Enhanced prediction of protein functional identity through the integration of sequence and structural features.

ABSTRACT: Although over 300 million protein sequences are registered in a reference sequence database, only 0.2 % have experimentally determined functions. This suggests that many valuable proteins, potentially catalyzing novel enzymatic reactions, remain undiscovered among the vast number of function-unknown proteins. In this study, we developed a method to predict whether two proteins catalyze the same enzymatic reaction by analyzing sequence and structural similarities, utilizing structural models predicted by AlphaFold2. We performed pocket detection and domain decomposition for each structural model. The similarity between protein pairs was assessed using features such as full-length sequence similarity, domain structural similarity, and pocket similarity. We developed several models using conv

SUBMITTER: Fujita S 

PROVIDER: S-EPMC11609699 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature