Due to the time and cost of experimental High-Throughput Screening (HTS), a fast, inexpensive computational screening method with HTS accuracy has long been an elusive goal of computational chemistry. Protein-Family Virtual Screening (PFVS) is finally achieving this for kinases and several other protein families. Three PFVS methodologies achieve unprecedented speed and accuracy by including massive amounts of IC50 and structural data from previous kinase projects into quantitative models for each new kinase: the 2D �Profile-QSAR� meta-QSAR method, the Kinase-Kernel chemogenomic method, and the 3D Surrogate AutoShim docking method. Between the methods, billions of activity predictions have been made for millions of internal and commercial compounds on 1,000+ kinase assays, so initial kinase virtual screening is now a table lookup. The methods have been applied to 60 active Novartis projects, with external R2=0.35�0.8 and enrichments of 20X�100X, even for novel chemotypes, on par with experimental HTS. Profile-QSAR predicts selectivity and cellular activity with similar success. PFVS has recently been extended to non-kinase adenosine-binding proteins, GPCRs, P450s, and to serine and cysteine proteases, in all now covering half of the estimated druggable genome. The methodologies will be briefly described and kinase virtual screening case studies will be presented from all stages of drug discovery, with an emphasis on identification of potent, selective, cell-penetrating tool compounds for rapid target (de)validation.

Protein-family virtual screening (PFVS) with accuracy comparable to experimental HTS: Tool compounds and leads for selective kinase inhibitors

248th National Meeting (2014)

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