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

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          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.

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          Most cited references 41

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          Virtual screening of chemical libraries.

          Virtual screening uses computer-based methods to discover new ligands on the basis of biological structures. Although widely heralded in the 1970s and 1980s, the technique has since struggled to meet its initial promise, and drug discovery remains dominated by empirical screening. Recent successes in predicting new ligands and their receptor-bound structures, and better rates of ligand discovery compared to empirical screening, have re-ignited interest in virtual screening, which is now widely used in drug discovery, albeit on a more limited scale than empirical screening.
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            ElNemo: a normal mode web server for protein movement analysis and the generation of templates for molecular replacement.

            Normal mode analysis (NMA) is a powerful tool for predicting the possible movements of a given macromolecule. It has been shown recently that half of the known protein movements can be modelled by using at most two low-frequency normal modes. Applications of NMA cover wide areas of structural biology, such as the study of protein conformational changes upon ligand binding, membrane channel opening and closure, potential movements of the ribosome, and viral capsid maturation. Another, newly emerging field of NMA is related to protein structure determination by X-ray crystallography, where normal mode perturbed models are used as templates for diffraction data phasing through molecular replacement (MR). Here we present ElNémo, a web interface to the Elastic Network Model that provides a fast and simple tool to compute, visualize and analyse low-frequency normal modes of large macro-molecules and to generate a large number of different starting models for use in MR. Due to the 'rotation-translation-block' (RTB) approximation implemented in ElNémo, there is virtually no upper limit to the size of the proteins that can be treated. Upon input of a protein structure in Protein Data Bank (PDB) format, ElNémo computes its 100 lowest-frequency modes and produces a comprehensive set of descriptive parameters and visualizations, such as the degree of collectivity of movement, residue mean square displacements, distance fluctuation maps, and the correlation between observed and normal-mode-derived atomic displacement parameters (B-factors). Any number of normal mode perturbed models for MR can be generated for download. If two conformations of the same (or a homologous) protein are available, ElNémo identifies the normal modes that contribute most to the corresponding protein movement. The web server can be freely accessed at http://igs-server.cnrs-mrs.fr/elnemo/index.html.
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              Protein normal-mode dynamics: trypsin inhibitor, crambin, ribonuclease and lysozyme.

              We have developed a new method for modelling protein dynamics using normal-mode analysis in internal co-ordinates. This method, normal-mode dynamics, is particularly well suited for modelling collective motion, makes possible direct visualization of biologically interesting modes, and is complementary to the more time-consuming simulation of molecular dynamics trajectories. The essential assumption and limitation of normal-mode analysis is that the molecular potential energy varies quadratically. Our study starts with energy minimization of the X-ray co-ordinates with respect to the single-bond torsion angles. The main technical task is the calculation of second derivative matrices of kinetic and potential energy with respect to the torsion angle co-ordinates. These enter into a generalized eigenvalue problem, and the final eigenvalues and eigenvectors provide a complete description of the motion in the basic 0.1 to 10 picosecond range. Thermodynamic averages of amplitudes, fluctuations and correlations can be calculated efficiently using analytical formulae. The general method presented here is applied to four proteins, trypsin inhibitor, crambin, ribonuclease and lysozyme. When the resulting atomic motion is visualized by computer graphics, it is clear that the motion of each protein is collective with all atoms participating in each mode. The slow modes, with frequencies of below 10 cm-1 (a period of 3 ps), are the most interesting in that the motion in these modes is segmental. The root-mean-square atomic fluctuations, which are dominated by a few slow modes, agree well with experimental temperature factors (B values). The normal-mode dynamics of these four proteins have many features in common, although in the larger molecules, lysozyme and ribonuclease, there is low frequency domain motion about the active site.
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                Author and article information

                Journal
                Drug Des Devel Ther
                Drug Des Devel Ther
                Drug Design, Development and Therapy
                Drug Design, Development and Therapy
                Dove Medical Press
                1177-8881
                2017
                19 June 2017
                : 11
                : 1803-1813
                Affiliations
                Faculty of Medicine in the Galilee, Bar Ilan University, Safed, Israel
                Author notes
                Correspondence: Abraham O Samson, Faculty of Medicine in the Galilee, Bar Ilan University, 8 Henrietta Szold Street, Safed, Israel, Tel +972 54 795 8894, Email avraham.samson@ 123456biu.ac.il
                [*]

                These authors contributed equally to this work

                Article
                dddt-11-1803
                10.2147/DDDT.S133127
                5484510
                © 2017 Glantz-Gashai et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Pharmacology & Pharmaceutical medicine

                normal modes, nmr, molecular dynamics, mcl-1, virtual screening

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