Literature DB >> 25275946

Molecular simulations with solvent competition quantify water displaceability and provide accurate interaction maps of protein binding sites.

Daniel Alvarez-Garcia1, Xavier Barril.   

Abstract

Binding sites present well-defined interaction patterns that putative ligands must meet. Knowing them is essential to guide structure-based drug discovery projects. However, complex aspects of molecular recognition-such as protein flexibility or the effect of aqueous solvation-hinder accurate predictions. This is particularly true for polar contacts, which are heavily influenced by the local environment and the behavior of discrete water molecules. Here we present and validate MDmix (Molecular Dynamics simulations with mixed solvents) as a method that provides much more accurate interaction maps than ordinary potentials (e.g., GRID). Additionally, MDmix also affords water displaceability predictions, with advantages over methods that use pure water as solvent (e.g., inhomogeneous fluid solvation theory). With current MD software and hardware solutions, predictions can be obtained in a matter of hours and visualized in a very intuitive manner. Thus, MDmix is an ideal complement in everyday structure-based drug discovery projects.

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Year:  2014        PMID: 25275946     DOI: 10.1021/jm5010418

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  27 in total

1.  Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR.

Authors:  Yvonne Westermaier; Sergio Ruiz-Carmona; Isabelle Theret; Françoise Perron-Sierra; Guillaume Poissonnet; Catherine Dacquet; Jean A Boutin; Pierre Ducrot; Xavier Barril
Journal:  J Comput Aided Mol Des       Date:  2017-07-15       Impact factor: 3.686

2.  Biased Docking for Protein-Ligand Pose Prediction.

Authors:  Juan Pablo Arcon; Adrián G Turjanski; Marcelo A Martí; Stefano Forli
Journal:  Methods Mol Biol       Date:  2021

3.  Dynamic undocking and the quasi-bound state as tools for drug discovery.

Authors:  Sergio Ruiz-Carmona; Peter Schmidtke; F Javier Luque; Lisa Baker; Natalia Matassova; Ben Davis; Stephen Roughley; James Murray; Rod Hubbard; Xavier Barril
Journal:  Nat Chem       Date:  2016-11-14       Impact factor: 24.427

4.  Docking-undocking combination applied to the D3R Grand Challenge 2015.

Authors:  Sergio Ruiz-Carmona; Xavier Barril
Journal:  J Comput Aided Mol Des       Date:  2016-10-05       Impact factor: 3.686

Review 5.  Computational functional group mapping for drug discovery.

Authors:  Olgun Guvench
Journal:  Drug Discov Today       Date:  2016-07-05       Impact factor: 7.851

Review 6.  Driving Structure-Based Drug Discovery through Cosolvent Molecular Dynamics.

Authors:  Phani Ghanakota; Heather A Carlson
Journal:  J Med Chem       Date:  2016-08-17       Impact factor: 7.446

7.  Predicting Displaceable Water Sites Using Mixed-Solvent Molecular Dynamics.

Authors:  Sarah E Graham; Richard D Smith; Heather A Carlson
Journal:  J Chem Inf Model       Date:  2018-01-16       Impact factor: 4.956

8.  Identifying binding hot spots on protein surfaces by mixed-solvent molecular dynamics: HIV-1 protease as a test case.

Authors:  Peter M U Ung; Phani Ghanakota; Sarah E Graham; Katrina W Lexa; Heather A Carlson
Journal:  Biopolymers       Date:  2016-01       Impact factor: 2.505

9.  Application of the quantum mechanical IEF/PCM-MST hydrophobic descriptors to selectivity in ligand binding.

Authors:  Tiziana Ginex; Jordi Muñoz-Muriedas; Enric Herrero; Enric Gibert; Pietro Cozzini; F Javier Luque
Journal:  J Mol Model       Date:  2016-05-17       Impact factor: 1.810

10.  Identification of Cryptic Binding Sites Using MixMD with Standard and Accelerated Molecular Dynamics.

Authors:  Richard D Smith; Heather A Carlson
Journal:  J Chem Inf Model       Date:  2021-02-18       Impact factor: 4.956

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