Connecting Small Molecules with Similar Assay Performance Profiles Leads to New Biological Hypotheses.
High-throughput screening allows rapid identification of new candidate compounds for biological probe or drug development. Here, we describe a principled method to generate "assay performance profiles" for individual compounds that can serve as a basis for similarity searches and cluster analyses. Our method overcomes three challenges associated with generating robust assay performance profiles: (1) we transform data, allowing us to build profiles from assays having diverse dynamic ranges and variability; (2) we apply appropriate mathematical principles to handle missing data; and (3) we mitigate the fact that loss-of-signal assay measurements may not distinguish between multiple mechanisms that can lead to certain phenotypes (e.g., cell death). Our method connected compounds with similar mechanisms of action, enabling prediction of new targets and mechanisms both for known bioactives and for compounds emerging from new screens. Furthermore, we used Bayesian modeling of promiscuous compounds to distinguish between broadly bioactive and narrowly bioactive compound communities. Several examples illustrate the utility of our method to support mechanism-of-action studies in probe development and target identification projects.
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA Mathematical Institute of the Slovak Academy of Sciences, Košice, Slovakia (on leave).
Vlado
V
Dančík
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Hyman
H
Carrel
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Nicole E
NE
Bodycombe
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA Champlain College, Division of Information Technology & Sciences, Burlington, VT, USA.
Kathleen Petri
KP
Seiler
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Dina
D
Fomina-Yadlin
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA CeMM Research Center for Molecular Medicine, Vienna, Austria.
Stefan T
ST
Kubicek
Cancer Program, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Kimberly
K
Hartwell
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Alykhan F
AF
Shamji
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Bridget K
BK
Wagner
Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA, USA pclemons@broadinstitute.org.
Paul A
PA
Clemons
D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D004353:Drug Evaluation, Preclinical / Q000379:methods*; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D053078:Membrane Potential, Mitochondrial; D051379:Mice; D008958:Models, Molecular; D010641:Phenotype; D015203:Reproducibility of Results; D054852:Small Molecule Libraries / Q000737:chemistry*
D054852:Small Molecule Libraries
high-throughput screening; mechanism of action; small-molecule profiling; target identification