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Surely you are joking, Mr Docking!
Gentile, F; Oprea, T I; Tropsha, A; Cherkasov, A.
  • Gentile F; Department of Chemistry and Biomolecular Sciences, University of Ottawa, Ottawa, ON, Canada.
  • Oprea TI; Roivant Sciences Inc, 451 D Street, Boston, MA, USA.
  • Tropsha A; Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA.
  • Cherkasov A; Vancouver Prostate Centre, Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada. acherkasov@prostatecentre.com.
Chem Soc Rev ; 52(3): 872-878, 2023 Feb 06.
Article in English | MEDLINE | ID: covidwho-2230297
ABSTRACT
In the wake of recent COVID-19 pandemics scientists around the world rushed to deliver numerous CADD (Computer-Aided Drug Discovery) methods and tools that could be reliably used to discover novel drug candidates against the SARS-CoV-2 virus. With that, there emerged a trend of a significant democratization of CADD that contributed to the rapid development of various COVID-19 drug candidates currently undergoing different stages of validation. On the other hand, this democratization also inadvertently led to the surge rapidly performed molecular docking studies to nominate multiple scores of novel drug candidates supported by computational arguments only. Albeit driven by best intentions, most of such studies also did not follow best practices in the field that require experience and expertise learned through multiple rigorously designed benchmarking studies and rigorous experimental validation. In this Viewpoint we reflect on recent disbalance between small number of rigorous and comprehensive studies and the proliferation of purely computational studies enabled by the ease of docking software availability. We further elaborate on the hyped oversale of CADD methods' ability to rapidly yield viable drug candidates and reiterate the critical importance of rigor and adherence to the best practices of CADD in view of recent emergence of AI and Big Data in the field.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Drug Design / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Chem Soc Rev Year: 2023 Document Type: Article Affiliation country: D2cs00948j

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Drug Design / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: Chem Soc Rev Year: 2023 Document Type: Article Affiliation country: D2cs00948j