ArticlePLoS computational biology2009
FINDSITE: a threading-based approach to ligand homology modeling.
Article in PLoS computational biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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Who cites it
50 citing papers in PubMed.
- Protein Structure Prediction Methods.Advances in experimental medicine and biology · 2026Review
- Comparative evaluation of methods for the prediction of protein-ligand binding sites.Journal of cheminformatics · 2024Article
- Utility of the Morgan Fingerprint in Structure-Based Virtual Ligand Screening.The journal of physical chemistry. B · 2024Article
- FRAGSITE2: A structure and fragment-based approach for virtual ligand screening.Protein science : a publication of the Protein Society · 2024Article
- Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein-Protein Interactions.The journal of physical chemistry. B · 2022Article
- FRAGSITE: A Fragment-Based Approach for Virtual Ligand Screening.Journal of chemical information and modeling · 2021Article
- ClusPro LigTBM: Automated Template-based Small Molecule Docking.Journal of molecular biology · 2020Article
- Binding site matching in rational drug design: algorithms and applications.Briefings in bioinformatics · 2019Review
- FINDSITEJournal of chemical information and modeling · 2018Article
- eModel-BDB: a database of comparative structure models of drug-target interactions from the Binding Database.GigaScience · 2018Article
- Comparative assessment of strategies to identify similar ligand-binding pockets in proteins.BMC bioinformatics · 2018Article
- Article
- Pocket detection and interaction-weighted ligand-similarity search yields novel high-affinity binders for Myocilin-OLF, a protein implicated in glaucoma.Bioorganic & medicinal chemistry letters · 2017Article
- Systems-level understanding of ethanol-induced stresses and adaptation in E. coli.Scientific reports · 2017Article
- Discovery of Nicotinamide Adenine Dinucleotide Binding Proteins in the Escherichia coli Proteome Using a Combined Energetic- and Structural-Bioinformatics-Based Approach.Journal of proteome research · 2017Article
- Discovery of Mycobacterium tuberculosis InhA Inhibitors by Binding Sites Comparison and Ligands Prediction.Journal of medicinal chemistry · 2016Article
- HOMCOS: an updated server to search and model complex 3D structures.Journal of structural and functional genomics · 2016Article
- Protein ligand-specific binding residue predictions by an ensemble classifier.BMC bioinformatics · 2016Article
- Assessing the similarity of ligand binding conformations with the Contact Mode Score.Computational biology and chemistry · 2016Article
- Automatic generation of bioinformatics tools for predicting protein-ligand binding sites.Bioinformatics (Oxford, England) · 2016Article
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2 authors.
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Abstract
Ligand virtual screening is a widely used tool to assist in new pharmaceutical discovery. In practice, virtual screening approaches have a number of limitations, and the development of new methodologies is required. Previously, we showed that remotely related proteins identified by threading often share a common binding site occupied by chemically similar ligands. Here, we demonstrate that across an evolutionarily related, but distant family of proteins, the ligands that bind to the common binding site contain a set of strongly conserved anchor functional groups as well as a variable region that accounts for their binding specificity. Furthermore, the sequence and structure conservation of residues contacting the anchor functional groups is significantly higher than those contacting ligand variable regions. Exploiting these insights, we developed FINDSITE(LHM) that employs structural information extracted from weakly related proteins to perform rapid ligand docking by homology modeling. In large scale benchmarking, using the predicted anchor-binding mode and the crystal structure of the receptor, FINDSITE(LHM) outperforms classical docking approaches with an average ligand RMSD from native of approximately 2.5 A. For weakly homologous receptor protein models, using FINDSITE(LHM), the fraction of recovered binding residues and specific contacts is 0.66 (0.55) and 0.49 (0.38) for highly confident (all) targets, respectively. Finally, in virtual screening for HIV-1 protease inhibitors, using similarity to the ligand anchor region yields significantly improved enrichment factors. Thus, the rather accurate, computationally inexpensive FINDSITE(LHM) algorithm should be a useful approach to assist in the discovery of novel biopharmaceuticals.
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