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      Identification of FDA approved drugs and nucleoside analogues as potential SARS-CoV-2 A1pp domain inhibitor: An in silico study

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          Abstract

          Coronaviruses are known to infect respiratory tract and intestine. These viruses possess highly conserved viral macro domain A1pp having adenosine diphosphate (ADP)-ribose binding and phosphatase activity sites. A1pp inhibits adenosine diphosphate (ADP)-ribosylation in the host and promotes viral infection and pathogenesis. We performed in silico screening of FDA approved drugs and nucleoside analogue library against the recently reported crystal structure of SARS-CoV-2 A1pp domain. Docking scores and interaction profile analyses exhibited strong binding affinity of eleven FDA approved drugs and five nucleoside analogues NA 1 (−13.84), nadide (−13.65), citicholine (−13.54), NA 2 (−12.42), and NA 3 (−12.27). The lead compound NA 1 exhibited significant hydrogen bonding and hydrophobic interaction at the natural substrate binding site. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface (SASA), hydrogen bond formation, principle component analysis, and free energy landscape calculations for NA 1 bound protein displayed stable complex formation in 100 ns molecular dynamics simulation, compared to unbound macro domain and natural substrate adenosine-5-diphosphoribose bound macro domain that served as a positive control. The molecular mechanics Poisson–Boltzmann surface area analysis of NA 1 demonstrated binding free energy of −175.978 ± 0.401 kJ/mol in comparison to natural substrate which had binding free energy of −133.403 ± 14.103 kJ/mol. In silico analysis by modelling tool ADMET and prediction of biological activity of these compounds further validated them as putative therapeutic molecules against SARS-CoV-2. Taken together, this study offers NA 1 as a lead SARS-CoV-2 A1pp domain inhibitor for future testing and development as therapeutics against human coronavirus.

          Highlights

          • SARS-CoV-2 ADP-Ribose phosphatase is a drugable target.

          • FDA approved drugs act as potential inhibitors of ADP-Ribose phosphatase.

          • Nucleoside inhibitor binds and stabilizes the ADP-Ribose phosphatase.

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          Most cited references37

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          UCSF Chimera--a visualization system for exploratory research and analysis.

          The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. Copyright 2004 Wiley Periodicals, Inc.
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              AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

              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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                Author and article information

                Journal
                Comput Biol Med
                Comput Biol Med
                Computers in Biology and Medicine
                Published by Elsevier Ltd.
                0010-4825
                1879-0534
                19 December 2020
                March 2021
                19 December 2020
                : 130
                : 104185
                Affiliations
                [a ]Molecular Signaling & Drug Discovery Laboratory, Department of Biochemistry, School of Basic and Applied Sciences, Central University of Punjab, Bathinda, 151401, India
                [b ]Department of Urology, Case Western Reserve University, Cleveland, OH, 44106, USA
                Author notes
                []Corresponding author. Department of Biochemistry, School of Basic and Applied Sciences, Central University of Punjab, Bathinda, 151001, India.
                [1]

                Authors contributed equally.

                Article
                S0010-4825(20)30516-3 104185
                10.1016/j.compbiomed.2020.104185
                7749648
                33352458
                805f94e6-0dde-45c5-a201-30ab7f313ddf
                © 2020 Published by Elsevier Ltd.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 7 October 2020
                : 15 December 2020
                : 15 December 2020
                Categories
                Article

                sars-cov-2,a1pp domain,macro domain,nucleoside analogues,fda approved drugs,in silico

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