ArticleBiomolecules2022
CavitySpace: A Database of Potential Ligand Binding Sites in the Human Proteome.
Article in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- From CASP13 to the Nobel Prize: DeepMind's AlphaFold Journey in Revolutionizing Protein Structure Prediction and Beyond.Current protein & peptide science · 2026Review
- Computational Ligand-Binding Site Prediction.Advances in experimental medicine and biology · 2026Review
- The Human Omnibus of Targetable Pockets.Journal of cheminformatics · 2025Article
- From Concepts to Inhibitors: A Blueprint for Targeting Protein-Protein Interactions.Chemical reviews · 2025Review
- Bile acids target an exposed cavity in the glucocorticoid receptor modulating receptor self-assembly, chromatin binding and transcriptional activity.bioRxiv : the preprint server for biology · 2025Article
- MAI-TargetFisher: A proteome-wide drug target prediction method synergetically enhanced by artificial intelligence and physical modeling.Acta pharmacologica Sinica · 2025Article
- Natural Language Processing Methods for the Study of Protein-Ligand Interactions.Journal of chemical information and modeling · 2025Review
- Computation suggests that the cell adhesion sub-proteome is enriched for sites of pH-dependence and charge burial.PloS one · 2025Article
- Databases of ligand-binding pockets and protein-ligand interactions.Computational and structural biotechnology journal · 2024Review
- GPCR-BSD: a database of binding sites of human G-protein coupled receptors under diverse states.BMC bioinformatics · 2024Article
- Article
- Autophagy3D: a comprehensive autophagy structure database.Database : the journal of biological databases and curation · 2024Article
- Comprehensive detection and characterization of human druggable pockets through binding site descriptors.Nature communications · 2024Article
- DiPPI: A Curated Data Set for Drug-like Molecules in Protein-Protein Interfaces.Journal of chemical information and modeling · 2024Article
- AlphaFold2 structures guide prospective ligand discovery.Science (New York, N.Y.) · 2024Article
- Artificial Intelligence in Drug Discovery: A Bibliometric Analysis and Literature Review.Mini reviews in medicinal chemistry · 2024Review
- Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-Based Featurization Method.Journal of chemical information and modeling · 2023Article
- CaviDB: a database of cavities and their features in the structural and conformational space of proteins.Database : the journal of biological databases and curation · 2023Article
- AlphaFold2 and its applications in the fields of biology and medicine.Signal transduction and targeted therapy · 2023Review
- HProteome-BSite: predicted binding sites and ligands in human 3D proteome.Nucleic acids research · 2023Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Location and properties of ligand binding sites provide important information to uncover protein functions and to direct structure-based drug design approaches. However, as binding site detection depends 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. Here, we constructed the CavitySpace database, the first pocket library for all the proteins in the human proteome, using a widely-applied ligand binding site detection program CAVITY. Our analysis showed that known ligand binding sites could be well recovered. We grouped the predicted binding sites according to their similarity which can be used in protein function prediction and drug repurposing studies. Novel binding sites in highly reliable predicted structure regions provide new opportunities for drug discovery. Our CavitySpace is freely available and provides a valuable tool for drug discovery and protein function studies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.