Deep Local Analysis evaluates protein docking conformations with locally oriented cubes.

ABSTRACT:

Motivation

With the recent advances in protein 3D structure prediction, protein interactions are becoming more central than ever before. Here, we address the problem of determining how proteins interact with one another. More specifically, we investigate the possibility of discriminating near-native protein complex conformations from incorrect ones by exploiting local environments around interfacial residues.

Results

Deep Local Analysis (DLA)-Ranker is a deep learning framework applying 3D convolutions to a set of locally oriented cubes representing the protein interface. It explicitly considers the local geometry of the interfacial residues along with their neighboring atoms and the regions of the interface with different solvent accessibility. We assessed its performance o

SUBMITTER: Mohseni Behbahani Y 

PROVIDER: S-EPMC9525006 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature