ArticleNucleic acids research2013
BioLiP: a semi-manually curated database for biologically relevant ligand-protein interactions.
Article in Nucleic acids research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 373 papers, 1 of them a synthesis that pooled it.
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Who cites it
373 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advances in the Application of Protein Language Modeling for Nucleic Acid Protein Binding Site Prediction.Genes · 2024Pooled it
- PrOMet: Accurate and Robust Metal-Binding Site and Type Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- NRB-FusePS: A Protein Language Model-Based Multimodal Framework for Predicting Ligand-Binding Residues in Nuclear Receptors.The protein journal · 2026Article
- PockLigGPT: Pocket-Sequence-Conditioned Molecular Generation with GPTs and RL.Journal of chemical information and modeling · 2026Article
- Protein-DNA Binding Sites Prediction via Integrating Pretrained Large Language Models and Contrastive Learning.Interdisciplinary sciences, computational life sciences · 2026Article
- Compositionally Biased Regions Within Structured Protein Domains.Biomolecules · 2026Article
- Deep Contrastive Learning for High-Throughput Prediction of Drug Resistance Mutations from Sequences.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- DeepPANB: integrating protein language model with PaiNN equivariant graph neural networks for prediction of protein-nucleic acid binding sites.Briefings in bioinformatics · 2026Article
- RGTBind: RBF-gate graph transformer with spatially biased attention for protein-DNA binding-site prediction.Journal of molecular modeling · 2026Article
- MotifLeadDB: A Hierarchical Structural Data Set for Congeneric Ligand Binding Activity Change.Journal of chemical information and modeling · 2026Article
- Sequence-based drug-target binding site pre-training enables cryptic pocket detection and improves binding affinity and kinetics prediction.Journal of cheminformatics · 2026Article
- Sequence-based Drug-Target Binding Site Pretraining Enables Cryptic Pocket Detection and Improves Binding Affinity and Kinetics Prediction.bioRxiv : the preprint server for biology · 2026Article
- Predicting protein-nucleic acid interactions via protein language models with biophysical and evolutionary priors.iScience · 2026Article
- Foundation models and deep learning for cancer drug response prediction: a framework for data, metrics, and validation.Briefings in bioinformatics · 2026Review
- Out-of-distribution generalization enhances protein function annotation for low-homology sequences.Briefings in bioinformatics · 2026Article
- SSAS-GO: structure-sequence adaptive synergy network for protein function prediction.Briefings in bioinformatics · 2026Article
- Benchmarking co-folding methods to predict the structures of covalent protein-ligand complexes.Acta pharmacologica Sinica · 2026Article
- Peptide-protein docking: from physics-based models to generative intelligence.Chemical communications (Cambridge, England) · 2026Review
- STAR-GO: improving protein function prediction by learning to hierarchically integrate ontology-informed semantic embeddings.Bioinformatics (Oxford, England) · 2026Article
- Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER.Nature biotechnology · 2026Article
313 more citing papers are in PubMed but not listed here.
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3 authors.
Funding
Abstract
BioLiP (http://zhanglab.ccmb.med.umich.edu/BioLiP/) is a semi-manually curated database for biologically relevant ligand-protein interactions. Establishing interactions between protein and biologically relevant ligands is an important step toward understanding the protein functions. Most ligand-binding sites prediction methods use the protein structures from the Protein Data Bank (PDB) as templates. However, not all ligands present in the PDB are biologically relevant, as small molecules are often used as additives for solving the protein structures. To facilitate template-based ligand-protein docking, virtual ligand screening and protein function annotations, we develop a hierarchical procedure for assessing the biological relevance of ligands present in the PDB structures, which involves a four-step biological feature filtering followed by careful manual verifications. This procedure is used for BioLiP construction. Each entry in BioLiP contains annotations on: ligand-binding residues, ligand-binding affinity, catalytic sites, Enzyme Commission numbers, Gene Ontology terms and cross-links to the other databases. In addition, to facilitate the use of BioLiP for function annotation of uncharacterized proteins, a new consensus-based algorithm COACH is developed to predict ligand-binding sites from protein sequence or using 3D structure. The BioLiP database is updated weekly and the current release contains 204 223 entries.
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