Polypharmacology guided drug repositioning approach for SARS-CoV2.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 09 04 2023
accepted: 27 07 2023
medline: 11 8 2023
pubmed: 9 8 2023
entrez: 9 8 2023
Statut: epublish

Résumé

Drug repurposing has emerged as an important strategy and it has a great potential in identifying therapeutic applications for COVID-19. An extensive virtual screening of 4193 FDA approved drugs has been carried out against 24 proteins of SARS-CoV2 (NSP1-10 and NSP12-16, envelope, membrane, nucleoprotein, spike, ORF3a, ORF6, ORF7a, ORF8, and ORF9b). The drugs were classified into top 10 and bottom 10 drugs based on the docking scores followed by the distribution of their therapeutic indications. As a result, the top 10 drugs were found to have therapeutic indications for cancer, pain, neurological disorders, and viral and bacterial diseases. As drug resistance is one of the major challenges in antiviral drug discovery, polypharmacology and network pharmacology approaches were employed in the study to identify drugs interacting with multiple targets and drugs such as dihydroergotamine, ergotamine, bisdequalinium chloride, midostaurin, temoporfin, tirilazad, and venetoclax were identified among the multi-targeting drugs. Further, a pathway analysis of the genes related to the multi-targeting drugs was carried which provides insight into the mechanism of drugs and identifying targetable genes and biological pathways involved in SARS-CoV2.

Identifiants

pubmed: 37556478
doi: 10.1371/journal.pone.0289890
pii: PONE-D-23-10719
pmc: PMC10411734
doi:

Substances chimiques

RNA, Viral 0
Protease Inhibitors 0
Antiviral Agents 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0289890

Informations de copyright

Copyright: © 2023 Jamir et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors declare no competing interests.

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Auteurs

Esther Jamir (E)

Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.

Himakshi Sarma (H)

Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India.

Lipsa Priyadarsinee (L)

Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.

Kikrusenuo Kiewhuo (K)

Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.

Selvaraman Nagamani (S)

Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.

G Narahari Sastry (GN)

Advanced Computation and Data Sciences Division, CSIR-North East Institute of Science and Technology, Jorhat, Assam, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India.

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