Structure-based virtual screening and molecular dynamics simulations for detecting novel candidates for allosteric inhibition of EGFRT790M

Abstract

Structure-based virtual screening (SBVS) was applied to predict lead compounds for the allosteric inhibition of epidermal growth factor receptor (EGFR) by screening the library of chemical compounds prepared from the e-molecules chemical database. The library of chemical compounds consisting of 133,083 ligands was composed by evaluating the chemical and physical properties of e-molecules chemicals. The prepared library was screened by CCDC Gold software in the allosteric binding site of EGFRT790M using the library and virtual screening default parameters to filter out, respectively. The GOLD fitness scores 75 and 80 were selected as threshold values for the library and virtual screening processes, respectively. After the docking study, molecular dynamics simulations (MDS) of the top 25 compounds were built for calculating binding free energies from their MDS trajectories. MM-GBSA binding free energies for the compounds were computed from 20 ns MDS, 50 ns MDS and 200 ns MDS trajectories to filter out the candidates. Following MM-GBSA/MM-PBSA binding free energy calculations, six compounds were detected as the most promising candidates for allosteric inhibition of EGFRT790M. The dynamic behaviors of final compounds inside EGFR T790M were searched using structure stability, binding modes and energy decomposition analysis. Besides, the estimated inhibitors were exposed to docking study and MM-GBSA/MM-PBSA binding free energy calculations inside wild-type EGFR, respectively, to be determined their selectivity towards mutant form. Five of the estimated inhibitors displayed estimated selectivity towards EGFRT790M. Besides the ADMET properties of the estimated inhibitors were predicted by PreAdmet tools.

Communicated by Ramaswamy H. Sarma

Keywords:

• EGFRT790M
• virtual screening
• molecular dynamics simulations
• binding free energy
• allosteric inhibition

Acknowledgements

This work has not been supported by any organization as financial. On the other hand, author appreciates to Pharmaceutical Sciences Research Centre (FABAL) of Ege University Faculty of Pharmacy and Ege University Rectorate for molecular modelling software support.

Author’s Contributions

G.C. planned the study, conducted the research, prepare the library, performed molecular docking and molecular dynamics simulations, analyzed the data, made corresponding figures, tables supplementary file, drafted and edited the manuscript.

Disclosure Statement

The author declared no conflict of interest in the manuscript.

Data Availability

Outputs obtained during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.