Deep Local Analysis deconstructs protein-protein interfaces and accurately estimates binding affinity changes upon mutation.

ABSTRACT:

Motivation

The spectacular recent advances in protein and protein complex structure prediction hold promise for reconstructing interactomes at large-scale and residue resolution. Beyond determining the 3D arrangement of interacting partners, modeling approaches should be able to unravel the impact of sequence variations on the strength of the association.

Results

In this work, we report on Deep Local Analysis, a novel and efficient deep learning framework that relies on a strikingly simple deconstruction of protein interfaces into small locally oriented residue-centered cubes and on 3D convolutions recognizing patterns within cubes. Merely based on the two cubes associated with the wild-type and the mutant residues, DLA accurately estimates the binding affinity change for th

SUBMITTER: Mohseni Behbahani Y 

PROVIDER: S-EPMC10311296 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature