ArticlePLoS computational biology2014
eMatchSite: sequence order-independent structure alignments of ligand binding pockets in protein models.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Beyond sequence: Structure-based machine learning.Computational and structural biotechnology journal · 2023Review
- A unified approach to sequential and non-sequential structure alignment of proteins, RNAs, and DNAs.iScience · 2022Article
- Estimating the Similarity between Protein Pockets.International journal of molecular sciences · 2022Review
- Binding site matching in rational drug design: algorithms and applications.Briefings in bioinformatics · 2019Review
- Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases.Briefings in bioinformatics · 2019Review
- PatchSearch: a web server for off-target protein identification.Nucleic acids research · 2019Article
- 3D-PP: A Tool for Discovering Conserved Three-Dimensional Protein Patterns.International journal of molecular sciences · 2019Article
- Updates to Binding MOAD (Mother of All Databases): Polypharmacology Tools and Their Utility in Drug Repurposing.Journal of molecular biology · 2019Article
- DeepDrug3D: Classification of ligand-binding pockets in proteins with a convolutional neural network.PLoS computational biology · 2019Article
- eModel-BDB: a database of comparative structure models of drug-target interactions from the Binding Database.GigaScience · 2018Article
- eRepo-ORP: Exploring the Opportunity Space to Combat Orphan Diseases with Existing Drugs.Journal of molecular biology · 2018Article
- Comparative assessment of strategies to identify similar ligand-binding pockets in proteins.BMC bioinformatics · 2018Article
- Large-scale computational drug repositioning to find treatments for rare diseases.NPJ systems biology and applications · 2018Article
- Large-scale detection of drug off-targets: hypotheses for drug repurposing and understanding side-effects.BMC pharmacology & toxicology · 2017Article
- Local Alignment of Ligand Binding Sites in Proteins for Polypharmacology and Drug Repositioning.Methods in molecular biology (Clifton, N.J.) · 2017Article
- PatchSurfers: Two methods for local molecular property-based binding ligand prediction.Methods (San Diego, Calif.) · 2016Article
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1 author.
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Abstract
Detecting similarities between ligand binding sites in the absence of global homology between target proteins has been recognized as one of the critical components of modern drug discovery. Local binding site alignments can be constructed using sequence order-independent techniques, however, to achieve a high accuracy, many current algorithms for binding site comparison require high-quality experimental protein structures, preferably in the bound conformational state. This, in turn, complicates proteome scale applications, where only various quality structure models are available for the majority of gene products. To improve the state-of-the-art, we developed eMatchSite, a new method for constructing sequence order-independent alignments of ligand binding sites in protein models. Large-scale benchmarking calculations using adenine-binding pockets in crystal structures demonstrate that eMatchSite generates accurate alignments for almost three times more protein pairs than SOIPPA. More importantly, eMatchSite offers a high tolerance to structural distortions in ligand binding regions in protein models. For example, the percentage of correctly aligned pairs of adenine-binding sites in weakly homologous protein models is only 4-9% lower than those aligned using crystal structures. This represents a significant improvement over other algorithms, e.g. the performance of eMatchSite in recognizing similar binding sites is 6% and 13% higher than that of SiteEngine using high- and moderate-quality protein models, respectively. Constructing biologically correct alignments using predicted ligand binding sites in protein models opens up the possibility to investigate drug-protein interaction networks for complete proteomes with prospective systems-level applications in polypharmacology and rational drug repositioning. eMatchSite is freely available to the academic community as a web-server and a stand-alone software distribution at http://www.brylinski.org/ematchsite.
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