ArticleJournal of chemical information and modeling2021
Identification of Cryptic Binding Sites Using MixMD with Standard and Accelerated Molecular Dynamics.
Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Mixed-Solvent MD suite: modular tools for building and analyzing mixed-solvent molecular dynamics systems.Journal of computer-aided molecular design · 2026Article
- FMOPhore for hotspot identification and efficient fragment-to-lead growth strategies.Nature communications · 2026Article
- Exploring the Structural Basis of Cryptic Pocket Formation Driven by Extensive Protein Conformational Changes in Drug Targets.Journal of chemical theory and computation · 2026Article
- Computational approaches to druggable site identification: Current status and future perspective.Acta pharmaceutica Sinica. B · 2026Review
- Unlocking the undruggable spliceosome: generative AI and structural dynamics in cancer therapy.Frontiers in cell and developmental biology · 2026Review
- Computational Ligand-Binding Site Prediction.Advances in experimental medicine and biology · 2026Review
- Chasing allosteric inhibition of the SARS-CoV-2 PLpro via molecular dynamics simulations with flooding fragments (MDFFr).Journal of computer-aided molecular design · 2025Article
- Boosting Drug Discovery: Expanding the Applicability of Fragment Dissolved Molecular Dynamics to Accelerate Binding Mode Elucidation.Journal of chemical information and modeling · 2025Article
- Targeting protein disorder: the next hurdle in drug discovery.Nature reviews. Drug discovery · 2025Review
- Discovering Uncharted Binding Pockets on E3 Ligases Leads to the Identification of FBW7 Allosteric Modulators.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- E-FTMap: A Protein Structure Based Pharmacophore Identification Server for Guiding Fragment Expansion.Journal of molecular biology · 2025Article
- CrypToth: Cryptic Pocket Detection through Mixed-Solvent Molecular Dynamics Simulations-Based Topological Data Analysis.Journal of chemical information and modeling · 2025Article
- CrypTothML: An Integrated Mixed-Solvent Molecular Dynamics Simulation and Machine Learning Approach for Cryptic Site Prediction.International journal of molecular sciences · 2025Article
- Exploring Binding Sites in Chagas Disease Protein TcP21 Using Integrated Mixed Solvent Molecular Dynamics Approaches.Journal of chemical information and modeling · 2025Article
- Recent computational advances in the identification of cryptic binding sites for drug discovery.Bioinformatics advances · 2025Review
- Revisiting theNPJ drug discovery · 2025Article
- CryptoBench: cryptic protein-ligand binding sites dataset and benchmark.Bioinformatics (Oxford, England) · 2024Article
- Global hinge sites of proteins as target sites for drug binding.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Which cryptic sites are feasible drug targets?Drug discovery today · 2024Review
- Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots.Journal of chemical information and modeling · 2024Article
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2 authors.
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Abstract
Protein dynamics play an important role in small molecule binding and can pose a significant challenge in the identification of potential binding sites. Cryptic binding sites have been defined as sites which require significant rearrangement of the protein structure to become physically accessible to a ligand. Mixed-solvent MD (MixMD) is a computational protocol which maps the surface of the protein using molecular dynamics (MD) of the unbound protein solvated in a 5% box of probe molecules with explicit water. This method has successfully identified known active and allosteric sites which did not require reorganization. In this study, we apply the MixMD protocol to identify known cryptic sites of 12 proteins characterized by a wide range of conformational changes. Of these 12 proteins, three require reorganization of side chains, five require loop movements, and four require movement of more significant structures such as whole helices. In five cases, we find that standard MixMD simulations are able to map the cryptic binding sites with at least one probe type. In two cases (guanylate kinase and TIE-2), accelerated MD, which increases sampling of torsional angles, was necessary to achieve mapping of portions of the cryptic binding site missed by standard MixMD. For more complex systems where movement of a helix or domain is necessary, MixMD was unable to map the binding site even with accelerated dynamics, possibly due to the limited timescale (100 ns for individual simulations). In general, similar conformational dynamics are observed in water-only simulations and those with probe molecules. This could imply that the probes are not driving opening events but rather take advantage of mapping sites that spontaneously open as part of their inherent conformational behavior. Finally, we show that docking to an ensemble of conformations from the standard MixMD simulations performs better than docking the apo crystal structure in nine cases and even better than half of the bound crystal structures. Poorer performance was seen in docking to ensembles of conformations from the accelerated MixMD simulations.
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