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CANDO and the infinite drug discovery frontier

  • Mark Minie
  • , Gaurav Chopra
  • , Geetika Sethi
  • , Jeremy Horst
  • , George White
  • , Ambrish Roy
  • , Kaushik Hatti
  • , Ram Samudrala
  • University of Washington
  • University of California at San Francisco
  • Georgia Institute of Technology
  • Indian Institute of Science Bangalore

Research output: Contribution to journal › Review article › peer-review

64 Scopus citations

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.

Original languageEnglish
Pages (from-to)1353-1363
Number of pages11
JournalDrug Discovery Today
Volume19
Issue number9
DOIs
StatePublished - Sep 2014

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