Novel drug compound hunting was carried out for SARS-CoV-2 proteins with low mutation susceptibility. The probability of escape mutation and drug resistance is lower if conserved microbial proteins are targeted by therapeutic drugs. Mutation rate of all SARS-CoV-2 proteins were analyzed via multiple sequence alignment Non-Structural Protein 13 and Non-Structural Protein 16 were selected for the current study due to low mutation rate among viral strains and significant functionality. Cross-species mutation rate analysis for NSP13 and NSP16 showed these are well-conserved proteins among four coronaviral species. Viral helicase inhibitors, identified using literature-mining, were docked against NSP13. Pharmacophore-based screening of 11,375 natural compounds was conducted for NSP16. Stabilities of top compounds inside human body were confirmed via molecular dynamic simulation. ADME properties and LD(50) values of the helicase inhibitors and Ambinter natural compounds were analyzed. Compounds against NSP13 showed binding affinities between -10 and -5.9Â kcal/mol whereby ivermectin and scutellarein showed highest binding energies of -10 and -9.9Â kcal/mol. Docking of 18 hit compounds against NSP16 yielded binding affinities between -8.9 and -4.1Â kcal/mol. Hamamelitannin and deacyltunicamycin were the top compounds with binding affinities of -8.9Â kcal/mol and -8.4Â kcal/mol. The top compounds showed stable ligand-protein interactions in molecular dynamics simulation. The analyses revealed two hit compounds against each targeted protein displaying stable behavior, high binding affinity and molecular interactions. Conversion of these compounds into drugs after in vitro experimentation can become better treatment options to elevate COVID management.
Targeting SARS-CoV-2 non-structural protein 13 via helicase-inhibitor-repurposing and non-structural protein 16 through pharmacophore-based screening.
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作者:Samdani Md Nazmus, Morshed Niaz, Reza Rumman, Asaduzzaman Muhammad, Islam Abul Bashar Mir Md Khademul
| 期刊: | Molecular Diversity | 影响因子: | 3.800 |
| 时间: | 2023 | 起止号: | 2023 Jun;27(3):1067-1085 |
| doi: | 10.1007/s11030-022-10468-8 | ||
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