Unknown

Dataset Information

0

Identification of highly effective inhibitors against SARS-CoV-2 main protease: From virtual screening to in vitro study


ABSTRACT: Background and Objective: The public’s safety has been significantly jeopardized by the pandemic of COVID-19, which is brought on by the highly virulent and contagious SARS-CoV-2 virus. Finding novel antiviral drugs is currently of utmost importance for the treatment of patients with COVID-19. Main protease (3CLpro) of SARS-CoV-2 is involved in replication of virus, so it is considered as a promising target. Using small molecules to inhibit SARS-CoV-2-3CLpro activity may be an effective way to prevent viral replication to fight COVID-19. Despite the fact that some SARS-CoV-2-3CLpro inhibitors have been described, only few of them have high levels of inhibition at nanomolar concentrations. In this study, we aimed to screen out effective SARS-CoV-2-3CLpro inhibitors. Methods: To identify highly effective SARS-CoV-2-3CLpro inhibitors, a pharmacophore mapping and multiple-conformation docking were efficiently applied to find novel hit compounds from a database. Then, the stability of the 3CLpro-hit complexes was validated by using molecular dynamics simulation. Finally, biological assay was used to assess the inhibition effects of hit compounds on SARS-CoV-2-3CLpro. Results: Four hit compounds were identified by using computer-assisted strategy. Molecular dynamics simulation suggested that these hits bound stably to the 3CLpro-active pocket. Bioassay showed that all the hits had potent inhibition against SARS-CoV-2-3CLpro with IC50 values in the range of 0.017–0.83 μM. Particularly, hit one was the best 3CLpro inhibitor and its inhibition effect of SARS-CoV-2-3CLpro (IC50 = 0.017 ± 0.003 µM) was about 236 times stronger than that of ML300 (IC50 = 4.01 ± 0.66 µM). Conclusion: These data indicate that hit one could be regarded as an anti-SARS-CoV-2 candidate worth exploring further for the treatment of COVID-19.

SUBMITTER: Wang H 

PROVIDER: S-EPMC9715617 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC7316061 | biostudies-literature
| S-EPMC7550866 | biostudies-literature
| S-EPMC8029447 | biostudies-literature
| S-EPMC7537881 | biostudies-literature
| S-EPMC8848513 | biostudies-literature
| S-EPMC8251402 | biostudies-literature
| S-EPMC7396980 | biostudies-literature
| S-EPMC8301192 | biostudies-literature
| S-EPMC10663854 | biostudies-literature
| S-EPMC9695405 | biostudies-literature