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Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking.
Ibrahim, Tamer M; Ismail, Muhammad I; Bauer, Matthias R; Bekhit, Adnan A; Boeckler, Frank M.
  • Ibrahim TM; Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Kafrelsheikh University, Kafrelsheikh, Egypt.
  • Ismail MI; Department of Pharmaceutical Chemistry, Faculty of Pharmacy, The British University in Egypt, Cairo, Egypt.
  • Bauer MR; Structure, Biophysics and Fragment-Based Lead Generation, Discovery Sciences, R&D, AstraZeneca, Cambridge, United Kingdom.
  • Bekhit AA; Department of Pharmacy, Eberhard-Karls University, Tuebingen, Germany.
  • Boeckler FM; Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Alexandria University, Alexandria, Egypt.
Front Chem ; 8: 592289, 2020.
Article in English | MEDLINE | ID: covidwho-945632
ABSTRACT
The coronavirus disease 19 (COVID-19) is a rapidly growing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its papain-like protease (SARS-CoV-2 PLpro) is a crucial target to halt virus replication. SARS-CoV PLpro and SARS-CoV-2 PLpro share an 82.9% sequence identity and a 100% sequence identity for the binding site reported to accommodate small molecules in SARS-CoV. The flexible key binding site residues Tyr269 and Gln270 for small-molecule recognition in SARS-CoV PLpro exist also in SARS-CoV-2 PLpro. This inspired us to use the reported small-molecule binders to SARS-CoV PLpro to generate a high-quality DEKOIS 2.0 benchmark set. Accordingly, we used them in a cross-benchmarking study against SARS-CoV-2 PLpro. As there is no SARS-CoV-2 PLpro structure complexed with a small-molecule ligand publicly available at the time of manuscript submission, we built a homology model based on the ligand-bound SARS-CoV structure for benchmarking and docking purposes. Three publicly available docking tools FRED, AutoDock Vina, and PLANTS were benchmarked. All showed better-than-random performances, with FRED performing best against the built model. Detailed performance analysis via pROC-Chemotype plots showed a strong enrichment of the most potent bioactives in the early docking ranks. Cross-benchmarking against the X-ray structure complexed with a peptide-like inhibitor confirmed that FRED is the best-performing tool. Furthermore, we performed cross-benchmarking against the newly introduced X-ray structure complexed with a small-molecule ligand. Interestingly, its benchmarking profile and chemotype enrichment were comparable to the built model. Accordingly, we used FRED in a prospective virtual screen of the DrugBank database. In conclusion, this study provides an example of how to harness a custom-made DEKOIS 2.0 benchmark set as an approach to enhance the virtual screening success rate against a vital target of the rapidly emerging pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Front Chem Year: 2020 Document Type: Article Affiliation country: Fchem.2020.592289

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study / Randomized controlled trials Language: English Journal: Front Chem Year: 2020 Document Type: Article Affiliation country: Fchem.2020.592289