ArticleThe journal of physical chemistry. B2016
Moving Beyond Active-Site Detection: MixMD Applied to Allosteric Systems.
Article in The journal of physical chemistry. B, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed, 106 citations in OpenAlex.
- Uncovering hidden druggable sites: computational approaches to allosteric and cryptic pocket discovery-from molecular dynamics to AI.Journal of computer-aided molecular design · 2026Review
- The influence of ligands on AlphaFold3 prediction of cryptic pockets.Communications biology · 2026Article
- Mixed-Solvent MD suite: modular tools for building and analyzing mixed-solvent molecular dynamics systems.Journal of computer-aided molecular design · 2026Article
- Computational Ligand-Binding Site Prediction.Advances in experimental medicine and biology · 2026Review
- Computational approaches to druggable site identification: Current status and future perspective.Acta pharmaceutica Sinica. B · 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
- 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
- Predicting multiple conformations of ligand binding sites in proteins suggests that AlphaFold2 may remember too much.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Exploration of Cryptic Pockets Using Enhanced Sampling Along Normal Modes: A Case Study of KRASJournal of chemical information and modeling · 2024Article
- Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots.Journal of chemical information and modeling · 2024Article
- Article
- Exploring Aromatic Cage Flexibility Using Cosolvent Molecular Dynamics Simulations─An In-Silico Case Study of Tudor Domains.Journal of chemical information and modeling · 2024Article
- Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART).Journal of cheminformatics · 2024Article
- In Silico Exploration of the Trypanothione Reductase (TryR) ofInternational journal of molecular sciences · 2023Article
- Application of Mixed-Solvent Molecular Dynamics Simulations for Prediction of Allosteric Sites on G Protein-Coupled Receptors.Molecular pharmacology · 2023Article
- Is the Stalk of the SARS-CoV-2 Spike Protein Druggable?Viruses · 2022Article
- Discovery of the Cryptic Sites of SARS-CoV-2 Papain-like Protease and Analysis of Its Druggability.International journal of molecular sciences · 2022Article
- Mapping the binding sites of challenging drug targets.Current opinion in structural biology · 2022Review
- FTMove: A Web Server for Detection and Analysis of Cryptic and Allosteric Binding Sites by Mapping Multiple Protein Structures.Journal of molecular biology · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Mixed-solvent molecular dynamics (MixMD) is a hotspot-mapping technique that relies on molecular dynamics simulations of proteins in binary solvent mixtures. Previous work on MixMD has established the technique's effectiveness in capturing binding sites of small organic compounds. In this work, we show that MixMD can identify both competitive and allosteric sites on proteins. The MixMD approach embraces full protein flexibility and allows competition between solvent probes and water. Sites preferentially mapped by probe molecules are more likely to be binding hotspots. There are two important requirements for the identification of ligand-binding hotspots: (1) hotspots must be mapped at very high signal-to-noise ratio and (2) the hotspots must be mapped by multiple probe types. We have developed our mapping protocol around acetonitrile, isopropanol, and pyrimidine as probe solvents because they allowed us to capture hydrophilic, hydrophobic, hydrogen-bonding, and aromatic interactions. Charged probes were needed for mapping one target, and we introduce them in this work. In order to demonstrate the robust nature and wide applicability of the technique, a combined total of 5 μs of MixMD was applied across several protein targets known to exhibit allosteric modulation. Most notably, all the protein crystal structures used to initiate our simulations had no allosteric ligands bound, so there was no preorganization of the sites to predispose the simulations to find the allosteric hotspots. The protein test cases were ABL Kinase, Androgen Receptor, CHK1 Kinase, Glucokinase, PDK1 Kinase, Farnesyl Pyrophosphate Synthase, and Protein-Tyrosine Phosphatase 1B. The success of the technique is demonstrated by the fact that the top-four sites solely map the competitive and allosteric sites. Lower-ranked sites consistently map other biologically relevant sites, multimerization interfaces, or crystal-packing interfaces. Lastly, we highlight the importance of including protein flexibility by demonstrating that MixMD can map allosteric sites that are not detected in half the systems using FTMap applied to the same crystal structures.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.