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  • The full spectrum of SLC22 ...
    Yee, Sook Wah; Macdonald, Christian B.; Mitrovic, Darko; Zhou, Xujia; Koleske, Megan L.; Yang, Jia; Buitrago Silva, Dina; Rockefeller Grimes, Patrick; Trinidad, Donovan D.; More, Swati S.; Kachuri, Linda; Witte, John S.; Delemotte, Lucie; Giacomini, Kathleen M.; Coyote-Maestas, Willow

    Molecular cell, 05/2024, Letnik: 84, Številka: 10
    Journal Article

    Mutations in transporters can impact an individual’s response to drugs and cause many diseases. Few variants in transporters have been evaluated for their functional impact. Here, we combine saturation mutagenesis and multi-phenotypic screening to dissect the impact of 11,213 missense single-amino-acid deletions, and synonymous variants across the 554 residues of OCT1, a key liver xenobiotic transporter. By quantifying in parallel expression and substrate uptake, we find that most variants exert their primary effect on protein abundance, a phenotype not commonly measured alongside function. Using our mutagenesis results combined with structure prediction and molecular dynamic simulations, we develop accurate structure-function models of the entire transport cycle, providing biophysical characterization of all known and possible human OCT1 polymorphisms. This work provides a complete functional map of OCT1 variants along with a framework for integrating functional genomics, biophysical modeling, and human genetics to predict variant effects on disease and drug efficacy. Display omitted •Deep mutational scan of OCT1 reveals the determinants of biogenesis and substrate uptake•Discovery of a conserved motif, the stability helix, essential to SLC22 biogenesis•AI structure prediction and mutational data for accurate structure-function modeling•Integrating genomic-health records reveals variants effect on human physiology Yee et al. create a complete functional map of how genetic variants in the OCT1 transporter alter biogenesis and substrate uptake. This work provides a framework for biophysically informed precision medicine by integrating functional genomics, mechanistic modeling, and human genetics to predict variant effects on disease and drug efficacy.