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

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.