Genomic sequencing has revealed vast numbers of human protein variants, offering transformative potential for disease research and therapy. Realizing this potential requires robust, quantitative functional data at scale to advance from observational associations to mechanistic understanding. Using high-throughput microfluidic enzyme kinetics (HT-MEK), we profiled 190 clinical variants of the protein tyrosine phosphatase SHP2, a driver of developmental disorders and cancers, across multiple biochemical parameters including catalytic activity, autoinhibition, stability, activator sensitivity, and drug response. Over 300,000 assays generated an unprecedented functional atlas, revealing functional alteration by each mutation, predictive biochemical signatures for diseases, and variant-specific therapeutic vulnerabilities. Integrating these quantitative parameters with drug response profiles uncovered unexpected patterns of inhibitor sensitivity and enabled refinement of the allosteric inhibition mechanism. The refined model accurately predicts inhibitory behavior and guides strategies to enhance drug efficacy. Our scalable approach establishes a general framework to elucidate how protein variants drive disease processes and shape therapeutic responses, with broad implications for protein biochemistry, precision medicine, and chemical biology.
Lee et al. (2026) studied this question.