ArticleThe journal of physical chemistry letters2016
Benzene Probes in Molecular Dynamics Simulations Reveal Novel Binding Sites for Ligand Design.
Article in The journal of physical chemistry letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Computational Ligand-Binding Site Prediction.Advances in experimental medicine and biology · 2026Review
- A druggable conformational switch in the c-MYC transactivation domain.Nature communications · 2024Article
- Applications of Molecular Dynamics Simulations in Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Stitched peptides as potential cell permeable inhibitors of oncogenic DAXX protein.RSC chemical biology · 2023Article
- Decrypting Integrins by Mixed-Solvent Molecular Dynamics Simulations.Journal of chemical information and modeling · 2023Article
- A pH-dependent cluster of charges in a conserved cryptic pocket on flaviviral envelopes.eLife · 2023Article
- Success probability of high-affinity DNA aptamer generation by genetic alphabet expansion.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Shape Theory Applied to Molecular Docking and Automatic Localization of Ligand Binding Pockets in Large Proteins.ACS omega · 2022Article
- Uncovering cryptic pockets in the SARS-CoV-2 spike glycoprotein.Structure (London, England : 1993) · 2022Article
- Application of Site-Identification by Ligand Competitive Saturation in Computer-Aided Drug Design.New journal of chemistry = Nouveau journal de chimie · 2022Article
- Identification of Secondary Binding Sites on Protein Surfaces for Rational Elaboration of Synthetic Protein Mimics.ACS chemical biology · 2021Article
- Computational Design of Macrocyclic Binders of S100B(ββ): Novel Peptide Theranostics.Molecules (Basel, Switzerland) · 2021Article
- Macrocyclization of an all-d linear α-helical peptide imparts cellular permeability.Chemical science · 2020Article
- Inhibition of striatal-enriched protein tyrosine phosphatase by targeting computationally revealed cryptic pockets.European journal of medicinal chemistry · 2020Article
- Rigorous Computational and Experimental Investigations on MDM2/MDMX-Targeted Linear and Macrocyclic Peptides.Molecules (Basel, Switzerland) · 2019Article
- The Dual Interactions of p53 with MDM2 and p300: Implications for the Design of MDM2 Inhibitors.International journal of molecular sciences · 2019Article
- Stereoisomerism of stapled peptide inhibitors of the p53-Mdm2 interaction: an assessment of synthetic strategies and activity profiles.Chemical science · 2019Article
- Incorporation of Putative Helix-Breaking Amino Acids in the Design of Novel Stapled Peptides: Exploring Biophysical and Cellular Permeability Properties.Molecules (Basel, Switzerland) · 2019Article
- Roles of computational modelling in understanding p53 structure, biology, and its therapeutic targeting.Journal of molecular cell biology · 2019Review
- Stapled Peptides Inhibitors: A New Window for Target Drug Discovery.Computational and structural biotechnology journal · 2019Review
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Protein flexibility poses a major challenge in binding site identification. Several computational pocket detection methods that utilize small-molecule probes in molecular dynamics (MD) simulations have been developed to address this issue. Although they have proven hugely successful at reproducing experimental structural data, their ability to predict new binding sites that are yet to be identified and characterized has not been demonstrated. Here, we report the use of benzenes as probe molecules in ligand-mapping MD (LMMD) simulations to predict the existence of two novel binding sites on the surface of the oncoprotein MDM2. One of them was serendipitously confirmed by biophysical assays and X-ray crystallography to be important for the binding of a new family of hydrocarbon stapled peptides that were specifically designed to target the other putative site. These results highlight the predictive power of LMMD and suggest that predictions derived from LMMD simulations can serve as a reliable basis for the identification of novel ligand binding sites in structure-based drug design.
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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.