0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Join our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessAbstract Coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic by the World Health Organization, and the situation worsens daily, associated with acute increases in case fatality rates. The main protease (Mpro) enzyme produced by SARS-CoV-2 was recently demonstrated to be responsible for not only viral reproduction but also impeding host immune responses. The element selenium (Se) plays a vital role in immune functions, both directly and indirectly. Thus, we hypothesised that Se-containing heterocyclic compounds might curb the activity of SARS-CoV-2 Mpro. We performed a molecular docking analysis and found that several of the selected selenocompounds showed potential binding affinities for SARS-CoV-2 Mpro, especially ethaselen (49), which exhibited a docking score of −6.7 kcal/mol compared with the −6.5 kcal/mol score for GC376 (positive control). Drug-likeness calculations suggested that these compounds are biologically active and possess the characteristics of ideal drug candidates. Based on the binding affinity and drug-likeness results, we selected the 16 most effective selenocompounds as potential anti-COVID-19 drug candidates. We also validated the structural integrity and stability of the drug candidate through molecular dynamics simulation. Using further in vitro and in vivo experiments, we believe that the targeted compound identified in this study (ethaselen) could pave the way for the development of prospective drugs to combat SARS-CoV-2 infections and trigger specific host immune responses.
Ahmed Rakib, Zulkar Nain, Saad Ahmed Sami, Shafi Mahmud, Md. Ashiqul Islam, Shahriar Ahmed, Adnan Bin Faisul Siddiqui, S.M. Omar Faruque Babu, Payar Hossain, Asif Shahriar, Firzan Nainu, Talha Bin Emran, Jesus Simal Gandara (2021). A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an <i>in silico</i> investigation. , 22(2), DOI: https://doi.org/10.1093/bib/bbab045.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2021
Authors
13
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1093/bib/bbab045
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free AccessYes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaboration