In silico identification of drug candidates against COVID-19

© 2020 The Author(s)..

The COVID-19 pandemic has caused unprecedented health and economic crisis throughout the world. However, there is no effective medication or therapeutic strategy for treatment of this disease currently. Here, to elucidate the inhibitory effects, we first tested binding affinities of 11 HIV-1 protease inhibitors or their pharmacoenhancers docked onto SARS-CoV-2 main protease (M pro ), and 12 nucleotide-analog inhibitors docked onto RNA dependent RNA polymerase (RdRp). To further obtain the effective drug candidates, we screened 728 approved drugs via virtual screening on SARS-CoV-2 M pro . Our results demonstrate that remdesivir shows the best binding energy on RdRp and saquinvir is the best inhibitor of M pro . Based on the binding energies, we also list 10 top-ranked approved drugs which can be potential inhibitors for M pro . Overall, our results do not only propose drug candidates for further experiments and clinical trials but also pave the way for future lead optimization and drug design.

Medienart:

E-Artikel

Erscheinungsjahr:

2020

Erschienen:

2020

Enthalten in:

Zur Gesamtaufnahme - volume:21

Enthalten in:

Informatics in medicine unlocked - 21(2020) vom: 20., Seite 100461

Sprache:

Englisch

Beteiligte Personen:

Wu, Yifei [VerfasserIn]
Chang, Kuan Y [VerfasserIn]
Lou, Lei [VerfasserIn]
Edwards, Lorette G [VerfasserIn]
Doma, Bly K [VerfasserIn]
Xie, Zhong-Ru [VerfasserIn]

Links:

Volltext

Themen:

COVID-19
Drug repurposing
Journal Article
Ligand-protein docking
Main protease
RNA-dependent RNA polymerase
Remdesivir
Virtual screening

Anmerkungen:

Date Revised 12.11.2023

published: Print-Electronic

Citation Status PubMed-not-MEDLINE

doi:

10.1016/j.imu.2020.100461

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM316715069