De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles.

ABSTRACT: A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, and transducing binding events into signals is challenging. Here we describe an integrated deep learning and energy based approach for designing high shape complementarity binders to small molecules that are poised for downstream sensing applications. We employ deep learning generated psuedocycles with repeating structural units surrounding central pockets; depending on the geometry of the structural unit and repeat number, these pockets span wide ranges of sizes and shapes. For a small molecule target of interest, we extensively sample hi

SUBMITTER: An L 

PROVIDER: S-EPMC10769206 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature