Probing Transmembrane Proteins Binding Domain via Multi-level Molecule Learning

The study of transmembrane proteins (TMPs) and their binding activities holds significant importance in the pharmaceutical industry. Due to their physicochemical properties, known binding information regarding TMPs remains comparatively scarce and prevented researchers to dig information from known samples. However, research into general binding structure basis can circumvent this barrier and provide more mechanism insights, which we previously demonstrated its existence and named it as TMPs binding Domain. In this study, we try to discover the TMPs binding domain more precisely. Through atomic-level heterogenous graph convolutions, we significantly improved the classification performance of binding domains. This lays the algorithmic groundwork for utilizing binding domains in the study of TMPs binding activities and further boost the drug target research or new drug development.