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      Exploring the active constituents of Oroxylum indicum in intervention of novel coronavirus (COVID-19) based on molecular docking method

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          Graphical abstract

          The severe acute respiratory syndrome COVID-19 declared a global pandemic by WHO has become the present wellbeing worry to the whole world. There is an emergent need to search for possible medications. We report in this study a molecular docking study of eighteen Oroxylum indicum molecules with the main protease (M pro) responsible for the replication of SARS-CoV-2 virus. The outcome of their molecular simulation and ADMET properties reveal four potential inhibitors of the enzyme (Baicalein-7- O-diglucoside, Chrysin-7- O-glucuronide, Oroxindin and Scutellarein) with preference of ligand Chrysin-7- O-glucuronide that has the second highest binding energy (− 8.6 kcal/mol) and fully obeys the Lipinski’s rule of five.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s13721-020-00279-y.

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          Is Open Access

          Open Babel: An open chemical toolbox

          Noel O’Boyle, Michael Banck, Craig James … (2011)
          Background A frequent problem in computational modeling is the interconversion of chemical structures between different formats. While standard interchange formats exist (for example, Chemical Markup Language) and de facto standards have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chemistry data, differences in the data stored by different formats (0D versus 3D, for example), and competition between software along with a lack of vendor-neutral formats. Results We discuss, for the first time, Open Babel, an open-source chemical toolbox that speaks the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chemical and molecular data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion. Conclusions Open Babel presents a solution to the proliferation of multiple chemical file formats. In addition, it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chemical data in areas such as organic chemistry, drug design, materials science, and computational chemistry. It is freely available under an open-source license from http://openbabel.org.
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            Genome Composition and Divergence of the Novel Coronavirus (2019-nCoV) Originating in China

            Aiping Wu, Yousong Peng, Baoying Huang … (2020)
            An in-depth annotation of the newly discovered coronavirus (2019-nCoV) genome has revealed differences between 2019-nCoV and severe acute respiratory syndrome (SARS) or SARS-like coronaviruses. A systematic comparison identified 380 amino acid substitutions between these coronaviruses, which may have caused functional and pathogenic divergence of 2019-nCoV.
            Article 0 comments Cited 1102 times – based on 0 reviews     Review now
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              Analysis of therapeutic targets for SARS-CoV-2 and discovery of potential drugs by computational methods

              Canrong Wu, Yang Liu, Yueying Yang … (2020)
              SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections.
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                Author and article information

                Contributors
                Sapan Shah:
                ORCID: https://orcid.org/0000-0002-8155-9361
                shah.sapan@rediffmail.com
                Dinesh Chaple: d.chaple@rediffmail.com
                Sumit Arora:
                ORCID: https://orcid.org/0000-0001-9453-6057
                sumitkishanarora@gmail.com
                Subhash Yende: subhashyende@gmail.com
                Keshav Moharir:
                ORCID: https://orcid.org/0000-0003-3792-2896
                keshavmoharir@gmail.com
                Govind Lohiya:
                ORCID: https://orcid.org/0000-0003-2286-3360
                lohiyagovind@gmail.com
                Journal
                Journal ID (nlm-ta): Netw Model Anal Health Inform Bioinform
                Journal ID (iso-abbrev): Netw Model Anal Health Inform Bioinform
                Title: Network Modeling and Analysis in Health Informatics and Bioinformatics
                Publisher: Springer Vienna (Vienna )
                ISSN (Print): 2192-6662
                ISSN (Electronic): 2192-6670
                Publication date (Electronic): 6 February 2021
                Publication date (Print): 2021
                Volume: 10
                Issue: 1
                Electronic Location Identifier: 8
                Affiliations
                [1 ]Department of Pharmaceutical Chemistry, Priyadarshini J. L. College of Pharmacy, Hingna Road, Nagpur, Maharashtra 440016 India
                [2 ]Pharmacognosy and Phytochemistry Division, Gurunanak College of Pharmacy, Nari, Nagpur, Maharashtra 440026 India
                [3 ]Pharmacology Department, Gurunanak College of Pharmacy, Nari, Nagpur, Maharashtra 440026 India
                [4 ]Pharmaceutics Department, Gurunanak College of Pharmacy, Nari, Nagpur, Maharashtra 440026 India
                Author information
                https://orcid.org/0000-0002-8155-9361
                https://orcid.org/0000-0001-9453-6057
                https://orcid.org/0000-0003-3792-2896
                https://orcid.org/0000-0003-2286-3360
                Article
                Publisher ID: 279
                DOI: 10.1007/s13721-020-00279-y
                PMC ID: 7865104
                SO-VID: c199631d-f59e-49e3-b4a0-b4a48273776f
                Copyright © © The Author(s), under exclusive licence to Springer-Verlag GmbH, AT part of Springer Nature 2021
                License:

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                Date received : 28 August 2020
                Date revision received : 24 November 2020
                Date accepted : 15 December 2020
                Categories
                Subject: Original Article
                Custom metadata
                issue-copyright-statement © Springer-Verlag GmbH Austria, part of Springer Nature 2021

                Keywords: covid-19,oroxylum indicum,molecular docking,molecular dynamics,admet study
                Data availability:
                Keywords: covid-19, oroxylum indicum, molecular docking, molecular dynamics, admet study

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