A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase

Abstract

Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased molecular dynamics simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased molecular dynamics simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) molecular dynamics simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding’s process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nano-second timescales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction. Supplementary information Supplementary data are available at Bioinformatics online.

The impact of inhibitor size and flexibility on the binding pathways to c-Src kinase

“…Our simulations, which extensively sample the inhibitor and kinase binding site residues, provide a statistically converged description for both binding and unbinding pathways. Closely concordant pathways have also been reported for dasatinib binding using unbiased simulations 33,38 . Traditionally, properties such as conformational flexibility and the number of rotatable bonds have been considered in relation to oral bioavailability 36 .…”

Reconstruction of the unbinding pathways of noncovalent SARS-CoV and SARS-CoV-2 3CLpro inhibitors using unbiased molecular dynamics simulations

“…MD simulation has been used in many science fields since the 1950s to predict hidden information that cannot be reached through experimental research [ 17 ]. The UMD method eliminates artificial interactions between protein and inhibitor because it does not apply any biasing forces or potentials to the simulations [ 18 ]. Studying the unbinding mechanisms of inhibitors in complex with their target proteins is one of the great features of the UMD simulation method.…”

Unraveling the unbinding pathways of SARS-CoV-2 Papain-like proteinase known inhibitors by Supervised Molecular Dynamics simulation

“…Computational Methods in SBDD such as Unbiased Molecular Dynamics (UMD) simulation can accurately investigate the important details of mechanisms such as binding and unbinding mechanisms that are vital for rational drug design [26][27][28][29][30][31][32]. Utilizing these fast and accurate methods is of great importance when urgent treatment solutions are needed.…”