Reporting dinaciclib and theodrenaline as a multitargeted inhibitor against SARS-CoV-2: an in-silico study

Abstract

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is one of the rapid spreading coronaviruses that belongs to the Coronaviridae family. The rapidly evolving nature of SARS-CoV-2 results in a variety of variants with a capability of evasion to existing therapeutics and vaccines. So, there is an imperative need to discover potent drugs that can able to disrupt the function of multiple drug targets to tackle the SARS-CoV-2 menace. Here in this study, we took the different targets of SARS-CoV-2 prepared in the Schrodinger maestro. The library of the DrugBank database is screened against the selected crucial targets. Our molecular docking, Molecular Mechanics/Generalized Born Surface Area (MMGBSA), and molecular dynamics simulation studies led to identifying dinaciclib and theodrenaline as potential drugs against multiple drug targets: main protease, NSP15-endoribonuclease and papain-like-protease, of SARS-CoV-2. Dinaciclib with papain-like protease and NSP15-endoribonuclease show the docking score of −7.015 and −8.737, respectively, while the theodrenaline with NSP15-endoribonuclease and main protease produced the docking score of −8.507 and −7.289, respectively. Furthermore, the binding free energy calculations with MM/GBSA and molecular dynamics simulation studies of the complexes confirm the reliability of the drugs. The selected drugs are capable of binding to multiple targets simultaneously, thus withstanding their activity of target disruption in different variants of SARS-CoV-2. Although, the repurposed drugs are showing potent activity, but may need further in-vitro and in-vivo validations.

Communicated by Ramaswamy H. Sarma

Keywords:

• SARS-CoV-2
• papain-like protease
• NSP15-endoribonuclease
• main protease
• molecular docking
• molecular dynamics simulation

Acknowledgements

The authors would like to thank SRM University and Jamia Millia Islamia for providing computational support. MKY is thankful to SERB for funding the project (CVD/2020/000447).

Availability of data and material

All the data and supplementary material can be made public after publication.

Competing interests

The authors declare there is no competing interest.

Consent for publication

All authors consent to submit the manuscript to the journal.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethical responsibilities

This manuscript is a core computational biology study, and the research does not involve humans or any other organism physically, so the ethical issues are not applicable.

Author contribution

Conceptulization, Data collection/curation, analysis, and writing the first draft, Shaban Ahmad; computational resources and result analysis, Murugesh Eswaran, Mussuvir KM; conceptualization and editing, Khalid Raza; Editing and reviewing, Misbahuddin M Rafeeq, Alaa Hamed Habib; conceptualization, supervision and Funding acquisition, Manoj Kumar Yadav.

Additional information

Funding

The project is supported by the Science and Engineering Research Board (SERB), Govt of India, with file no. CVD/2020/000447.