Webinar: Massively Parallel SPR Based Fragment Screening on Ligand Arrays

Download Poster: Massively Parallel SPR-Based Fragment Screening of Kinase Arrays

Abstract: The era of proteomics and big data has paved the way for efficient utilization of higher-throughput and more expansive experimental characterization of biomolecular interactions. Drug discovery increasingly seeks to understand the interactions of hit- and lead-like molecules in context of the greater biological milieu in which pharmacological effects are sought.  In practice lead-generation methodologies are constrained to screen one or a few targets at a time and enable hit-to-lead activities with a limited set of off-target/mutant paneling in-house or through CROs.  We propose that ligand-array biosensors can allow for testing interactions of compounds against up to hundreds of proteins at a time allowing for broad paneling using very little reagent and generating very precise differences between on/off targets, mutants, homologs, post-translationally modifications, etc.  SPR -based direct-binding assays do not require counterscreens for assay interference further speeding data interpretation.  In one case a screen of the Maybridge fragment library against a panel of off-the-shelf biotinylated kinases resulted in ~125,000 fragment/protein interactions to be collected in 3 days.  Another screen of 96 unique proteins against an ~3500 compound library resulted in ~320,000 interactions in 11 days.  Datasets of this type allow for the simultaneous assessment of selectivity, specificity, and ligandability.  Use through hit-to-lead activities will provide broader information to enable medicinal chemistry, pathway profiling, and earlier indications of off-target engagement.

Speaker:
Anthony Giannetti, PhD, Associate Director, Applications, Carterra
Tony has more than two decades of experience in SPR, biophysics, and structural biology, specializing in fragment-based lead discovery, small molecule drug design, and platform development at Roche, Genentech, and Google[X]/Verily.