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license: mit |
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# Description |
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Structure Similarity Prediction predicts the (aligned) Local Distance Difference Test (LDDT) of the structures given an unaligned pair of proteins. Target values are computed after alignment with TM-align for all pairs of 1000 randomly sampled single-chain proteins. |
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# Splits |
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**Structure type:** PDB |
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The dataset is from [**ProteinShake Building datasets and benchmarks for deep learning on protein structures**](https://papers.nips.cc/paper_files/paper/2023/file/b6167294ed3d6fc61e11e1592ce5cb77-Paper-Datasets_and_Benchmarks.pdf). We use the splits based on 70% structure similarity, with the number of training, validation and test set shown below: |
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- Train: 300699 |
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- Valid: 4559 |
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- Test: 4850 |
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# Data format |
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We organize all data in LMDB format. The architecture of the databse is like: |
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**length:** The number of samples |
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**0:** |
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- **name_1:** The PDB ID of the protein 1 |
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- **name_2:** The PDB ID of the protein 2 |
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- **chain_1:** The chain ID of the protein 1 |
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- **chain_2:** The chain ID of the protein 2 |
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- **seq_1:** The structure-aware sequence 1 |
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- **seq_2:** The structure-aware sequence 2 |
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- **label:** Similarity value of the pair of proteins |
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**1:** |
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**···** |
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