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Novel inhibitors to ADP ribose phosphatase of SARS-CoV-2 identified by structure-based high throughput virtual screening and molecular dynamics simulations.
Patel, Dhrumi C; Hausman, Katherine R; Arba, Muhammad; Tran, Annie; Lakernick, Phillip M; Wu, Chun.
  • Patel DC; Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, NJ, 08028, United States.
  • Hausman KR; Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, NJ, 08028, United States.
  • Arba M; Faculty of Pharmacy, Universitas Halu Oleo, Kendari, 93232, Indonesia.
  • Tran A; Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, NJ, 08028, United States.
  • Lakernick PM; Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, NJ, 08028, United States.
  • Wu C; Department of Molecular & Cellular Biosciences, College of Science and Mathematics, Rowan University, Glassboro, NJ, 08028, United States. Electronic address: wuc@rowan.edu.
Comput Biol Med ; 140: 105084, 2021 Nov 30.
Article in English | MEDLINE | ID: covidwho-2158639
ABSTRACT
The outbreak of a new coronavirus (SARS-CoV-2) was first identified in Wuhan, People's Republic of China, in 2019, which has led to a severe, life-threatening form of pneumonia (COVID-19). Research scientists all around the world have been trying to find small molecule drugs to treat COVID-19. In the present study, a conserved macrodomain, ADP Ribose phosphatase (ADRP), of a critical non-structural protein (Nsp3) in all coronaviruses was probed using large-scale Molecular Dynamics (MD) simulations to identify novel inhibitors. In our virtual screening workflow, the recently-solved X-ray complex structure, 6W6Y, with a substrate-mimics was used to screen 17 million ZINC15 compounds using drug property filters and Glide docking scores. The top twenty output compounds each underwent 200 ns MD simulations (i.e. 20 × 200 ns) to validate their individual stability as potential inhibitors. Eight out of the twenty compounds showed stable binding modes in the MD simulations, as well as favorable drug properties from our predctions. Therefore, our computational data suggest that the resulting top eight out of twenty compounds could potentially be novel inhibitors to ADRP of SARS-CoV-2.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Comput Biol Med Year: 2021 Document Type: Article Affiliation country: J.compbiomed.2021.105084

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Comput Biol Med Year: 2021 Document Type: Article Affiliation country: J.compbiomed.2021.105084