calorimetry would be needed to provide the data for a model that can include a non-zero heat capacity change.
|
16982646_p39
|
16982646
|
DISCUSSION
| 4.152421 |
biomedical
|
Study
|
[
0.9992635846138,
0.0001659692352404818,
0.0005704961367882788
] |
[
0.9988510608673096,
0.0005120720015838742,
0.000586472568102181,
0.00005037907976657152
] |
en
| 0.999998 |
There are common error sources that should be considered for the prediction of base pairs. Free energy minimization assumes that the secondary structure is at equilibrium. The nearest neighbor model is an incomplete representation of structural free energy. The parameters average some sequence-specific effects and were derived from a limited set of experiments. Some RNA sequences, in particular mRNA, may sample multiple structures at equilibrium. The parameters are derived from experimental data at 1 M NaCl, whereas the salt concentration in different organisms may be very different.
|
16982646_p40
|
16982646
|
DISCUSSION
| 4.040001 |
biomedical
|
Study
|
[
0.9992067217826843,
0.00012715069169644266,
0.0006661837687715888
] |
[
0.9564226269721985,
0.038537364453077316,
0.004815271124243736,
0.0002246923540951684
] |
en
| 0.999997 |
In spite of all these limitations, the nearest neighbor model predicts secondary structures with a 72.8% average sensitivity ( 17 ). Recent experimental results on the self-folding of the 16S rRNA 5′ domain ( 75 ) support the assumption of thermodynamic control of folding pathway. Moreover, the base pair prediction with the partition function can be used to determine pairs predicted with greater confidence ( 22 ).
|
16982646_p41
|
16982646
|
DISCUSSION
| 4.141675 |
biomedical
|
Study
|
[
0.9994903802871704,
0.0001583887351443991,
0.0003512372786644846
] |
[
0.9991337656974792,
0.00027336878702044487,
0.0005461093969643116,
0.00004681853897636756
] |
en
| 0.999996 |
In spite of the fact that the enthalpy parameters have larger percent errors than the free energy parameters for 37°C, the enthalpy parameters are able to predict optical melting temperatures for small model sequences. Predicted melting temperatures for structural RNA sequences correlate well with optimal growth temperature, suggesting that these parameters capture many of the sequence-dependent features of RNA folding enthalpy change.
|
16982646_p42
|
16982646
|
DISCUSSION
| 4.165381 |
biomedical
|
Study
|
[
0.9995225667953491,
0.0001953410537680611,
0.0002821236848831177
] |
[
0.9985256791114807,
0.0005437695072032511,
0.0008587153861299157,
0.00007191595068434253
] |
en
| 0.999998 |
Supplementary Data are available at NAR Online.
|
16982646_p43
|
16982646
|
SUPPLEMENTARY DATA
| 0.985075 |
biomedical
|
Other
|
[
0.7697952389717102,
0.0054101841524243355,
0.22479452192783356
] |
[
0.01419480424374342,
0.982682466506958,
0.0018953380640596151,
0.00122743786778301
] |
en
| 0.999995 |
Telomeres are specialized DNA–protein structures that protect the ends of chromosomes and distinguish natural chromosome termini from unnatural breaks produced by DNA damage ( 1 ). Alterations in telomere structure are associated with distinct cellular programs including apoptosis and unlimited proliferation indicating that telomeres play an important role in the processes of aging and cancer ( 2 ). Telomere DNA length and protein composition vary during the life of a cell, and telomere structures may involve double-stranded DNA-binding proteins ( 3 , 4 ), single-stranded DNA (ssDNA)-binding proteins ( 5 – 7 ) and DNA–DNA interactions ( 8 ). Human telomeric DNA, located at the ends of each chromosome, contains G-rich termini as relatively short single-stranded 3′ overhangs designated G-overhangs ( 9 , 10 ). Such single-stranded telomere DNAs have been found in protozoa, yeast and vertebrates ( 11 – 13 ). They are synthesized specifically by a unique ribonucleoprotein reverse transcriptase called telomerase ( 14 , 15 ).
|
16973897_p0
|
16973897
|
INTRODUCTION
| 4.721559 |
biomedical
|
Study
|
[
0.998619794845581,
0.0006348293973132968,
0.0007452875142917037
] |
[
0.8022648692131042,
0.0020612296648323536,
0.19499503076076508,
0.0006789096514694393
] |
en
| 0.999997 |
It is well known that clusters of G residues may adopt non-B structures stabilized by interactions between the guanine bases under in vitro physiological conditions [for a review see ( 16 )]. These structures are four-stranded DNA complexes where layers of four guanine bases, one from each strand, are bound by Hoogsteen hydrogen bonds, thereby forming stacked G-quartets that hold the chains together. Therefore, it is conceivable that these G-quadruplex structures may occur in living cells ( 17 , 18 ) and affect essential cellular processes, such as recombination and extension of telomeric sequences by the telomerase ( 19 ).
|
16973897_p1
|
16973897
|
INTRODUCTION
| 4.217107 |
biomedical
|
Review
|
[
0.998213529586792,
0.000660833204165101,
0.0011256503639742732
] |
[
0.1866907775402069,
0.001884446362964809,
0.8109321594238281,
0.000492652936372906
] |
en
| 0.999998 |
It has been suggested that cells might possess a mechanism allowing them to resolve these structures into single strands, thereby providing the best opportunity for telomerase access to the 3′ end of a chromosome ( 14 ). Replication protein A (RPA) was shown recently to be present at the telomeric ends of chromosomes with maximum association in the S phase and to play an essential role in telomere maintenance ( 7 ). Schramke et al. ( 20 ) proposed that RPA activates the telomerase via its p32 subunit, by maintaining ssDNA in a state amenable to the binding of telomeric components. In addition, Cohen et al. ( 21 ) showed that in an in vitro system, low concentrations of human RPA (hRPA) stimulate extension of G-rich DNA primers by the telomerase (although high concentrations are inhibitory) and proposed a mechanism of unwinding of the unusual structures formed between G residues.
|
16973897_p2
|
16973897
|
INTRODUCTION
| 4.374313 |
biomedical
|
Study
|
[
0.9994863271713257,
0.0002620843588374555,
0.0002515806118026376
] |
[
0.9957504272460938,
0.0002951261994894594,
0.003840699326246977,
0.00011374471796443686
] |
en
| 0.999995 |
RPA is an ssDNA-binding protein (ssDBP) that is highly conserved in eukaryotes ( 22 , 23 ). hRPA is a heterotrimeric complex consisting of three subunits p70, p32 and p14, named according to their molecular masses of 70, 32 and 14 kDa, respectively. hRPA has four DNA-binding domains (A, B and C in p70 and D in p32), and it binds ssDNA via a multistep pathway ( 24 , 25 ).
|
16973897_p3
|
16973897
|
INTRODUCTION
| 4.305636 |
biomedical
|
Study
|
[
0.9994901418685913,
0.00014987675240263343,
0.0003599397896323353
] |
[
0.9941762685775757,
0.004851247649639845,
0.0008386702393181622,
0.00013383335317485034
] |
en
| 0.999997 |
The mechanism of ssDNA binding by the RPA involves at least three different binding modes, which are best defined by the length of the interacting ssDNA. The first mode, designated ‘compact conformation’, is characterized by an 8–10 nt occluded binding site, an intermediate, or ‘elongated contracted’ (13–14 nt) binding site, and an ‘elongated extended’ conformation characterized by a 30 nt occluded binding site ( 22 – 26 ). RPA plays essential roles in many aspects of nucleic acids metabolism, including replication, recombination, transcription, checkpoints and DNA repair ( 22 ). To determine the role of RPA in telomere maintenance, we have investigated the in vitro binding of hRPA under physiological conditions with an oligonucleotide based on the minimal human telomere repeat sequence capable of forming an intramolecular G-quadruplex structure.
|
16973897_p4
|
16973897
|
INTRODUCTION
| 4.243216 |
biomedical
|
Study
|
[
0.9995494484901428,
0.0002578578714746982,
0.0001926156401168555
] |
[
0.999194324016571,
0.00027534281252883375,
0.00045559124555438757,
0.00007471759454347193
] |
en
| 0.999998 |
Subsets and Splits
Clinical Cases Sample
Retrieves 100 samples of clinical cases, providing a basic overview of this specific document type.
High-Score Clinical Cases
The query retrieves a limited set of clinical case documents with a high educational score, providing a basic filtered view of the dataset.