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Virtual screening for potential inhibitors of Mcl-1 conformations sampled by normal modes, molecular dynamics, and nuclear magnetic resonance

Authors Glantz-Gashai Y, Meirson T, Reuveni E, Samson AO

Received 24 January 2017

Accepted for publication 6 April 2017

Published 19 June 2017 Volume 2017:11 Pages 1803—1813

DOI https://doi.org/10.2147/DDDT.S133127

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Rasika Samarasinghe

Peer reviewer comments 2

Editor who approved publication: Dr Anastasios Lymperopoulos

Yitav Glantz-Gashai,* Tomer Meirson,* Eli Reuveni, Abraham O Samson

Faculty of Medicine in the Galilee, Bar Ilan University, Safed, Israel

*These authors contributed equally to this work

Abstract: Myeloid cell leukemia-1 (Mcl-1) is often overexpressed in human cancer and is an important target for developing antineoplastic drugs. In this study, a data set containing 2.3 million lead-like molecules and a data set of all the US Food and Drug Administration (FDA)-approved drugs are virtually screened for potential Mcl-1 ligands using Protein Data Bank (PDB) ID 2MHS. The potential Mcl-1 ligands are evaluated and computationally docked on to three conformation ensembles generated by normal mode analysis (NMA), molecular dynamics (MD), and nuclear magnetic resonance (NMR), respectively. The evaluated potential Mcl-1 ligands are then compared with their clinical use. Remarkably, half of the top 30 potential drugs are used clinically to treat cancer, thus partially validating our virtual screen. The partial validation also favors the idea that the other half of the top 30 potential drugs could be used in the treatment of cancer. The normal mode-, MD-, and NMR-based conformation greatly expand the conformational sampling used herein for in silico identification of potential Mcl-1 inhibitors.

Keywords: virtual screening, Mcl-1, molecular dynamics, NMR, normal modes

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