TMPs Interaction Domain: A Discovery of Structural Universality Among TMPs Interaction Sites Using Deep Learning Method

Abstract

Transmembrane proteins (TMPs) serve as important drug targets and accounts for nearly half of the drugs currently available in the market. Research into TMPs interactions and their structural basis will provide key information for drug research and new drug development. Based on previous works like a binding pocket or binding site, our main purpose in this study is to find whether the structural universality (Interaction Domain) exists in all kinds of TMPs interaction regions through a computational approach. After implementing the experiments using our 3D deep learning model and achieve the Matthews correlation coefficient (MCC) of 0.36, we found strong evidence for the existence of the structural basis among TMPs interaction regions. That means those regions, or we call them interaction domains, are structural specific distinguishing to the domains without any interaction. According to this, this work provides a new theoretical basis for TMPs interaction research and can greatly boost the development of the drug industry.