Computational insights into tetracyclines as inhibitors against SARS-CoV-2 Mpro via combinatorial molecular simulation calculations.
Life Sci
; 257: 118080, 2020 Sep 15.
Article
in English
| MEDLINE | ID: covidwho-1152544
Semantic information from SemMedBD (by NLM)
1. Antibiotics compared_with Inhibitor
2. Antibiotics compared_with Inhibitor
ABSTRACT
The COVID-19 pandemic raised by SARS-CoV-2 is a public health emergency. However, lack of antiviral drugs and vaccine against human coronaviruses demands a concerted approach to challenge the SARS-CoV-2 infection. Under limited resource and urgency, combinatorial computational approaches to identify the potential inhibitor from known drugs could be applied against risen COVID-19 pandemic. Thereof, this study attempted to purpose the potent inhibitors from the approved drug pool against SARS-CoV-2 main protease (Mpro). To circumvent the issue of lead compound from available drugs as antivirals, antibiotics with broad spectrum of viral activity, i.e. doxycycline, tetracycline, demeclocycline, and minocycline were chosen for molecular simulation analysis against native ligand N3 inhibitor in SARS-CoV-2 Mpro crystal structure. Molecular docking simulation predicted the docking score >-7 kcal/mol with significant intermolecular interaction at the catalytic dyad (His41 and Cys145) and other essential substrate binding residues of SARS-CoV-2 Mpro. The best ligand conformations were further studied for complex stability and intermolecular interaction profiling with respect to time under 100 ns classical molecular dynamics simulation, established the significant stability and interactions of selected antibiotics by comparison to N3 inhibitor. Based on combinatorial molecular simulation analysis, doxycycline and minocycline were selected as potent inhibitor against SARS-CoV-2 Mpro which can used in combinational therapy against SARS-CoV-2 infection.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Tetracyclines
/
Betacoronavirus
Type of study:
Prognostic study
Topics:
Vaccines
Limits:
Humans
Language:
English
Journal:
Life Sci
Year:
2020
Document Type:
Article
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