GeoBind: segmentation of nucleic acid binding interface on protein surface with geometric deep learning.

ABSTRACT: Unveiling the nucleic acid binding sites of a protein helps reveal its regulatory functions in vivo. Current methods encode protein sites from the handcrafted features of their local neighbors and recognize them via a classification, which are limited in expressive ability. Here, we present GeoBind, a geometric deep learning method for predicting nucleic binding sites on protein surface in a segmentation manner. GeoBind takes the whole point clouds of protein surface as input and learns the high-level representation based on the aggregation of their neighbors in local reference frames. Testing GeoBind on benchmark datasets, we demonstrate GeoBind is superior to state-of-the-art predictors. Specific case studies are performed to show the powerful ability of GeoBind to explore molecular surf

SUBMITTER: Li P 

PROVIDER: S-EPMC10250245 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature