Structure-based virtual screening and molecular dynamics simulations for detecting novel candidates as FGFR1 inhibitors

Abstract

Structure-based virtual screening (SBVS) was performed to predict lead compounds for fibroblast growthfactor receptor 1 (FGFR1) inhibition screening the kinase inhibitor database taken from ChEMBL. The prepared kinaseinhibitor database consisted of 48017 ligands were screened in ATP binding site of FGFR1 by CCDC Gold softwareusing virtual screening parameters to filter out. After then, 720 ligands were docked inside FGFR1 using default dockingparameters of CCDC Gold software. The GOLD fitness score values of 70 and 80 was used a threshold value forscreening and docking process, respectively. The ligands as reduced numbers to twenty-two in terms of docking resultswere utilized to calculate MMGBSA free binding energy from 10 ns molecular dynamics simulations (MDS). Forrefinement of results, six of twenty-two ligands which have better calculated MMGBSA free binding energy wereexposed to 100 ns MDS. Then, 100 ns MDS trajectories of six compounds were used to calculate MMGBSA free bindingenergy, and MDS were expended to 250 ns for three ligands which have highest free binding energies. By free bindingenergies calculated from expanded MDS, were used to predict the most promising candidates (compounds G9 andG10) for FGFR1 inhibition. Structure stability, binding modes and energy decomposition analysis were performed toinsight into dynamic behaviors of compounds G9 and G10 inside FGFR-1.