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      Pangenome Analysis of Mycobacterium tuberculosis Reveals Core-Drug Targets and Screening of Promising Lead Compounds for Drug Discovery

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          Abstract

          Tuberculosis, caused by Mycobacterium tuberculosis ( M. tuberculosis), is one of the leading causes of human deaths globally according to the WHO TB 2019 report. The continuous rise in multi- and extensive-drug resistance in M. tuberculosis broadens the challenges to control tuberculosis. The availability of a large number of completely sequenced genomes of M. tuberculosis has provided an opportunity to explore the pangenome of the species along with the pan-phylogeny and to identify potential novel drug targets leading to drug discovery. We attempt to calculate the pangenome of M. tuberculosis that comprises a total of 150 complete genomes and performed the phylo-genomic classification and analysis. Further, the conserved core genome (1251 proteins) is subjected to various sequential filters (non-human homology, essentiality, virulence, physicochemical parameters, and pathway analysis) resulted in identification of eight putative broad-spectrum drug targets. Upon molecular docking analyses of these targets with ligands available at the DrugBank database shortlisted a total of five promising ligands with projected inhibitory potential; namely, 2′deoxy-thymidine-5′-diphospho-alpha- d-glucose, uridine diphosphate glucose, 2′-deoxy-thymidine-beta- l-rhamnose, thymidine-5′-triphosphate, and citicoline. We are confident that with further lead optimization and experimental validation, these lead compounds may provide a sound basis to develop safe and effective drugs against tuberculosis disease in humans.

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          AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. Copyright 2009 Wiley Periodicals, Inc.
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            The Protein Data Bank (PDB; http://www.rcsb.org/pdb/ ) is the single worldwide archive of structural data of biological macromolecules. This paper describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information, and near-term plans for the future development of the resource.
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                Author and article information

                Journal
                Antibiotics (Basel)
                Antibiotics (Basel)
                antibiotics
                Antibiotics
                MDPI
                2079-6382
                17 November 2020
                November 2020
                : 9
                : 11
                : 819
                Affiliations
                [1 ]Atta-ur-Rahman School of Applied Biosciences, National University of Sciences and Technology, Islamabad 44000, Pakistan; darhamza000@ 123456gmail.com (H.A.D.); zaheertahreem@ 123456gmail.com (T.Z.); nimatscholar@ 123456gmail.com (N.U.)
                [2 ]Department of Bioinformatics and Biosciences, Capital University of Science and Technology Islamabad expressway, Kahuta Road, Zone-V, Islamabad 44000, Pakistan; marriam@ 123456cust.edu.pk
                [3 ]State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health (GIBH), Chinese Academy of Sciences, Guangzhou 510530, China; zhang_tianyu@ 123456gibh.ac.cn
                [4 ]Special Infectious Agents Unit, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 21589, Saudi Arabia; yamuhammad@ 123456kau.edu.sa
                [5 ]Medical Laboratory Technology Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah 21589, Saudi Arabia
                Author notes
                [* ]Correspondence: eazhar@ 123456kau.edu.sa (E.I.A.); amjad.ali@ 123456asab.nust.edu.pk (A.A.); Tel.: +92-3339191903 (A.A.)
                Author information
                https://orcid.org/0000-0002-0667-5653
                https://orcid.org/0000-0002-7138-1272
                https://orcid.org/0000-0001-5647-6014
                https://orcid.org/0000-0003-1111-1104
                https://orcid.org/0000-0002-1736-181X
                https://orcid.org/0000-0002-0486-4661
                Article
                antibiotics-09-00819
                10.3390/antibiotics9110819
                7698547
                33213029
                cc4b6cd4-d64b-4ee4-9387-81083d5f67cb
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 October 2020
                : 15 November 2020
                Categories
                Article

                mycobacterium tuberculosis,pangenome,drug targets,molecular docking,lead compounds,drug discovery,tuberculosis

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