ArticleJournal of chemical theory and computation2015
Identification of protein-ligand binding sites by the level-set variational implicit-solvent approach.
Article in Journal of chemical theory and computation, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Article
- Assessing the ligand native-like pose using a quantum mechanical-derived hydropathic score for protein-ligand complementarity.npj drug discovery · 2026Article
- In Silico Analysis of CMolecules (Basel, Switzerland) · 2025Article
- Use of High Pressure NMR Spectroscopy to Rapidly Identify Proteins with Internal Ligand-Binding Voids.bioRxiv : the preprint server for biology · 2025Article
- Implicit Solvent Models and Their Applications in Biophysics.Biomolecules · 2025Review
- Identification of druggable binding sites and small molecules as modulators of TMC1.Communications biology · 2025Article
- Methoxy group: a non-lipophilic "scout" for protein pocket finding.Future medicinal chemistry · 2025Article
- Importance of Computer-aided Drug Design in Modern Pharmaceutical Research.Current drug discovery technologies · 2025Review
- Phytoconstituents of Withania somnifera (L.) Dunal (Ashwagandha) unveiled potential cerebroside sulfotransferase inhibitors: insight through virtual screening, molecular dynamics, toxicity, and reverse pharmacophore analysis.Journal of biological engineering · 2024Article
- Article
- Article
- Computational workflow for discovering small molecular binders for shallow binding sites by integrating molecular dynamics simulation, pharmacophore modeling, and machine learning: STAT3 as case study.Journal of computer-aided molecular design · 2023Article
- It's ok to be outnumbered - sub-stoichiometric modulation of homomeric protein complexes.RSC medicinal chemistry · 2023Review
- Druggable Pockets at the RNA Interface Region of Influenza A Virus NS1 Protein Are Conserved across Sequence Variants from Distinct Subtypes.Biomolecules · 2022Article
- AP-2δ Is the Most Relevant Target of AP-2 Family-Focused Cancer Therapy and Affects Genome Organization.Cells · 2022Article
- Identification of Drug Combination Therapies for SARS-CoV-2: A Molecular Dynamics Simulations Approach.Drug design, development and therapy · 2022Article
- Targeting the Achilles Heel of FtsZ: The Interdomain Cleft.Frontiers in microbiology · 2021Review
- Modeling Epac1 interactions with the allosteric inhibitor AM-001 by co-solvent molecular dynamics.Journal of computer-aided molecular design · 2020Article
- Validation strategies for target prediction methods.Briefings in bioinformatics · 2020Review
- The design and development of covalent protein-protein interaction inhibitors for cancer treatment.Journal of hematology & oncology · 2020Review
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Authors and funding
6 authors.
Funding
Abstract
Protein–ligand binding is a key biological process at the molecular level. The identification and characterization of small-molecule binding sites on therapeutically relevant proteins have tremendous implications for target evaluation and rational drug design. In this work, we used the recently developed level-set variational implicit-solvent model (VISM) with the Coulomb field approximation (CFA) to locate and characterize potential protein–small-molecule binding sites. We applied our method to a data set of 515 protein–ligand complexes and found that 96.9% of the cocrystallized ligands bind to the VISM-CFA-identified pockets and that 71.8% of the identified pockets are occupied by cocrystallized ligands. For 228 tight-binding protein–ligand complexes (i.e, complexes with experimental pKd values larger than 6), 99.1% of the cocrystallized ligands are in the VISM-CFA-identified pockets. In addition, it was found that the ligand binding orientations are consistent with the hydrophilic and hydrophobic descriptions provided by VISM. Quantitative characterization of binding pockets with topological and physicochemical parameters was used to assess the “ligandability” of the pockets. The results illustrate the key interactions between ligands and receptors and can be very informative for rational drug design.
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