Literature DB >> 28318252

Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

Juan Pablo Arcon1, Lucas A Defelipe1, Carlos P Modenutti1, Elias D López1, Daniel Alvarez-Garcia2, Xavier Barril3,4, Adrián G Turjanski1, Marcelo A Martí1.   

Abstract

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

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Year:  2017        PMID: 28318252     DOI: 10.1021/acs.jcim.6b00678

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  11 in total

1.  AutoDock Bias: improving binding mode prediction and virtual screening using known protein-ligand interactions.

Authors:  Juan Pablo Arcon; Carlos P Modenutti; Demian Avendaño; Elias D Lopez; Lucas A Defelipe; Francesca Alessandra Ambrosio; Adrian G Turjanski; Stefano Forli; Marcelo A Marti
Journal:  Bioinformatics       Date:  2019-10-01       Impact factor: 6.937

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.  Application of Site-Identification by Ligand Competitive Saturation in Computer-Aided Drug Design.

Authors:  Himanshu Goel; Anthony Hazel; Wenbo Yu; Sunhwan Jo; Alexander D MacKerell
Journal:  New J Chem       Date:  2021-11-29       Impact factor: 3.591

4.  Impact of electronic polarizability on protein-functional group interactions.

Authors:  Himanshu Goel; Wenbo Yu; Vincent D Ustach; Asaminew H Aytenfisu; Delin Sun; Alexander D MacKerell
Journal:  Phys Chem Chem Phys       Date:  2020-04-06       Impact factor: 3.676

5.  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

6.  Computer simulation of the Receptor-Ligand Interactions of Mannose Receptor CD206 in Comparison with the Lectin Concanavalin A Model.

Authors:  Igor D Zlotnikov; Elena V Kudryashova
Journal:  Biochemistry (Mosc)       Date:  2022-01       Impact factor: 2.824

7.  Elucidating the Interactions of Fluoxetine with Human Transferrin Employing Spectroscopic, Calorimetric, and In Silico Approaches: Implications of a Potent Alzheimer's Drug.

Authors:  Mohd Shahnawaz Khan; Moyad Shahwan; Anas Shamsi; Fahad A Alhumaydhi; Suliman A Alsagaby; Waleed Al Abdulmonem; Bekhzod Abdullaev; Dharmendra Kumar Yadav
Journal:  ACS Omega       Date:  2022-03-02

8.  Cosolvent Sites-Based Discovery of Mycobacterium Tuberculosis Protein Kinase G Inhibitors.

Authors:  Osvaldo Burastero; Lucas A Defelipe; Gabriel Gola; Nancy L Tateosian; Elias D Lopez; Camila Belen Martinena; Juan Pablo Arcon; Martín Dodes Traian; Diana E Wetzler; Isabel Bento; Xavier Barril; Javier Ramirez; Marcelo A Marti; Maria M Garcia-Alai; Adrián G Turjanski
Journal:  J Med Chem       Date:  2022-06-23       Impact factor: 8.039

9.  Arylsulfonyl histamine derivatives as powerful and selective α-glucosidase inhibitors.

Authors:  M I Osella; M O Salazar; M D Gamarra; D M Moreno; F Lambertucci; D E Frances; R L E Furlan
Journal:  RSC Med Chem       Date:  2020-03-12

10.  Surface Probing by Fragment-Based Screening and Computational Methods Identifies Ligandable Pockets on the von Hippel-Lindau (VHL) E3 Ubiquitin Ligase.

Authors:  Xavier Lucas; Inge Van Molle; Alessio Ciulli
Journal:  J Med Chem       Date:  2018-08-08       Impact factor: 7.446

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