Computational Analysis of Novel Drug
Opportunities (CANDO) 

Ram Samudrara

The University of Washington

 We have a developed a novel and unique computational multitarget fragment-based docking with dynamics protocol to implement a comprehensive and efficient drug discovery pipeline with higher efficiency, lowered cost, and increased success rates, compared with current approaches. We are applying this pipeline to evaluate how all approved drugs bind to all known disease target protein structures. The top ranked predictions are then immediately and directly verified in human clinical studies, sometimes with only a minimal amount of in vitro sanity checks. Our goal is to identify and repurpose the entire repertoire of known drugs as new therapies with an emphasis on underserved diseases. The project represents an integration of our group's applied research on therapeutic discovery, building upon basic protein and proteome structure, function, and interaction prediction research. In addition to repurposing drugs, our compound-structure matrix will provide an atomic level mechanistic understanding of how all known drugs interact with all their targets, antitargets, and offtargets, as well as entire pathways and organisms, to cause their desired (and undesired) effects.  The talk will focus on the breaking research being generated by the Computational Analysis of Novel Drug Opportunities (CANDO) drug discovery pipeline, which is funded in part by a 2010 NIH Director’ s Pioneer Award. Further information and details are available from the project web site located at (cando.compbio.washington.edu).