Clustering and Sampling of the c-Met Conformational Space: A Computational Drug Discovery Study

Korosh Mashayekh; Shahrzad Sharifi; Tahereh Damghani; Maryam Elyasi; Mohammad S Avestan; Somayeh Pirhadi

doi:10.2174/1386207322666191024103902

Clustering and Sampling of the c-Met Conformational Space: A Computational Drug Discovery Study

Comb Chem High Throughput Screen. 2019;22(9):635-648. doi: 10.2174/1386207322666191024103902.

Authors

Korosh Mashayekh¹, Shahrzad Sharifi¹, Tahereh Damghani^{1

2}, Maryam Elyasi¹, Mohammad S Avestan³, Somayeh Pirhadi¹

Affiliations

¹ Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
² School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
³ Department of Chemistry, University of Cincinnati, Cincinnati, OH 45221, United States.

PMID: 31696808
DOI: 10.2174/1386207322666191024103902

Abstract

Background: c-Met kinase plays a critical role in a myriad of human cancers, and a massive scientific work was devoted to design more potent inhibitors.

Objective: In this study, 16 molecular dynamics simulations of different complexes of potent c-Met inhibitors with U-shaped binding mode were carried out regarding the dynamic ensembles to design novel potent inhibitors.

Methods: A cluster analysis was performed, and the most representative frame of each complex was subjected to the structure-based pharmacophore screening. The GOLD docking program investigated the interaction energy and pattern of output hits from the virtual screening. The most promising hits with the highest scoring values that showed critical interactions with c-Met were presented for ADME/Tox analysis.

Results: The screening yielded 45,324 hits that all of them were subjected to the docking studies and 10 of them with the highest-scoring values having diverse structures were presented for ADME/Tox analyses.

Conclusion: The results indicated that all the hits shared critical Pi-Pi stacked and hydrogen bond interactions with Tyr1230 and Met1160 respectively.

Keywords: c-Met; clustering; docking; molecular dynamics simulation; potent inhibitor; virtual screening..

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Cluster Analysis
Drug Discovery*
High-Throughput Screening Assays
Humans
Molecular Dynamics Simulation*
Molecular Structure
Protein Kinase Inhibitors / chemistry
Protein Kinase Inhibitors / pharmacology*
Proto-Oncogene Proteins c-met / antagonists & inhibitors*
Proto-Oncogene Proteins c-met / metabolism

Substances

Protein Kinase Inhibitors
Proto-Oncogene Proteins c-met