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676d46fd6dde43c9086402b6 | 9 | The degree of functionalization or methacrylation of gelatins was assessed using proton nuclear magnetic resonance ( 1 H NMR) spectroscopy, following a previously reported method. All NMR spectra were recorded using a Bruker Advance 500 spectrometer (Bruker Scientific Inc., USA). To prepare the samples for NMR analysis, 20 mg of freeze-dried functionalized gelatin and unmodified gelatin were dissolved in 1.5 mL of deuterium oxide (D2O) at 40°C. |
676d46fd6dde43c9086402b6 | 10 | The solutions were then transferred to 5 mm NMR tubes, and all NMR spectra were acquired at room temperature. The degree of methacrylation was determined by quantifying the percentage of ε-amino groups of gelatins (lysine, hydroxylysine) that were functionalized by the addition of methacrylic anhydride (MAA). The calculation of the degree of methacrylation for functionalized gelatin was performed using equation 1. |
676d46fd6dde43c9086402b6 | 11 | The recorded NMR data was post-processed using MestreNova software (Mestrelab Research, Spain). The spectrum was phase and baseline corrected, and the desired peaks were integrated to determine the area under the peaks. The signals of phenylalanine (6.9 -7.5 ppm), indicative of gelatin concentration, were used for normalization of the NMR spectra. The lysine methylene signals (2.8 -3.0 ppm) from both unmodified and functionalized gelatin spectra were integrated to obtain the corresponding peak areas. |
676d46fd6dde43c9086402b6 | 12 | For the investigation of surface topography, a Zeiss SIGMA VP-FESEM (Thornwood, NY, USA) field emission scanning electron microscope was employed. Samples were carefully placed onto aluminum stubs using carbon tape to ensure secure attachment. Subsequently, a thin layer of iridium, approximately 5 nm in thickness, was sputter-coated onto the sample surfaces using a Leica EM ACE600 sputter-coater (Leica, Wetzlar, Germany). The microscope was operated standard EDT at an accelerating voltage of 5 keV. The working distance (WD) was set at 15 mm. The resulting images allowed for the analysis and characterization of the surface features, including morphology, texture, and microstructural details of the freeze-dried crosslinked hydrogel samples. |
676d46fd6dde43c9086402b6 | 13 | Porosity and pore size measurements were conducted using scanning electron microscopy (SEM) images of the hydrogel samples obtained as described previously. For each sample, a total of 8 random spots were imaged at 200x magnification for each test group. The images were analyzed using the Analyze Particles function in ImageJ software (National Institutes of Health, USA). First, the images were imported into the ImageJ software, and a scale was set to establish the pixel-to-distance ratio of the images. The images were then converted to 8-bit format, and the threshold was subjectively adjusted for each image to enhance pore visibility. Next, the Analyze Particles function was employed to calculate the average pore size (µm) and porosity (%) of the hydrogel samples based on the analyzed images. |
676d46fd6dde43c9086402b6 | 14 | Particle sizes were determined using the Mastersizer 3000 laser diffraction particle size analyzer (Malvern, Worcestershire, UK). The samples were added to the water tank of the Mastersizer while maintaining constant stirring. To ensure accurate measurements, sonication was employed for 60 s to break up any large particles present in the samples. Each sample was subjected to three measurements, with each measurement repeated five times to obtain reliable and representative results. The Mastersizer 3000 software was configured with specific settings for the analysis. In the software settings, the refractive index of gelatin was selected to account for the optical properties of the sample. Additionally, the software was configured to consider the non-spherical nature of the particles being analyzed. This data is then analyzed to determine the particle size distribution of the sample. |
676d46fd6dde43c9086402b6 | 15 | To investigate the water uptake behavior of the samples, the mass swell ratio was examined. Cylindrical disc-shaped hydrogels with dimensions of 16 mm × 5 mm were prepared following the previously described procedure. Immediately after photo-polymerization, the mass of the hydrogel constructs was measured. Subsequently, the hydrogel samples were placed in a well plate and submerged in MilliQ water before being incubated at 37°C overnight. This allowed the samples to absorb water and reach equilibrium swelling. After removing the samples from the water, any excess moisture was gently blotted using Kimwipes, and the swollen weight of the hydrogel samples was determined. Next, the samples were placed in a -80°C freezer overnight to facilitate freeze drying. The samples were then subjected to lyophilization at -50°C for 24 h, followed by the measurement of their dry weight. |
676d46fd6dde43c9086402b6 | 16 | Mechanical characterization of the samples was conducted using unconfined compression testing on an Instron 5940 Series Universal Testing System (Instron, USA) equipped with a compression clamp with a maximum load capacity of 10 kN. The samples were positioned between two parallel compression clamps, and the tests were carried out at room temperature. Prior to testing, the dimensions of the samples, including diameter and height, were recorded. The samples were subjected to unconfined static compression at a compression rate of 1 mm/min, and the testing was manually stopped upon reaching a compressive strain of 50-60%. The compressive Young's modulus was determined by calculating the slope of the regenerated data obtained from the best linear regression fit on the stress-strain curve within the range of 0 to 20% compressive strain. |
676d46fd6dde43c9086402b6 | 17 | To investigate the thermal behavior of the sample components, a simultaneous DSC/TGA analyzer (SDT Q600; TA Instruments Inc., DE, USA) was utilized. Approximately 15-25 mg of samples were loaded into an alumina pan specifically designed for Q600. The samples were then subjected to a heating process with a heating rate of 10 °C/min, starting from |
676d46fd6dde43c9086402b6 | 18 | Where 𝜎𝜎 is the shear stress (Pa), 𝑘𝑘 is the consistency coefficient (Pa.s n ), 𝛾𝛾 ̇ is the shear rate (s - 1 ), and n is the flow behavior index. The yield stress was not modeled using this procedure as this procedure was not sensitive enough to allow for accurate yield stress determination. |
676d46fd6dde43c9086402b6 | 19 | Using the same rheometer and geometry setup as described above, the rheometer was run under controlled stress mode to determine yield stress. Sample strain was monitored as the stress applied to each sample gradually increased in 0.1 Pa increments. Each stress was applied for 30 s and then increased to the next stress level to determine when sample flow was initiated (seen as a continuous increase in sample strain). This procedure allowed for more sensitive yield stress determination with 0.1 Pa being the experimentally determined yield stress sensitivity limit. Note, any yield stress below 0.1 Pa was not recorded, but yield stresses below 0.1 Pa may still exist in these samples. |
676d46fd6dde43c9086402b6 | 20 | The light absorption properties of the samples were analyzed using a UV-Vis spectrophotometer. The spectrophotometer used in this study was spectronic GENESYS 10 Bio (Thermo Scientific, USA). Approximately 1 mL of each sample was prepared and placed in a single-cell cuvette with a specific path length. The cuvette was then inserted into the spectrophotometer, and the absorbance spectrum was recorded over the desired wavelengths (365 and 405 nm). To ensure accurate measurements, Milli-Q water was used as a reference. |
676d46fd6dde43c9086402b6 | 21 | Pluronic 40% (w/v) was loaded into two separate 3 cc syringe barrels (Nordson EFD, Fluid Dispensing system, USA) at room temperature and centrifuged in an Avanti J-26 XPI centrifuge (Beckman Coulter, USA) at 1600 rpm for 5 min to remove air bubbles. The syringe barrel was connected to a nozzle (red gauge 25 and pink gauge 20) and loaded on an Allevi 3D bioprinter (Allevi, USA). Printing speed and path plan was controlled by programmed G-code. |
676d46fd6dde43c9086402b6 | 22 | The choice of porcine and fish gelatin for this study was driven by the distinct properties of each gelatin type, which offer complementary advantages when combined in a composite hydrogel system. The functional properties of gelatin can vary significantly depending on its source, influencing the behavior and stability of hydrogels in bio-fabrication applications. Porcine gelatin, derived from mammalian sources, has a high gel strength and gelation temperature compared to fish gelatin. This characteristic provides structural robustness, making porcine gelatin a valuable component for enhancing the mechanical integrity of composite hydrogels. However, porcine gelatin alone tends to gel rapidly at room temperature, which limits its usability in applications requiring prolonged fluidity, such as Digital Light Processing (DLP) printing. DLP relies on light-based crosslinking of a liquid or semi-fluid precursor to build complex 3D structures, and materials with rapid gelation can hinder this process. |
676d46fd6dde43c9086402b6 | 23 | Fish gelatin, on the other hand, has a lower gel strength and gelation temperature due to the lower content of proline and hydroxyproline, making it a more flexible and easily manipulated matrix under ambient conditions. Its relatively lower viscosity enables it to serve as a continuous phase in the composite, maintaining fluidity until photo-crosslinking is initiated. Fish gelatin's characteristics thus complement the rigidity of porcine gelatin, creating a composite hydrogel with both mechanical stability and processability for extrusion and DLP printing. The blend of these two gelatin types provides a tunable system where porcine gelatin microparticles reinforce the structure, while the fish gelatin matrix maintains the composite's printability and photoreactivity. |
676d46fd6dde43c9086402b6 | 24 | The scientific rationale for combining porcine and fish gelatin lies in the ability to finetune the composite's properties to match the requirements of advanced bio-fabrication methods. By leveraging the high gel strength of porcine gelatin and the lower viscosity of fish gelatin, this composite hydrogel achieves a balance between strength and printability, making it suitable for various 3D printing applications. |
676d46fd6dde43c9086402b6 | 25 | To make the selected gelatins compatible with light-based 3D printing, both fish and porcine gelatin were modified with methacrylic anhydride to introduce methacrylate groups, enabling UV or visible light crosslinking and precise control over hydrogel formation. Methacrylation, confirmed by NMR, directly influences the crosslinking density, affecting mechanical strength, swelling, and degradation of modified gelatin. |
676d46fd6dde43c9086402b6 | 26 | The degree of methacrylation, representing the proportion of gelatin functional groups substituted with methacrylate moieties, significantly influences hydrogel properties. It affects crosslinking density, mechanical properties, swelling behavior, degradation kinetics, and biocompatibility. Characterizing this parameter is crucial for tailoring hydrogel properties to specific applications and understanding structure-property relationships. Analysis shows clear differences in methacrylate substitution between low-bloom (gel strength ~175g) and high-bloom (gel strength ~300g) porcine skin gelatins (Figure ). Lowbloom gelatin exhibits a steady increase in substitution across methacrylation categories, whereas high-bloom gelatin shows a lower substitution, comparatively. This difference likely arises from variations in molecular weight distribution and amino acid (AA) composition, particularly the availability of lysine, hydroxylysine, and arginine residues, which methacrylate groups primarily target. Higher bloom-strength gelatins, with denser molecular networks and more crosslinking, may limit accessibility to these reactive AAs, reducing methacrylation efficiency. These findings emphasize that gelatin bloom strength significantly impacts methacrylation potential, which is crucial for designing UV-curable hydrogel systems. Tailoring methacrylation based on specific gelatin properties can enhance hydrogel mechanical performance and biocompatibility for biomedical applications. |
676d46fd6dde43c9086402b6 | 27 | The SEM images in Figure , taken from the cross-sectional area of freeze-dried samples, provide a clear view of the microstructural impact of methacrylation on the hydrogels. Freezedrying removes water content to expose the polymer network, revealing differences in pore structure stability across methacrylation levels. In low and medium methacrylation hydrogels, the pore walls appear thin and collapsed, with indistinct and irregular boundaries. This structural weakness likely results from insufficient crosslinking, which fails to support the pore walls during the freeze-drying process, causing them to shrink and lose their form. The reduced wall thickness and partially collapsed pores indicate a less stable network with limited mechanical integrity. Conversely, hydrogels with higher methacrylation display a wellpreserved, open porous structure with defined, thick pore walls. This intact network reflects strong crosslinking, allowing the hydrogel to maintain its structure under freeze-drying conditions. The prominent pore walls and uniform porosity in the highly methacrylated samples indicate robust structural stability and integrity. |
676d46fd6dde43c9086402b6 | 28 | The process for producing crosslinked porcine gelatin microparticles, as depicted in the schematic in Figure , involved multiple steps to achieve a consistent particle size distribution, with additional images and size data provided in is given as volume density (%) across different size classes in micrometers, highlighting a predominantly uniform distribution. Smaller particles with an optimal surface area-to-volume ratio enhance interaction with the methacrylated fish gelatin matrix, providing improved mechanical reinforcement. This consistency is particularly beneficial for applications requiring stable and mechanically reinforced hydrogel structures, such as tissue engineering scaffolds and drug delivery systems. |
676d46fd6dde43c9086402b6 | 29 | With increasing blending time, particle size decreased, as observed with scale bars for 1 min and 2 min set at 500 µm, 3 min at 250 µm, and 4 min and 5 min at 200 µm. These images confirm that extended blending leads to finer microparticles, supporting the selection of optimal parameters for achieving the desired particle size for incorporation into composite hydrogels. Although there are some differences in pore size, the variation across compositions is subtle, indicating that changes in MPG ratios produce only minor adjustments in pore size. The MPG hydrogel, with larger average pore sizes between 50 µm and 100 µm, exhibits a loosely crosslinked network that supports high swelling capacity but may compromise mechanical integrity. In contrast, MFG hydrogels have smaller pore sizes (~60 µm), suggesting a more compact and densely crosslinked structure that limits swelling but enhances compressive strength. Composite hydrogels, such as those with 3:7 and 5:5 ratios, display intermediate pore sizes, but overall, no strong trend is observed, implying that the effect of MPG ratio on pore size is limited. These results suggest that while varying the MPG composition slightly affects pore size and porosity, the overall trend remains small, indicating a minor influence on microstructural features. Nevertheless, MPG-rich hydrogels with larger pores and higher porosity support increased water absorption, while MFG-rich hydrogels with smaller pores offer structural stability. These insights guide the design of hydrogels for specific biomedical applications, where the balance between swelling capacity and mechanical integrity is key, such as in tissue engineering scaffolds and drug delivery systems. |
676d46fd6dde43c9086402b6 | 30 | The mass swell ratio, defined as the swollen hydrogel mass relative to its dry mass, was analyzed for various hydrogel compositions to assess water absorption capacity and network integrity, as shown in Figure . This metric provides insight into each hydrogel's porosity, crosslink density, and water affinity. The MPG hydrogel exhibited the highest mass swell ratio, ranging from 50% to 65%, indicating a high water affinity and a lower crosslink density, which allows for significant network expansion upon hydration. This behavior likely results from the hydrophilic nature of MPG, promoting water absorption and network swelling. In contrast, the MFG hydrogel showed the lowest mass swell ratio, around 30%, suggesting a denser crosslink structure and a more compact network. The reduced water absorption may be due to hydrophobic moieties within MFG that limit water penetration, resulting in a more stable and rigid network. |
676d46fd6dde43c9086402b6 | 31 | Composite hydrogels with microparticle ratios from 1:9 to 5:5 displayed intermediate mass swell ratios, reflecting a balance between the water-absorbing capacity of MPG and the structural integrity provided by MFG. Notably, a trend can be observed for composites 1:9 to 5:5 showing increasing swell ratios, suggesting that these ratios optimize hydrophilicity and network rigidity. |
676d46fd6dde43c9086402b6 | 32 | This swelling behavior offers guidance for hydrogel applications: MPG-rich hydrogels, with high swelling, are suitable for wound dressings, drug delivery, and absorbent materials, while MFG-rich hydrogels, with greater stability, suit load-bearing applications like tissue engineering scaffolds. Additionally, higher-swelling hydrogels likely have a larger pore size distribution after swelling. Adjusting MPG ratios enables fine-tuning of swelling properties, making these hydrogels adaptable for diverse biomedical and industrial uses. |
676d46fd6dde43c9086402b6 | 33 | The mechanical properties of composite hydrogels were assessed through compressive modulus and stress-strain measurements in both pre-swelling and post-swelling conditions This increased stiffness in MFG hydrogels is likely due to a denser, more tightly crosslinked network. Conversely, MPG and mixed microparticle compositions exhibit lower stress responses, suggesting a softer network structure. All hydrogels display nonlinear stress-strain behavior, indicating a combination of elastic and plastic deformation before failure. |
676d46fd6dde43c9086402b6 | 34 | After swelling, all hydrogels exhibit a decrease in stress values, which highlights water's softening effect on the network. However, MFG-based hydrogels retain relatively higher stress values and compressive modulus (Figure ), indicating superior structural resilience even when hydrated. The strain-hardening behavior in some hydrogels at higher strains further suggests robustness in structure despite swelling. This mechanical stability in MFG-rich hydrogels can be attributed to their compact network and strong interchain interactions. In both, pre and post-swelling, a trend of decreasing compressive modulus can be observed as the microparticle ratio increases. Table summarizes key thermal properties, including T5% (temperature at 5% mass loss), T50% (temperature at 50% mass loss), Tonset (temperature at initial detectable weight loss), |
676d46fd6dde43c9086402b6 | 35 | The rheological behavior of the prepolymer hydrogel composite slurries was assessed to evaluate their suitability for 3D printing applications, specifically regarding shear-thinning and yield stress, which are critical for extrusion-based and embedded printing. The slurries exhibited a shear-thinning (pseudoplastic) flow, where apparent viscosity decreased with increasing shear rate, as shown in Figure . This shear-thinning behavior is essential for extrusion-based 3D printing, as it allows for easy flow through a nozzle under applied pressure while maintaining shape fidelity once deposited. As the microparticle concentration exceeded 70%, the slurries transitioned to Bingham plastic behavior, showing both shear-thinning characteristics and measurable yield stress (Table ), which helps maintain structural stability in complex print geometries, essential for embedded 3D printing and ideal support bath. |
676d46fd6dde43c9086402b6 | 36 | This characteristic is desirable for 3D printing modalities, as materials with a low flow behavior index can better adapt to the flow requirements of the nozzle without excessive force. The consistency coefficient ( 𝒌𝒌 ), reflecting slurry thickness, also increased with microparticle addition (Figure ), contributing to structural integrity in printed forms by providing higher viscosity at low shear rates. Yield stress values, which became measurable at microparticle concentrations above 70%, suggest the slurry's ability to withstand deformation until a critical stress threshold is met, which is crucial for embedded printing where the material must support subsequent layers. This rheological property allows for printing complex, unsupported structures, enhancing stability in 3D printed constructs. Hydrogel formulations with higher absorbance and lower transmittance are likely to support rapid UV curing and higher crosslinking densities, enhancing mechanical stability. |
676d46fd6dde43c9086402b6 | 37 | Moderate absorbance and transmittance can allow for uniform curing throughout the hydrogel, while low absorbance and high transmittance may require prolonged UV exposure to achieve effective crosslinking, albeit with the risk of photodegradation. These findings highlight the importance of tailoring the optical properties of hydrogels to optimize UV curing conditions, enabling the design of photopolymerizable hydrogels with customized performance characteristics suitable for specific applications. Digital light processing (DLP) printing, a layer-by-layer photopolymerization technique using UV light, demonstrated the hydrogel's ability to achieve high-resolution constructs with precise geometries. As shown in Figure , the DLP setup includes a build plate, liquid resin reservoir, and UV light projection system that selectively cures specific areas to form intricate 3D structures. The hydrogel's compatibility with DLP printing is illustrated by its ability to produce microfluidic devices (Figure ) with internal hollow channels (~500 µm in diameter), as well as cell strainers with hexagonal wells (Figure ) that maintain structural integrity and fine detail. The successful resolution of these features is attributed to the hydrogel's fine-tuned rheological properties, which enable precise UV curing without significant resin diffusion. |
676d46fd6dde43c9086402b6 | 38 | The results are consistent with literature reports on hydrogel systems used in DLP printing, such as PEGDA-based materials, which also achieve high-resolution features but often lack the biomimetic properties provided by gelatin-based matrices. Compared to other methacrylated gelatin hydrogels reported in prior studies, the MFG hydrogel demonstrated improved control over internal channel formation and structural fidelity. Embedded 3D printing, which employs a support bath to stabilize printed structures during fabrication, further highlights the hydrogel system's versatility. As shown in Figure , I, the hydrogel-supported slurry bath enabled the successful extrusion and stabilization of a hollow spiral construct (~1.2 cm in diameter). The ability to print elevated, unsupported geometries without compromising structural integrity underscores the hydrogel's excellent rheological and viscoelastic properties. This capability compares favorably with other reported support baths, such as Pluronic F-127 composite, which can destabilize under extended print durations or complex geometries. The 7:3 MFG hydrogel support bath outperformed these systems by maintaining structural fidelity during printing and post-processing. |
676d46fd6dde43c9086402b6 | 39 | The spiral construct, visualized in both side and top views (Figure , I), demonstrates the embedded printing modality's potential for producing vascular-like networks and complex hollow structures. Similar studies in literature have achieved comparable results using alginatebased hydrogels in embedded systems. However, the MFG hydrogel provides additional advantages, such as improved biocompatibility, better integration with sacrificial inks, and tunable degradation rates, which are critical for applications like tissue scaffolding and biofabrication of vascularized tissues. |
676d46fd6dde43c9086402b6 | 40 | Traditional PEG-based hydrogels, while offering mechanical strength, often lack the celladhesive properties inherent in gelatin-based systems. Similarly, alginate hydrogels, widely used for embedded printing, provide good printability but suffer from limited tunability in degradation and mechanical properties. The combination of methacrylation and microparticle incorporation in the MFG hydrogel addresses these limitations, providing both structural customization and biomimetic features. Furthermore, the ability to switch seamlessly between DLP and embedded 3D printing broadens the scope of potential applications, from creating high-resolution microfluidic devices to fabricating large-scale tissue constructs with complex architectures. |
676d46fd6dde43c9086402b6 | 41 | This study demonstrates the successful development of a composite hydrogel system incorporating methacrylated porcine gelatin (MPG) microparticles within a methacrylated fish gelatin (MFG) matrix. The composite's unique combination of tunable mechanical properties, thermal stability, and controlled swelling behavior highlights its potential for diverse applications in tissue engineering, drug delivery, and regenerative medicine. By adjusting the size and concentration of MPG microparticles and optimizing the methacrylation degree of the MFG matrix, the hydrogels offer enhanced customization, allowing for precise control over key properties critical for biofabrication. The rheological analysis reveals that the shear-thinning and yield stress properties of these hydrogels make them particularly well-suited for extrusionbased 3D printing, while the photo-crosslinkable nature of MFG enables effective utilization in DLP printing. Although larger microparticles did not yield the anticipated reinforcement, findings suggest that particle size and morphology are crucial for network integrity, as irregular or oversized particles may act as structural defects. This study provides a foundation for further optimization of composite hydrogel formulations, positioning them as promising materials for advanced 3D printing applications in biomedical fields. |
6206bca10c0bf0490ee66ce3 | 0 | Many manufactured products such as dyes and oils, among others, have in their composition phenolic compounds that are of natural origin . They are present in vegetables in free form or linked to sugars (glycosides) and proteins . These compounds also lead to the polymerization of natural polyphenols such as lignin and melanin, besides forming an important class of antioxidants, which inhibit the oxidative degradation of organic or bio-organic molecules . The antioxidant activity of phenols against free radicals comes from their elimination role, which is related to their ability to react with radicals much more quickly than other organic substrates. For example, tocopherol (vitamin E) is mentioned as an efficient capture agent that can eliminate harmful peroxide radicals in the blood plasma . |
6206bca10c0bf0490ee66ce3 | 1 | Protonation and deprotonation processes in aromatic molecules such as phenols are important in organic chemistry and biochemistry . Through the deprotonation of phenol, the phenoxide or phenolate ion is formed, stabilized by resonance. In comparison with phenol, the phenoxide ion is more stable because of the high displacement of the negative charge on the aromatic ring. The resonance structures of phenol involve separation of negative and positive charges. Thus, phenol is more likely to form phenoxide, releasing the proton . |
6206bca10c0bf0490ee66ce3 | 2 | The preferred protonation sites for phenols have been discussed from an experimental point of view and theoretical . In super-acidic solutions, phenols are protonated in oxygen atoms, to form oxon ions (O-PhH + ), or carbon in the aromatic ring in the ortho (o-PhH + ), meta (m-PhH + ) or para (p-PhH + ) . |
6206bca10c0bf0490ee66ce3 | 3 | The relative extent of protonation in oxygen and carbon atoms and the position of protonation in carbons depend on several factors, such as electronic structure of the base, acidity and solvation properties of the medium and temperature . Theoretical studies have been dedicated mainly to the exploration of the intrinsic basicities in the different positions in phenol molecules and in the relationship between protonic affinities and ionization energies . |
6206bca10c0bf0490ee66ce3 | 4 | The acidity of phenols can be influenced by other groups linked to the ring . The presence of any substituent on the aromatic ring that can stabilize the phenoxide ion will tend to increase the acidity of the phenol. On the other hand, any substituent that destabilizes the phenoxide ion, increasing its negative charge, will decrease the acidic nature of the phenol. In other words, the presence of electron withdrawing groups in phenols will increase their acidity, while electron density donor groups reduce their acidity . |
6206bca10c0bf0490ee66ce3 | 5 | To measure the basicity of organic compounds in the gas phase, the proton affinity (PA) can be used. The proton affinity is defined as the negative of the enthalpy change for the reaction M (g) + H + (g) →MH + (g), being M a chemical species: molecule, radical or atom . The higher the PA, the stronger the conjugate base and the weaker the conjugated acid in the gas phase. The PA value also illustrates the role of hydration in Brønsted acidity in the aqueous phase . The relationships between the energies of the highest molecular orbitals (HOMO and other frontier orbitals; HOMO: Highest Occupied Molecular Orbital) and PA are often present for families of compounds, such as phenols. However, for a large number of compounds, the energies of their HOMOs do not present a good correlation with PA values . Accordingly, the question arose: why are HOMO energies good acid-base descriptors for some compounds and not for others? Faced with such limitations, another approach has emerged to understand chemical reactivity: the concept of FERMO (Frontier Effective for Reaction Molecular Orbital), proposed by Silva and Ramalho . |
6206bca10c0bf0490ee66ce3 | 6 | A strategy to quantify the location of the FERMO was developed, leading to the construction of the MOLPROJ software, based on the use of projection operators to build the molecular orbitals (MOs) by linear combination of atomic orbitals (AOs; the LCAO approach). In this same study , it was possible to determine the reaction site of a series of amines and describe their acid-base behavior. Thus, the location of the FERMO would indicate the orbital in which the reaction occurs and, consequently, would point to the most favorable location for protonation. |
6206bca10c0bf0490ee66ce3 | 7 | Other computational studies also look for different approaches to rationalize reactivity properties. One of these approaches is the study of the atomic charge distribution in molecules to quantify regioselectivity . Liu and coworkers proposed a method to simultaneously quantify electrophilicity and nucleophilicity using the Hirshfeld charge. This quantification is based on the Information Conservation Principle, which states that information must be conserved before and after a molecular system is formed. |
6206bca10c0bf0490ee66ce3 | 8 | It decides both where electrophilic and nucleophilic attacks will preferentially occur, but also dictates the amount of Hirshfeld charge distribution, which correlates with experimental scales of electrophilicity and nucleophilicity. In order to have the information conservation, the system that was formed is adjusted in order to have each one of the components loaded according to the contribution of its "stock" of electronic density. Therefore, the Hirshfeld charge should be a good descriptor for both electrophilicity and nucleophilicity . |
6206bca10c0bf0490ee66ce3 | 9 | Another very useful method for modeling molecule-molecule interactions are derived from a least squares fit to the electrostatic potential (ESP). ESP is one of the useful properties to acquire partial atomic charges suitable for modeling short-and long-range molecule-molecule interactions . The grid-oriented CHELP (Charges from Electrostatic potentials method) was the first method of its kind to be developed, being modified to CHELPG (Charges from Electrostatic Potentials using a Grid based method) by Breneman and Wiberg. The CHELPG method is less dependent upon molecular orientation than the original CHELP method in which partial atomic charges are fitted to reproduce the molecular ESP at a number of points around the molecule . |
6206bca10c0bf0490ee66ce3 | 10 | In addition to computational studies, experimental liquid-phase spectroscopy studies, mainly NMR and IR spectroscopy, were widely used to locate the preferred protonation site (s) of the phenol and benzene molecules substituted as a function of solvent and temperature . To produce information about the competitive protonation in the substituents in substituted aromatic compounds, in addition to the protonation in the ring itself, it is necessary to separate the effects of the solvent from the molecular electronic properties, whose investigations must be made in the gas phase . |
6206bca10c0bf0490ee66ce3 | 11 | The spectroscopic data, particularly those from NMR, are sufficiently accurate to unambiguously identify the protonation sites in aromatic compounds. Experimental information on protonation in the gas phase also comes from mass spectrometry studies involving proton transfer reactions . Even though these studies have shown the existence of several protonated isomers of many aromatic ions, and in some cases also the specific locations of the protons, the details of their structures constantly remained confused. For these cases, the structural attribution of the various isomers sometimes depended on computational chemical calculations . |
6206bca10c0bf0490ee66ce3 | 12 | In this article, we seek to locate the frontier molecular orbitals involved in the protonation reactions of substituted phenols using the FERMO concept, quantifying the orbital coefficients of the carbon and oxygen atoms involved. Once these orbitals are identified, we seek to compare the computational results with experimental NMR data obtained in the literature. In addition, we also search to computationally evaluate these stereo-electronic effects that govern reactions of aromatic electrophilic substitution using an experimental study as an example. |
6206bca10c0bf0490ee66ce3 | 13 | The description of the solvent model was carried out with the Polarizable Continuum Model (PCM) using the integral equation formalism variant (IEFPCM). No symmetry restrictions were imposed during the optimization process. No imaginary frequencies were found for the optimized geometries, which were used in all subsequent calculations and had their single point energies determined with the same functional and basis set. |
6206bca10c0bf0490ee66ce3 | 14 | MOs figures were prepared using Avogadro software with a contour value of 0.010. The charge calculations have been performed with Gaussian 09 . The Hirshfeld and CHELPG (Charges from Electrostatic Potentials using a Grid based method) charges are obtained from the population analysis with the keyword pop= hirshfeld and pop=chelpg, respectively. |
6206bca10c0bf0490ee66ce3 | 15 | Considering the Brönsted-Lowry acid-base concept, the MO that drives the protonation reactions of the investigated phenols must be centered on the atoms that bind to the proton. Using the software developed in our group, MOLPROJ , the investigation of these orbitals was carried out in a quantitative way from the output data generated by GAMESS. |
6206bca10c0bf0490ee66ce3 | 16 | being 𝐶 𝑙𝜇 the matrix of the coefficients of the molecular orbitals and the Gaussian 𝜁 𝑙 (𝑥)AOs. These are created as an orthogonal set of vectors, which have components in each atomic orbital of a given molecule. The 𝑆 𝑖𝑗 overlap matrix is then defined by the set of AOs 𝜁 𝑙 (𝑥), which forms a set of non-orthogonal bases : |
6206bca10c0bf0490ee66ce3 | 17 | The projector can be understood as the projection of a "shadow" of a selected MO in the subspace of a set of AOs , thus making it a quantitative characterization of the shape of MO in a set of AOs and, consequently, a set of atoms. Thus, it is possible to define the degree of localization ΓFERMO: it is the norm of an MO projected on the expected set of atomic orbitals, which are important and that participate in the reaction of a certain compound, as follows in Equation 4 : |
6206bca10c0bf0490ee66ce3 | 18 | Using the MOLPROJ software, optimized structures of the selected compounds were analyzed using their MOs eigenvectors and overlap matrices, both extracted from output files of single point energy calculations with GAMESS. The degree of localization for each MO and their respective energies were calculated and analyzed. For this, the PG projection operators were applied to all 2px-z orbitals of aromatic carbon atoms as for the hydroxyl oxygen atom. Subsequently, we calculated the coefficients of degree of localization for the HOMO and FERMO molecular orbitals (ΓHOMO and ΓFERMO) for comparison. These coefficients are shown in Table , together with the corresponding MO energies. A: HSO3F/SbF5 ; B: H2SO4 ; C: HSO3F ; D: CF3SO3H From these data, two doubts emerged: (1) is the reaction site pointed by the software in accordance with experimental results found in the literature, based on NMR? |
6206bca10c0bf0490ee66ce3 | 19 | We know that even simple molecules have favorable sites for protonation and that the preferred site depends significantly on its chemical environment. Much of the experimental information on protonation processes in gas phase came from mass spectrometry studies involving proton transfer reactions . These studies revealed the existence of several isomers of MH + ions, and, in some cases, specific . |
6206bca10c0bf0490ee66ce3 | 20 | Using data from literature about protonation of phenols based on NMR techniques, as can be seen in Table , we performed an analysis of the protonation sites as pointed by NMR technique and by the MOLPROJ software (Table ). Literature data for protonation of phenols through NMR technique was indeed rare and, therefore, there is not a large number of samples. |
6206bca10c0bf0490ee66ce3 | 21 | As it can be seen, in some cases, and as previously discussed, the protonation site changes according to the chemical environment in which the compound is present. In our calculations, we used the water as implicit solvent and at the same temperature. Due to the scarcity of data in the literature for computational reproduction of the experimental solvation environment (i.e, H2SO4, HSO3F or CF3SO3H in aqueous solution), we chose to describe the system only in implicit water, considering that, experimentally, water would already be the more abundant species. As there could be more than one protonation site, we compared the experimental reaction sites with the values of the location coefficients Γ generated by MOLPROJ for the frontier orbitals related to the atoms corresponding to these sites, checking which ones had the highest Γ values (above 0.4) between the possible protonation sites. It was done for all compounds. We start from the premise that atoms with higher location coefficients, as returned by MOLPROJ, contribute better to the protonation sites and to the construction of the involved boundary molecular orbitals. |
6206bca10c0bf0490ee66ce3 | 22 | Pictures of the highest MOs for each compound are shown in Figure . The Γ coefficients from HOMO to HOMO-3 for O and C1-C6 atoms of all compounds can be find in Supplementary Material. For the simplest compound, phenol (01), protonation in H2SO4 medium occurs only in the oxygen atom. An analysis performed with the MOLPROJ software returned a slightly higher Γ coefficient value for the HOMO-2 (0.505728), located at the oxygen atom, in relation to the HOMO orbital (0.500961), which is mainly located at the C4 carbon atom (the para-hydroxy carbon; Figure ). With that, it can be understood that protonation would be more favored in this oxygen atom, which agrees with the experimental results in H2SO4 solvent, indicating that, in this case, HOMO-2 is the FERMO of the reaction. Analyzing the figure of the orbitals for compound 01, we can see that HOMO-2 describes the protonation site better than the HOMO-1 orbital. |
6206bca10c0bf0490ee66ce3 | 23 | The p-fluoro compound 3 shares the same 100% experimental protonation in the oxygen atom in H2SO4. For this compound, the MOLPROJ software returned the HOMO-2 as the FERMO of the reaction (centered at the oxygen atom). As with compound 01, HOMO-2 has a high localization coefficient Γ value in the oxygen atom (0.505810 over 0.454808 for the HOMO at C4). Thus, we understand that HOMO-2 would be the FERMO of this reaction as well. In the same way as compound 1, based on the analysis of the shape of the orbitals in Figure , it is possible to verify that HOMO-2 has, in fact, the characteristics of a favorable location for protonation. |
6206bca10c0bf0490ee66ce3 | 24 | For the compounds 07, 12 and 13, experimentally protonated only at the C4 carbon atom in HSO3F (with/without SbF5) or CF3SO3H, the MOLPROJ software returned sufficiently high (higher than 0.4) Γ coefficient values only for the HOMO, mainly located at the C4 carbon atom (Figure ). In these compounds, the HOMO is the FERMO of the reaction. |
6206bca10c0bf0490ee66ce3 | 25 | The compound 11, also with a high Γ coefficient value for its HOMO at C4 carbon and for HOMO-1 at C2 (Figure ), was experimentally protonated at C2 and, in less extension, at C4. For the protonation of 2,4,5-trimethylphenol (09), the experimentally preferred site in the presence of HSO3F was the C4 carbon (85% protonation), accompanied by about 15% protonation in the C6 carbon. Our MOLPROJ software returned that the three largest location coefficients were found at carbon C4, C3 and carbon C6 (0.487159, 0.492505 and 0.539112, respectively). It can be seen that, when the protonation occurs at C4 (para), the reaction orbital is the HOMO. When it occurs at C6 (ortho), the orbital that is describing the reaction is the HOMO-1. Therefore, both orbitals are the FERMOs of the reaction (Figure ). |
6206bca10c0bf0490ee66ce3 | 26 | Finally, for the compounds 05 and 08, it was observed that some protonation sites were different from those experimentally found. In 05, the C4 and C5 carbon atoms would be protonated according to MOLPROJ but, however, it was experimentally observed that protonation occurred at C4 and C6. We attribute this to the fact that the MOLPROJ analysis is based only on electronic effects and the fact that there is a mixture of solvent, which makes computational analysis difficult. Also because the studies used as reference are relatively old and the parameterization of implicit solvation calculations containing solvent mixtures is extremely difficult. We mean that, based on the analysis of MOs, the software helps to determine which AOs are relevant for the reaction center of a given compound. |
6206bca10c0bf0490ee66ce3 | 27 | An alternative to such approach is to apply electron density localizations at the respective atomic sites as the measure of reactivity, specifically for the protonation reactions considered. According to Liu (2014) , the Hirshfeld charge can determine regioselectivity. As the Hirshfeld charge is derived from the Conservation of Information Principle, which requires that atomic identity be maintained as much as possible in molecules. So, this charge can reflect the electronegativity or the electropositivity nature of atoms. Therefore, the regioselectivity can be evaluated by using Hirshfeld charges . |
6206bca10c0bf0490ee66ce3 | 28 | When the direct analysis of the values of the Hirshfeld charges was performed, that is, direct analysis of the charges on the atoms involved in the protonation reaction, it was observed that the most negative values were present in the hydroxyl oxygen and in the methyl substituents and in the fluorine. Considering only the carbons of the benzene ring and oxygen and that there was at least one hit in the protonation site when compared to the experimental protonation site, 69.23% of hits were obtained (01, 02, 03, 05, 06, 08, 09, 10 and 11 compounds). |
6206bca10c0bf0490ee66ce3 | 29 | When the charge difference analysis was performed , with phenol being the standard of Hirshfeld charge (∆Hirsh ) values compared with the insertion of substituents in phenol, 46.15% (01, 06, 08, 10, 11 and 12 compounds) of correct answers were obtained. The analysis of the CHELPG charges was done in the same way as the Hirsfeld charges, in a direct way. Reaching 61.53% hits (01, 02, 03, 06, 09, 10, 11 and 12 compounds) with a correct answer. |
6206bca10c0bf0490ee66ce3 | 30 | As the MOLPROJ it is still a code under development, we will continue to seek in future works to evaluate better the effects of solvents on molecular orbitals. However, even considering that these compounds were computationally studied in an aqueous medium, without the appropriate experimentally applied solvents and compared to experimental results in different phases, we obtained 86% of correctness of the protonation sites using the developed software. We mean that 11 compounds (01, 02, 03, 04, 06, 07, 09, 10, 11, 12, 13) presented exact results when compared to the experimental results and the Hirshfeld and CHELPG charge methods. |
6206bca10c0bf0490ee66ce3 | 31 | In a second step, we validated, through a computational study using MOLPROJ, an experimental approach regarding the ortho-cyanation reaction of phenols to obtain aromatic nitriles by means of Lewis acids . The importance of aromatic nitriles comes from the fact that they can be easily converted into a variety of valuable syntones, such as ketones, aldehydes, amines, among others, conferring them an important role in synthetic chemistry . |
6206bca10c0bf0490ee66ce3 | 32 | According to Zhang, Yang and Zhao , authors of the study under consideration, the control of regioselectivity with 3,4-disubstituted phenols is still a significant and challenging work, which remains unsolved. So, they proposed to develop a selective method for C-H ortho-cyanation promoted by Lewis acid in 3-substituted and 3,4-disubstituted phenols in two different ortho positions, as can be seen in Figure . After an initial step for optimizing reaction conditions, in which it was stablished that the reaction would be best conducted under a combination of both AlCl3 and BF3 • OEt2 as Lewis acid catalysts and CH3SCN as cyan donor, they explored the scope of its reaction through the cyanation of 3-substituted and 3,4-disubstituted phenols to afford a wide range of the corresponding 2-hydroxybenzonitriles in good or excellent yields and with enhanced regioselectivity. and Zhao . |
6206bca10c0bf0490ee66ce3 | 33 | In order to explain their results, the authors proposed a mechanism in which the intermediate I (Figure ) is generated from the 3-substituted phenol and BF3 • OEt2 as it can be seen in Figure . For this step, the compound meta-cresol was chosen as model. These two structures were generated through optimization with B3LYP/6-31G(d,p). According to the authors, C2 and C6 would be the ring carbons favorable for cyanation but the reaction in C6 would happen in a major way. Their explanation for the preference of TS1 formation is related to the steric hindrance at the C3 meta-substituent, therefore unfavoring the formation of TS2. Based on this assumption, we obtained the values of the coefficients Γ over C2 and C6 for both structures A and B in Figure . The data returned by the MOLPROJ software and the experimental cyanation site are shown in Table . As it can be seen in Table , the site for ortho-cyanation reaction indicated by MOLPROJ corresponds to C2, which is does not correspond to the experimental results, pointing to C6 as the experimental site. The MOs analysis identified the HOMO-1 as the FERMO for the ortho-cyanation reaction instead of HOMO. The ΓHOMO-1 coefficients calculated by MOLPROJ showed higher values for C2 than for C6 for both A and B. In From these results, another question arose: would this reaction be coordinated by steric or electronic effects (or even by both)? To answer this question, we decided to replace the 3-methyl group by an isoelectronic and smaller fluorine atom in the new structures A' and B' and running only single point calculations with the same base. We did this because 3-fluorophenol was one of the 3-substituted phenols examined in the scope of the selective ortho-cyanation reaction substrate in the article . According to the results returned by MOLPROJ, the main reaction site, when a meta-fluorine atom is present, remains at the C2 atom in the aromatic ring, as can be seen below in Table . Looking at the results, we can see that the reaction path depends on two factors: |
6206bca10c0bf0490ee66ce3 | 34 | This electronic repulsion then makes it difficult to approach the substituent, making the electrophilic substitution reaction unfeasible, as occurs in the studied reaction. Now thinking about lower size groups, as in the case of fluorine, we can think about nonclassical models. In other words, we are analyzing the electronic density of FERMO to correctly predict which carbon atoms would be the reaction site of this reaction. |
6206bca10c0bf0490ee66ce3 | 35 | The MOLPROJ software, based on the use of projection operators for quantifying the FERMO localization, was employed again successfully now for phenol protonation. The FERMO concept can be applied to find the protonation site for phenols. It was possible, even with different environments in which the experimental compounds were inserted, to have an idea of the preferred protonation site of these molecules. We obtained approximately 86% of correctness of the protonation sites using our theoretical methodology. It was also possible to rationalize a reaction with only experimental results that the reaction path depended on two factors: the size of the substituent and its position. |
62a98d561fdc3450d63a8077 | 0 | An alternative approach to the substitution of halopyridines is to employ pyridine-N-oxides (or benzo-fused variants) in conjunction with an electrophilic activating agent. In this way, a similarly broad range of active methylene nucleophiles may be heteroarylated, 8 along with alternative nucleophiles such as silyl ketene acetals and aldehydes (under conditions of enamine organocatalysis). We have previously reported the use of azlactones as nucleophiles for the substitution of activated pyridine-N-oxides. The intermediate azlactones served as electrophiles which could be opened with a diverse range of nucleophiles (alcohols, amines, organometallics and hydride reagents) to give -disubstituted amino acid derivatives; 12a alternatively, the use of water as a nucleophile triggered a hydrolysis/decarboxylation sequence to achieve a formal 'umpoled' synthesis of 2-(1-amidoalkyl)pyridines. We envisaged that a general synthesis of diverse pyridylcarboxylate derivatives would be possible using Meldrum's acids in place of azlactones (Scheme 1). Thus, activation of pyridine-N-oxides 1 and nucleophilic substitution by the Meldrum's acid derivatives 2 would generate an intermediate which could act as an electrophilic partner for ring-opening by a range of nucleophiles; the resulting carboxylic acids would undergo facile decarboxylation to yield the desired products 3. Below we describe the successful implementation of this simple three-component approach to substituted pyridylacetic acid derivatives, along with an investigation into the substrate scope of the process. |
62a98d561fdc3450d63a8077 | 1 | We began by investigating the coupling of 5-methyl Meldrum's acid 2a with pyridine-N-oxide 1a under our previously-developed activation conditions using tosyl chloride and triethylamine. On completion of the substitution reaction, the solvent was swapped for methanol and sodium methoxide added. We were pleased to find that the desired 4-pyridylsubstituted propionate ester 3a was isolated in 63% yield as a single regioisomer, and so examined the scope of the coupling of 2a with various substituted pyridine-N-oxides 2 (Table ). Substitution at the 4-position was also observed with 2-and 3methylpyridine-N-oxides 2b/c to give esters 3b/c, while when 4-substituted pyridine-N-oxide substrates were employed, clean substitution at the 2-position was observed. TABLE 1. Three-Component Coupling: Scope of the Pyridine-N-oxide. |
62a98d561fdc3450d63a8077 | 2 | Alkyl (3d,e) and aryl (3f) substituents were well tolerated. The presence of an electron-donating alkoxy group was also tolerated, albeit that 3g was formed in a slightly lower yield, as was bromo-substituted 3h. Finally, isoquinoline-N-oxide and quinoline-N-oxide gave somewhat lower yields of the substitution products 3i,j, the latter as an effectively equimolar mixture of regioisomers. |
62a98d561fdc3450d63a8077 | 3 | Variation of the carboxylate side-chain was investigated using substituted Meldrum's acids 2b-i, which were prepared using a modified one-pot reductive coupling of Meldrum's acid itself with aldehydes, mediated by sodium triacetoxyborohydride (see Supporting Information). The resulting nucleophiles were reacted with pyridine-N-oxide 1a under the standard conditions, then subjected to methanolysis/decarboxylation (Table ). While Meldrum's acid itself gave only a moderate 29% yield of the (4-pyridyl)acetate 3k, the efficiency of the process for substituted variants 3l-s was relatively unaffected by the nature of the side-chain, with all yields falling in the range 52-65%. In all cases, the products were isolated as single regioisomers (4-substitution). |
62a98d561fdc3450d63a8077 | 4 | Finally, we examined the scope of the nucleophilic partner. Activation of 4-methylpyridine-N-oxide 1d with tosyl chloride and substitution with methyl-substituted Meldrum's acid 2a was carried out as normal; following removal of the solvent, the resulting crude material was exposed to different nucleophilic ring-opening conditions. The formation of different esters was achieved conveniently by treating the intermediate with a mixture of the relevant alcohol and potassium tertbutoxide in THF at room temperature: in this way, benzyl ester 3t and allyl ester 3u were prepared in yields similar to that of 3d from the methanolytic procedure. We also investigated the use of an organometallic nucleophile, and found that exposure to iso-butylmagnesium bromide at -40 o C gave, after warming to room temperature and aqueous work-up, the ketone 3v in 39% yield. Finally, we examined the use of amine nucleophiles. The crude intermediate was taken up in toluene, the relevant amine added, and the mixture heated in a sealed microwave vial at 200 o C for 20 minutes. Following cooling, extractive work-up and purification, good yields of the resulting amides 3w-ab were obtained. The reaction worked well with both primary and secondary amines, including less nucleophilic aromatic amines such as indoline. |
62a98d561fdc3450d63a8077 | 5 | [a] other alkoxides [b] organometallics [c] primary amines [d] In summary, a convenient new approach to the synthesis of diverse substituted 2-(pyridyl)acetic acid derivatives is reported utilising Meldrum's acids as linchpin reagents, acting initially as nucleophiles to effect substitution at activated pyridine-N-oxides, and subsequently as electrophiles to trigger ring-opening and decarboxylation. Distinct from approaches that utilise halopyridine substrates, the process avoids the need for metal catalysts, pre-formed enolate equivalents (e.g. silyl ketene acetals) or strongly basic species, as well as obviating the need to handle potentially decarboxylation-sensitive pyridylacetic acids themselves. Additionally, the three-component nature of the process lends itself well to the ready generation of analogues through parallel synthesis protocols. The method therefore complements existing approaches to this class of biologically-relevant molecules and we hope will prove of use to the community. |
65c9f0bf9138d23161ecc7b7 | 0 | Discrete three-dimensional (3D) organic and metal-organic (porous) cages have emerged as promising biomimetic systems. They offer synthetic modularity and tunability, enabling chemists to efficiently create structures with customized sizes and shapes from simple building blocks. A critical factor contributing to their functional properties is the presence of a welldefined inner cavity capable of binding and even catalyzing chemical reactions, prompting chemists to draw parallels between these systems and enzymes. In molecular cages, the affinity of the host towards a particular guest depends on various structural and electronic parameters. A key structural parameter used to assess the ability of a cage to act as a host is the relative cavity size of the cage and guest molecules. For instance, Rebek determined that 'closed' organic capsules exhibit binding when the guest occupies around 55% of the host cavity volume. Since then, this rule has been extended to other supramolecular structures with varying success, and also to enzymes. Several tools have been developed for the identification and characterization of protein binding pockets based on grid, rolling probe, or tessellation algorithms, including VOIDOO, McVol, Volarea, GRASP, CAVER, CAST, HOLLOW, MDpocket, ProteinVolume, 3V, Voronoia, PoreBlazer, Zeo++, and CavVis. However, most of these cannot be easily adapted for supramolecular cages, and software exclusively dedicated to cage architectures is scarce, with PyWindow, and MoloVol being the only notable examples. |
65c9f0bf9138d23161ecc7b7 | 1 | Most of these programs designed for proteins and cages utilize a rolling probe algorithm, typically using one or two probes. The one-probe algorithm is best suited for cavities with small windows, which are the apertures within a cage structure connecting its enclosed cavity with the external environment. This algorithm defines the cavity as the volume enclosed by a probe "rolling" around the entire cage structure without escaping (Figure ). However, a limitation of the rolling one-probe algorithm is its failure when the probe's radius is smaller than the cage's windows, causing the probe to escape and leading to an overestimation of the volume. This problem can be solved by increasing the probe size to prevent it from escaping, but this underestimates the cavity volume as the gaps between the probe and the atoms of the cage are larger. |
65c9f0bf9138d23161ecc7b7 | 2 | On the other hand, the rolling two-probe algorithm is suitable for cavities with larger windows, solving the probing escaping from the cavity issue encountered in the one-probe method. In this approach, the cavity is defined as the volume enclosed by a small probe, which cannot escape, when a second, larger probe blocks the cage's windows (Figure ). However, the two-probe rolling method can fail if the radius of the larger probe is too small, allowing it to move inside the cavity through the cage windows, and resulting in inaccurate volume calculations. In contrast, if the larger probe is too big, the calculated volume is overestimated by an "artificial volume" generated by the gap between the larger probe and the cage atoms. Indeed, this is a significant limitation of the rolling probe algorithm, as the success of the cavity volume calculation depends on the user-defined probe(s) radii, which must be carefully chosen and may not be universally applicable to all systems. Therefore, the results can be improved by a delicate fine-tuning of probe(s) radii in systems with large windows. This process is laborious and difficult to generalize across different systems or when analyzing molecular dynamics (MD) trajectories, where the window sizes dynamically change along the simulation time. Alternatively, one can calculate the largest sphere that fits into the cavity, as done in PyWindow, but this compromises the accuracy of the computed volume as cavities in cages often deviate from a perfect spherical shape. |
65c9f0bf9138d23161ecc7b7 | 3 | To address the limitations of the rolling oneand two-probe methods for cavity calculation, we have developed an approach that uses an angle measurement technique (Figure ). This method relies on determining the angle θ formed by the center of mass (COM) of the cage, the probe, and the atom of the cage. For probes that do not overlap with cage atoms, one calculates the average of all angles θ for each cage atom within the threshold distance (automatically calculated as the diameter of the maximum escape sphere from the cavity). If the average angle is greater than 90º the probe is considered to be inside the cage; otherwise, it is considered to be outside of the cavity. |
65c9f0bf9138d23161ecc7b7 | 4 | The angle-based method offers a practical, easy-to-implement, and computationally efficient method that eliminates the need for manual parameter optimization, facilitating automated analyses across cages of different sizes, shapes, and window dimensions. In addition to host-guest size complementarity, guest binding is significantly influenced by electrostatic, hydrogen bonding, and Van der Waals interactions with the host, which can be significantly affected by the solvent. For example, in water, the hydrophobic effect plays a key role in driving guest binding. Ward and coworkers demonstrated that hydrophobic guests exhibit 2-3 orders of magnitude higher association constants compared to polar guests, Similarly, Ballester and coworkers established a linear relationship between binding free energies and the surface area of the non-polar guests' fragments, indicating a hydrophobic effect of 33-38 cal mol -1 Å -2 . Electrostatic complementarity is often visualized through electrostatic potential (ESP) surfaces. Molecular ESP can be calculated using ab initio methods or from charge distributions obtained by numerically solving the Poisson-Boltzmann equation or its approximate form, the generalized Born model. Additionally, hydrophobic interactions can be indirectly estimated using methods based on hydrophobic-lipophilic interactions (HLI), which quantify the tendency of nonpolar molecules to avoid contact with polar solvents, inducing aggregation and self-coiling. Another parameter, molecular hydrophobicity potential (MHP), derived from 1octanol/water partition coefficient (logP), has proven useful in describing hydrophobicity in proteins, analyzing protein pockets in docking engines, and predicting protein-ligand binding affinities. However, despite its utility in ligand-protein binding analysis, the MHP descriptor has not been commonly used to analyze cage cavities, likely due to the lack of userfriendly tools for their generation. |
65c9f0bf9138d23161ecc7b7 | 5 | In this work, we introduce C3, a tool that calculates the cavity size electrostatic and hydrophobic potentials of molecular cages. The developed Python module can be used from the command line, python script, or as a plugin to the molecular visualization program PyMol. Overall, the developed module enables the efficient characterization of cavity and host-guest properties. |
65c9f0bf9138d23161ecc7b7 | 6 | Herein, we outline the methodology and demonstrate the ability of C3 to determine the cavity volume of molecular cages with diverse sizes and shapes. We illustrate the utility of C3 and highlight its advantages in terms of accuracy compared to rolling probe methods when assessing cavities of varying cages. Furthermore, we employ C3 to compute the MHP and ESP surfaces in the calculated cavities aiding the determination of host-guest properties. |
65c9f0bf9138d23161ecc7b7 | 7 | C3 is a stand-alone Python module designed for the characterization of organic and metallocage cavities. It employs scientific programming libraries, including NumPy, SciPy, and scikitlearn. Optional functionalities can be enabled using the chemical programming libraries RDKit, MDAnalysis, OpenBabel, and cgbind, which facilitate the handling of chemical structures, including the identification of functional group and the calculation of molecular properties. |
65c9f0bf9138d23161ecc7b7 | 8 | The core of the code is based on the Cavity class, featuring several functions: file reading, center of mass calculation, 3D grid setup, identification of grid points within the cage calculation. Of MHP and ESP, and the subsequent saving of results in PDB and/or PyMol formats. Additionally, the GridPoint and CageGrid classes define attributes associated with each grid point in the 3D grid. The code also includes different functions for assigning hydrophobic values to the cage atoms, computing partial charges of the cage atoms, and calculating the maximum radius escape sphere, among other functions (See SI §S1 for a full description). Additionally, it offers a PyMol plugin with the corresponding C3 graphical user interface to set up all calculation parameters of C3 (see details in SI). Figure illustrates a simplified schematic diagram of C3 functionality. |
65c9f0bf9138d23161ecc7b7 | 9 | Upon loading the 3D cage structure into C3, a 3D grid filled with grid points is generated, with customizable size and grid spacing (default parameters are described in SI §S2). The cavity size is then calculated by iteratively examining all grid points to determine whether they form part of the cage cavity. |
65c9f0bf9138d23161ecc7b7 | 10 | Once the cavity size is calculated, several properties can be computed using the molecular properties of each cage atom. These properties include aromatic contacts, solvent-accessible surface area (SASA), hydrophobicity (MHP), and/or electrostatic potential (ESP). The calculated values are stored as the B-factor in the generated cavity PDB file, facilitating their visualization in any standard molecular visualization software. Subsequent sections detail each of these steps. |
65c9f0bf9138d23161ecc7b7 | 11 | The first step in C3 involves loading the cartesian coordinates of the cage structure obtained by the user from either a crystal structure (CIF files) or via molecular modeling, employing software such as Stk or cgbind. C3 supports various molecular file formats such as .xyz, .pdb, .mol, .mol2, and others handled by MDAnalysis. The plugin stores the atom types and the cartesian coordinates in NumPy arrays. |
65c9f0bf9138d23161ecc7b7 | 12 | In C3, the cavity volume calculation is performed without requiring user-defined parameters, as the default settings yield satisfactory results across a wide range of cages. The algorithm starts by generating a box around the cage structure with dimensions to fit all cage atoms followed by the generation of a 3D grid. By default, the grid spacing is set to 1 Å, but users can modify it. For example, for cavity volumes exceeding 5000 Å 3 a grid size of 2 Å will be equally accurate and reduce computation time. The calculation of the cavity volume involves iterating over grid points and classifying them as either part of the cavity or outside of it. This selection involves two steps: |
65c9f0bf9138d23161ecc7b7 | 13 | (b) For each grid point the cavity angle θ is calculated as the angle between two vectors: the vector defined by the center of mass of the cage (COM) and the selected grid point k (COM-GPk), and the vector defined by the selected grid point k and the atom of the cage i (GPk-CAi)(see description of the angle in Figure ). The θ angle is calculated for each cage atom i in the threshold distance. |
65c9f0bf9138d23161ecc7b7 | 14 | The process of iterating over all cage atoms within the threshold distance is sped up by using the SciPy Spatial KDTree algorithm, which partitions multidimensional data into a binary tree structure, enabling efficient nearest-neighbor searches and spatial queries. To achieve this, the cartesian positions of all cage atoms are stored in a KDTree dictionary by atom types, significantly reducing the time required for obtaining atoms within a threshold distance compared to brute-force iteration. Once the iteration over all grid points in the grid is completed, and all grid points are assigned as within or outside the cavity, C3 uses a DBSCAN clustering algorithm to identify the main cavity region, disregarding isolated grid points that do not correspond to the cavity. In cases where more than one cavity is identified, the main cavity is selected based on the largest cluster, or alternatively, the cluster closest to the cage center of mass. |
65c9f0bf9138d23161ecc7b7 | 15 | After extensive testing, we developed an algorithm that effectively addresses challenges encountered in dealing with large cavities, where the rolling probe method fails due to the inner probe escaping from the cavity. This is demonstrated when considering Cage 1, an organic cage that features eight large windows, originally reported by Yuan and coworkers (Figure ). In this system, the rolling two-probe method implemented in MoloVol struggles as the smaller probe escapes through the windows, thus requiring the use of a large radius for the outside probe (Figure ). This causes an overestimation of the volume due to the gap generated between the cage and the probe. For Cage 1, the rolling two-probe method in MoloVol, using a probe radius of 11 Å and 1.4 Å for the large and small probe and a grid resolution of 0.5 Å, results in a volume of 8,934 Å 3 (Figure ). However, this value represents an upper limit, as an "artificial volume" is generated by the gap between the cage and the probe. Attempts to minimize this "artificial volume" by reducing the large probe radius to 10 Å resulted in the large probe entering the cavity. |
65c9f0bf9138d23161ecc7b7 | 16 | To overcome this limitation, Yuan et al. manually blocked the cage windows using a "virtual plane", obtaining a volume of 7,026 Å 3 using the one-probe rolling probe method (probe radius of 1.4 Å) using VOIDOO (Figure ). Utilizing C3, with a 2.0 Å grid spacing, we obtained a volume of 6,800 Å 3 , which is comparable to the volume obtained by Yuan and coworkers (Figure ). |
65c9f0bf9138d23161ecc7b7 | 17 | MoloVol, obtaining a volume of 226 Å 3 using a large probe radius of 3 Å, a small probe radius of 1.0 Å, and a grid resolution of 0.5 Å (Figure ). These results are therefore in line with the expected good performance of rolling probe methods when considering cages with small window sizes. |
65c9f0bf9138d23161ecc7b7 | 18 | To demonstrate the utility of the C3 algorithm, we tested it in 23 algorithm using MoloVol with a large probe radius of 3 Å, a small probe radius of 1.0 Å, and grid resolution of 0.5 Å, (f) Calculation reported in Ref. 71 using SwissPDBViewer with a probe radius of 1.4 Å. Figure An important feature of our algorithm is its compatibility with MD simulations, enabling the assessment of dynamic changes in volume over time. To illustrate this, we analyzed the MD trajectory of the [Pd4L6] 12+ , Cage 3, using VOIDOO software that employs the rolling probe algorithm and our C3 software. This comparison highlighted the advantages of the C3 angle-based algorithm over the rolling one-probe algorithm (Figure ). The calculation of the cavity volume with VOIDOO with a standard probe size of radius 1.4 Å exhibited significant variations in the calculated volume over time of ca. 30% (Vcavity = 307 ± 97 Å 3 ), primarily due to over-/underestimating the cavity volume in several frames, giving 0 values in some instances (see Figure blue line). While increasing the probe size (radius = 2.4 Å) mitigated this issue by preventing the probe from escaping from the cavity, it led to a much smaller cavity size with a ca. 60% variation over time (Vcavity = 57 ± 35 Å 3 , see Figure green line). In contrast, our C3 algorithm with default parameters provided a more robust and well-defined cavity with a volume variation over time of ca. 10% (Vcavity = 323 ± 31 Å 3 , see Figure orange line). These results highlight the robustness of the angle-base algorithm of C3 for analyzing MD trajectories. |
65c9f0bf9138d23161ecc7b7 | 19 | We showed that the C3 algorithm is efficient in calculating cavity volumes on cages with all types of shapes, cavity sizes, and window sizes. The angle-based algorithm of C3 is especially efficient with cages with large windows, where the rolling probe algorithm fails due to the probe escaping from the cavity. Once the cavity calculation is completed, various properties of the cavity are computed for a more comprehensive understanding of the cavity's characteristics and the interaction with potential guest molecules, thereby aiding in enhancing and designing novel hostguest complexes. These properties include aromatic contacts, solvent accessible surface area (SASA), hydrophobicity (MHP) and/or electrostatic potential (ESP) described below. |
65c9f0bf9138d23161ecc7b7 | 20 | The hydrophobicity of the cage cavity serves to identify favorable interactions with nonpolar guests in aqueous media. This is achieved by assigning hydrophobic contributions (Fi) to each atom in the cage, which was tabulated by Ghose and coworkers for various atom types based on their contributions to the 1-octanol/water partition coefficient. |
65c9f0bf9138d23161ecc7b7 | 21 | The commonly used distance functions are: The Hydrophobic Index (HI) is defined based on the distinction between negative MHP values (MHP -) associated with polar regions and positive MHP values (MHP + ) corresponding to hydrophobic regions, as shown in Eqn 5. 𝐻𝐼 = The calculated hydrophobic potential information is then stored as B-factor data for each cavity grid point alongside the original cage coordinates in a PDB format. This format enables users to visualize these values easily using standard visualization software such as Chimera, VMD, or PyMol (Figure ). |
65c9f0bf9138d23161ecc7b7 | 22 | To illustrate the use of C3 for calculating cavity properties, we computed the MHP for Cages 1 and 2. The average cavity hydrophobicity, 0.01 for Cage 1 and 0.09, for Cage 2, indicates that the cavity of Cage 2 is 9 times more hydrophobic than Cage 1 (Figure ). This illustrates that small cavities efficiently isolated by the cage walls are much more hydrophobic than large cages containing large windows. However, the algorithm is unsuitable for calculating the hydrophobicity of metallocages due to the lack of tabulated hydrophobic contributions for metals. |
65c9f0bf9138d23161ecc7b7 | 23 | Where k is the Coulomb constant, qi is a partial charge of a cage atom, and d(grid,i) is the distance between the cage atom and the cavity grid point. The partial charges are determined using the electronegativity equalization method (EEM) implemented in Open Babel, a widely accepted and efficient procedure for deriving charge-based descriptors in QSAR studies. The cavity ESP is a valuable tool for identifying favorable interactions between hosts and polar guests. For example, by computing the ESP for a [Pd2L4] 4+ cage and 1,4-dicyanobenzene as a potential guest, one can easily visualize the complementarity of their ESPs, suggesting the formation of a strongly bound host-guest complex (Figure ). Negatively charged cages are relatively less common than positively charged ones. Nevertheless, we present an example of a purely organic cage, containing carboxylic groups, which results in a cavity with a negative ESP. This feature suggests that the cage can potentially encapsulate and stabilize positively charged guest molecules (Figure ). |
65c9f0bf9138d23161ecc7b7 | 24 | In addition to the Python module and the command line interface, we have developed a graphical user interface (GUI) as a PyMol plugin that requires no programming skills. This GUI enables users to select a molecule and perform calculations with just a few clicks. To use it, the user simply needs to load the molecule in PyMol, open the C3 plugin, select the molecule from the drop-down list, and then press the "Calculate volume" button. Optionally, the user can adjust the grid size, select the properties to calculate (and adjust their parameters, such as the hydrophobicity method, the distance function, etc.), or choose a clustering algorithm to remove noisy cavity points, i.e. to remove isolated cavity points that do not belong to the main cavity. As an example, we provide the output obtained for the calculation of a [Pd2L4] 4+ cage providing in the same PyMol session the output obtained for the cavity, with an individual output for each selected property (Figure ). |
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