Drugsniffer: An Open Source Workflow for Virtually Screening Billions of Molecules for Binding Affinity to Protein Targets.

Venkatraman, Vishwesh; Colligan, Thomas H; Lesica, George T; Olson, Daniel R; Gaiser, Jeremiah; Copeland, Conner J; Wheeler, Travis J; Roy, Amitava

Venkatraman, Vishwesh; Colligan, Thomas H; Lesica, George T; Olson, Daniel R; Gaiser, Jeremiah; Copeland, Conner J; Wheeler, Travis J; Roy, Amitava.

Afiliação

Venkatraman V; Department of Chemistry, Norwegian University of Science and Technology, Trondheim, Norway.
Colligan TH; Department of Computer Science, University of Montana, Missoula, MT, United States.
Lesica GT; Department of Computer Science, University of Montana, Missoula, MT, United States.
Olson DR; Department of Computer Science, University of Montana, Missoula, MT, United States.
Gaiser J; Department of Computer Science, University of Montana, Missoula, MT, United States.
Copeland CJ; Department of Computer Science, University of Montana, Missoula, MT, United States.
Wheeler TJ; Department of Computer Science, University of Montana, Missoula, MT, United States.
Roy A; Department of Computer Science, University of Montana, Missoula, MT, United States.

Front Pharmacol ; 13: 874746, 2022.

Article em En | MEDLINE | ID: mdl-35559261

Palavras-chave

SARS-C0V-2; computer aided drug design; de novo design; machine learning; protein-ligand docking; virtual screeening

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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Screening_studies Idioma: En Revista: Front Pharmacol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Noruega

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