FUpred: detecting protein domains through deep-learning-based contact map prediction.

ABSTRACT:

Motivation

Protein domains are subunits that can fold and function independently. Correct domain boundary assignment is thus a critical step toward accurate protein structure and function analyses. There is, however, no efficient algorithm available for accurate domain prediction from sequence. The problem is particularly challenging for proteins with discontinuous domains, which consist of domain segments that are separated along the sequence.

Results

We developed a new algorithm, FUpred, which predicts protein domain boundaries utilizing contact maps created by deep residual neural networks coupled with coevolutionary precision matrices. The core idea of the algorithm is to retrieve domain boundary locations by maximizing the number of intra-domain contacts, while minimizi

SUBMITTER: Zheng W 

PROVIDER: S-EPMC7320627 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature