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CANDO and the infinite drug discovery frontier.
Minie, Mark; Chopra, Gaurav; Sethi, Geetika; Horst, Jeremy; White, George; Roy, Ambrish; Hatti, Kaushik; Samudrala, Ram.
Afiliación
  • Minie M; University of Washington, Department of Bioengineering, Seattle, WA 98109, United States.
  • Chopra G; University of Washington, Department of Microbiology, Seattle, WA 98109, United States; University of California, San Francisco, Diabetes Center, San Francisco, CA 94143, United States.
  • Sethi G; University of Washington, Department of Microbiology, Seattle, WA 98109, United States.
  • Horst J; University of California, School of Medicine, San Francisco, CA 94143, United States.
  • White G; University of Washington, Department of Microbiology, Seattle, WA 98109, United States.
  • Roy A; Georgia Institute of Technology, Center for the Study of Systems Biology, Atlanta, GA 30318, United States.
  • Hatti K; Molecular Biophysics Unit, Indian Institute of Science Bangalore, 560012, India.
  • Samudrala R; University of Washington, Department of Microbiology, Seattle, WA 98109, United States. Electronic address: ram@compbio.org.
Drug Discov Today ; 19(9): 1353-63, 2014 Sep.
Article en En | MEDLINE | ID: mdl-24980786
ABSTRACT
The Computational Analysis of Novel Drug Opportunities (CANDO) platform (http//protinfo.org/cando) uses similarity of compound-proteome interaction signatures to infer homology of compound/drug behavior. We constructed interaction signatures for 3733 human ingestible compounds covering 48,278 protein structures mapping to 2030 indications based on basic science methodologies to predict and analyze protein structure, function, and interactions developed by us and others. Our signature comparison and ranking approach yielded benchmarking accuracies of 12-25% for 1439 indications with at least two approved compounds. We prospectively validated 49/82 'high value' predictions from nine studies covering seven indications, with comparable or better activity to existing drugs, which serve as novel repurposed therapeutics. Our approach may be generalized to compounds beyond those approved by the FDA, and can also consider mutations in protein structures to enable personalization. Our platform provides a holistic multiscale modeling framework of complex atomic, molecular, and physiological systems with broader applications in medicine and engineering.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Biología Computacional / Descubrimiento de Drogas Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Drug Discov Today Asunto de la revista: FARMACOLOGIA / TERAPIA POR MEDICAMENTOS Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Proteínas / Biología Computacional / Descubrimiento de Drogas Tipo de estudio: Prognostic_studies Límite: Animals / Humans Idioma: En Revista: Drug Discov Today Asunto de la revista: FARMACOLOGIA / TERAPIA POR MEDICAMENTOS Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos
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