Combining label-free cell phenotypic profiling with computational approaches for novel drug discovery.
BACKGROUND
Drug discovery is a long and costly process. Innovations and paradigm shifts are essential for continuous improvement in the productivity of pharmaceutical R&D.


METHODS
The author reviews the progress of label-free cell phenotypic and computational approaches in early drug discovery since 2004 and proposes a novel paradigm, which combines both approaches.


CONCLUSIONS
Label-free cell phenotypic profiling techniques offer an unprecedented and integrated approach to comprehend drug-target interactions in their native environments. However, these approaches have disadvantages associated with the lack of molecular details. Computational approaches, including ligand-, structure- and phenotype-based virtual screens, have become versatile tools in the early drug discovery process. However, these approaches mostly predict the binding of drug molecules to targets of interest and are limited to targets that are either well annotated for ligands or that are structurally resolved. Thus, combining label-free cell phenotypic profiling with computational approaches can provide a potential paradigm to accelerate novel drug discovery by taking advantages of the best of both approaches.
Corning Inc., Biochemical Technologies, Science and Technology Division , Corning, NY 14831 , USA fangy2@corning.com.
Ye
Y
Fang
D000818:Animals; D017076:Computer-Aided Design; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D004345:Drug Industry / Q000379:methods; D017598:Efficiency, Organizational; D006801:Humans; D008024:Ligands; D010641:Phenotype; D014584:User-Computer Interface
D008024:Ligands
chemical similarity; drug discovery; label-free cell phenotypic approach; ligand-based virtual screen; polypharmacology; structure-based virtual screen; text mining