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• W4386304573 abstract "Target deconvolution is a crucial but costly and time-consuming task that hinders large-scale profiling for drug discovery. We present a matrix-augmented pooling strategy (MAPS) which mixes multiple drugs into samples with optimized permutation and delineates targets of each drug simultaneously with mathematical processing. We validated this strategy with thermal proteome profiling (TPP) testing of 15 drugs concurrently, increasing experimental throughput by 60x while maintaining high sensitivity and specificity. Benefiting from the lower cost and higher throughput of MAPS, we performed target deconvolution of the 15 drugs across 5 cell lines. Our profiling revealed that drug-target interactions can differ vastly in targets and binding affinity across cell lines. We further validated BRAF and CSNK2A2 as potential off-targets of bafetinib and abemaciclib, respectively. This work represents the largest thermal profiling of structurally diverse drugs across multiple cell lines to date." @default.
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• W4386304573 date "2023-08-01" @default.
• W4386304573 modified "2023-09-29" @default.
• W4386304573 title "Target deconvolution with matrix-augmented pooling strategy reveals cell-specific drug-protein interactions" @default.
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• W4386304573 doi "https://doi.org/10.1016/j.chembiol.2023.08.002" @default.
• W4386304573 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37652024" @default.
• W4386304573 hasPublicationYear "2023" @default.
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