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CavitySpace: A database of potential ligand binding sites in the human proteome
Open accessPreprint — published as 10.3390/biom12070967 · Paper page
Abstract
The ligand binding sites of a protein provide useful information to uncover its functions and to direct the structure-based drug design. However, as binding site detection relies on the three-dimensional (3D) structural data of proteins, functional analysis based on protein ligand binding sites is formidable for proteins without structural information. Recent developments in protein structure prediction and the 3D structures built by AlphaFold provide an unprecedented opportunity for analyzing ligand binding sites in human proteins. We have used the reliable ligand binding site detection program CAVITY to analyse all the proteins in the human proteome and constructed the CavitySpace database, which is the first pocket library for predicted protein structures. CavitySpace can be used to predict protein function based on pocket information, to identify new druggable protein targets for drug design, and to search for new binding sites for known drugs for drug repurposing. CavitySpace is freely available at http://www.pkumdl.cn:8000/cavityspace/ .
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Highly accurate protein structure prediction with AlphaFold
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Metadata
- Authors
- Wang, S., Lin, H., Huang, Z., He, Y., Deng, X., Xu, Y., Pei, J., & Lai, L.
- Affiliations
- Peking University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Corresponding author
- Pei, Jianfeng
- Lai, Luhua
- Venue
- Biomolecules
- Publisher
- openRxiv
- Published
- 2022-01-27
- Volume
- 12
- Issue
- 7
- Pages
- 967-967
- ISSN
- 2218-273X (ISSN-L)
- PMC
- PMC9312471
- OpenAlex
- W4285020367
- Cited by
- 39
- References
- 1
- Citations by year
- 2026: 3 · 2025: 10 · 2024: 13 · 2023: 8 · 2022: 5
- FWCI
- 5.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Biomolecules (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Natural Science Foundation of China (22033001, 21673010, 2016YFA0502303, 2021-I2M-5-014)
- Chinese Academy of Medical Sciences (2021‐ I2M‐5‐014, 22033001)
- Peking University (2016YFA0502303)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Keywords
- ligand binding sites, human proteome, protein binding site prediction, cavities, AlphaFold, protein structure prediction, protein function prediction, drug repurposing, structure-based drug design
- MeSH terms
- Binding Sites, Humans, Ligands, Protein Binding, Proteome, Biophysical Phenomena
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