Toward quantitative estimates of binding affinities for protein-ligand systems involving large inhibitor compounds a steered molecular dynamics simulation route

Toward quantitative estimates of binding affinities for protein-ligand systems involving large inhibitor compounds : a steered molecular dynamics simulation route

Copyright © 2013 Wiley Periodicals, Inc.

Bibliographische Detailangaben
Veröffentlicht in:Journal of computational chemistry. - 1984. - 34(2013), 18 vom: 05. Juli, Seite 1561-76
1. Verfasser: Nicolini, Paolo (VerfasserIn)
Weitere Verfasser: Frezzato, Diego, Gellini, Cristina, Bizzarri, Marco, Chelli, Riccardo
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2013
Zugriff auf das übergeordnete Werk:Journal of computational chemistry
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Antineoplastic Agents Enzyme Inhibitors Ligands Pyrimidines Pyrroles pyrrolopyrimidine Focal Adhesion Protein-Tyrosine Kinases EC 2.7.10.2
Beschreibung
Zusammenfassung:Copyright © 2013 Wiley Periodicals, Inc.
Understanding binding mechanisms between enzymes and potential inhibitors and quantifying protein-ligand affinities in terms of binding free energy is of primary importance in drug design studies. In this respect, several approaches based on molecular dynamics simulations, often combined with docking techniques, have been exploited to investigate the physicochemical properties of complexes of pharmaceutical interest. Even if the geometric properties of a modeled protein-ligand complex can be well predicted by computational methods, it is still challenging to rank with chemical accuracy a series of ligand analogues in a consistent way. In this article, we face this issue calculating relative binding free energies of a focal adhesion kinase, an important target for the development of anticancer drugs, with pyrrolopyrimidine-based ligands having different inhibitory power. To this aim, we employ steered molecular dynamics simulations combined with nonequilibrium work theorems for free energy calculations. This technique proves very powerful when a series of ligand analogues is considered, allowing one to tackle estimation of protein-ligand relative binding free energies in a reasonable time. In our cases, the calculated binding affinities are comparable with those recovered from experiments by exploiting the Michaelis-Menten mechanism with a competitive inhibitor
Beschreibung:Date Completed 19.09.2014
Date Revised 23.02.2022
published: Print-Electronic
Citation Status MEDLINE
ISSN:1096-987X
DOI:10.1002/jcc.23286