In Silico Reoptimization of Binding Affinity and Drug-Resistance Circumvention Ability in Kinase Inhibitors: A Case Study with RL-45 and Src Kinase.

Abstract

A major bottleneck in the development of kinase inhibitors has been the onset of drug resistance around the gatekeeper residues of Src kinase. Although recent times have seen the reports of certain second-generation kinase inhibitors which are capable of bypassing the drug resistance by circumventing kinase mutation, their kinase-binding efficacy has remained considerably weaker than that of the classical adenosine 5'-triphosphate-competitive kinase inhibitors. Using a recently synthesized second-generation kinase inhibitor RL-45 as a template, the current work integrates fragment-based drug discovery and quantitative structure-activity relationship study with enhanced molecular dynamics simulation approaches, namely, metadynamics and replica exchange free-energy perturbation, and demonstrates how one can optimally redesign and assess novel Src kinase inhibitors, by minimal introduction of new functional moieties around template kinase inhibitor. Interestingly, unlike many synthetic kinase inhibitors, these in silico optimized small-molecule derivatives of RL-45 are found to be potentially capable of serving dual purposes, crucial for efficacy of an ideal kinase inhibitor: (a) circumventing gatekeeper residue mutation-related drug resistance in Src kinase, unlike many commercial kinase inhibitors and (b) manifesting superior resilience against unbinding from the kinase active site. The computer simulation, boosted by enhanced sampling techniques, further reveals that these designed inhibitors bring about key interactions in the form of significantly long-standing hydrogen bonds and hydrophobic pocket otherwise weak in the template bioactive kinase inhibitor, which enhance the binding efficacy of these newly designed ligands in the kinase-binding pocket.