title: CANDO and the infinite drug discovery frontier.
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.
authors: University of Washington, Department of Bioengineering, Seattle, WA 98109, United States.
authors: Mark
authors: M
authors: Minie
authors: University of Washington, Department of Microbiology, Seattle, WA 98109, United States; University of California, San Francisco, Diabetes Center, San Francisco, CA 94143, United States.
authors: Gaurav
authors: G
authors: Chopra
authors: University of Washington, Department of Microbiology, Seattle, WA 98109, United States.
authors: Geetika
authors: G
authors: Sethi
authors: University of California, School of Medicine, San Francisco, CA 94143, United States.
authors: Jeremy
authors: J
authors: Horst
authors: University of Washington, Department of Microbiology, Seattle, WA 98109, United States.
authors: George
authors: G
authors: White
authors: Georgia Institute of Technology, Center for the Study of Systems Biology, Atlanta, GA 30318, United States.
authors: Ambrish
authors: A
authors: Roy
authors: Molecular Biophysics Unit, Indian Institute of Science Bangalore, 560012, India.
authors: Kaushik
authors: K
authors: Hatti
authors: University of Washington, Department of Microbiology, Seattle, WA 98109, United States. Electronic address: ram@compbio.org.
authors: Ram
authors: R
authors: Samudrala
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods*; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D058492:Drug Repositioning; D006801:Humans; D008962:Models, Theoretical; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000378:metabolism*; D020543:Proteome
chemical_list: D011506:Proteins; D020543:Proteome