title: Toward quantitative estimates of binding affinities for protein-ligand systems involving large inhibitor compounds: a steered molecular dynamics simulation route.
abstract: 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.
authors.affiliation: Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Campus Nord B4-B5, E-08034 Barcelona, Spain.
authors.forename: Paolo
authors.initials: P
authors.lastname: Nicolini
authors.forename: Diego
authors.initials: D
authors.lastname: Frezzato
authors.forename: Cristina
authors.initials: C
authors.lastname: Gellini
authors.forename: Marco
authors.initials: M
authors.lastname: Bizzarri
authors.forename: Riccardo
authors.initials: R
authors.lastname: Chelli
mesh_terms: D000970:Antineoplastic Agents / Q000737:chemistry* / Q000494:pharmacology; D001665:Binding Sites / Q000187:drug effects; D004791:Enzyme Inhibitors / Q000737:chemistry* / Q000494:pharmacology; D051416:Focal Adhesion Protein-Tyrosine Kinases / Q000037:antagonists & inhibitors / Q000737:chemistry*; D008024:Ligands; D056004:Molecular Dynamics Simulation; D011743:Pyrimidines / Q000737:chemistry* / Q000494:pharmacology; D011758:Pyrroles / Q000737:chemistry* / Q000494:pharmacology; D013329:Structure-Activity Relationship
chemical_list: D000970:Antineoplastic Agents; D004791:Enzyme Inhibitors; D008024:Ligands; D011743:Pyrimidines; D011758:Pyrroles; C527741:pyrrolopyrimidine; D051416:Focal Adhesion Protein-Tyrosine Kinases