PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery
Abstract Prediction of protein-protein binding (PPB) affinity plays an important role in large-molecular drug discovery. Deep learning (DL) has been adopted to predict the changes of PPB binding affinities upon mutations, but there was a scarcity of studies predicting the PPB affinity itself. The ma...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-03997-4 |
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| author | Huaqing Liu Peiyi Chen Xiaochen Zhai Ku-Geng Huo Shuxian Zhou Lanqing Han Guoxin Fan |
| author_facet | Huaqing Liu Peiyi Chen Xiaochen Zhai Ku-Geng Huo Shuxian Zhou Lanqing Han Guoxin Fan |
| author_sort | Huaqing Liu |
| collection | DOAJ |
| description | Abstract Prediction of protein-protein binding (PPB) affinity plays an important role in large-molecular drug discovery. Deep learning (DL) has been adopted to predict the changes of PPB binding affinities upon mutations, but there was a scarcity of studies predicting the PPB affinity itself. The major reason is the paucity of open-source dataset with PPB affinity data. To address this gap, the current study introduced a large comprehensive PPB affinity (PPB-Affinity) dataset. The PPB-Affinity dataset contains key information such as crystal structures of protein-protein complexes (with or without protein mutation patterns), PPB affinity, receptor protein chain, ligand protein chain, etc. To the best of our knowledge, this is the largest publicly available PPB affinity dataset, and we believe it will significantly advance drug discovery by streamlining the screening of potential large-molecule drugs. We also developed a deep-learning benchmark model with this dataset to predict the PPB affinity, providing a foundational comparison for the research community. |
| format | Article |
| id | doaj-art-84b520fde9814b32a761fda2a63cf8db |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-84b520fde9814b32a761fda2a63cf8db2024-12-08T12:17:56ZengNature PortfolioScientific Data2052-44632024-12-0111111110.1038/s41597-024-03997-4PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discoveryHuaqing Liu0Peiyi Chen1Xiaochen Zhai2Ku-Geng Huo3Shuxian Zhou4Lanqing Han5Guoxin Fan6Artificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River DeltaArtificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River DeltaCyagen Biosciences (Suzhou) Inc.Cyagen Biosciences (Guangzhou) Inc.Artificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River DeltaArtificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River DeltaDepartment of Pain Medicine, Shenzhen Nanshan People’s Hospital, Shenzhen University Medical SchoolAbstract Prediction of protein-protein binding (PPB) affinity plays an important role in large-molecular drug discovery. Deep learning (DL) has been adopted to predict the changes of PPB binding affinities upon mutations, but there was a scarcity of studies predicting the PPB affinity itself. The major reason is the paucity of open-source dataset with PPB affinity data. To address this gap, the current study introduced a large comprehensive PPB affinity (PPB-Affinity) dataset. The PPB-Affinity dataset contains key information such as crystal structures of protein-protein complexes (with or without protein mutation patterns), PPB affinity, receptor protein chain, ligand protein chain, etc. To the best of our knowledge, this is the largest publicly available PPB affinity dataset, and we believe it will significantly advance drug discovery by streamlining the screening of potential large-molecule drugs. We also developed a deep-learning benchmark model with this dataset to predict the PPB affinity, providing a foundational comparison for the research community.https://doi.org/10.1038/s41597-024-03997-4 |
| spellingShingle | Huaqing Liu Peiyi Chen Xiaochen Zhai Ku-Geng Huo Shuxian Zhou Lanqing Han Guoxin Fan PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery Scientific Data |
| title | PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery |
| title_full | PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery |
| title_fullStr | PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery |
| title_full_unstemmed | PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery |
| title_short | PPB-Affinity: Protein-Protein Binding Affinity dataset for AI-based protein drug discovery |
| title_sort | ppb affinity protein protein binding affinity dataset for ai based protein drug discovery |
| url | https://doi.org/10.1038/s41597-024-03997-4 |
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