DeepConPred2: An Improved Method for the Prediction of Protein Residue Contacts.

Content Provider	Europe PMC
Author	Ding, Wenze Mao, Wenzhi Shao, Di Zhang, Wenxuan Gong, Haipeng
Copyright Year	2018
Abstract	Information of residue-residue contacts is essential for understanding the mechanism of protein folding, and has been successfully applied as special topological restraints to simplify the conformational sampling in de novo protein structure prediction. Prediction of protein residue contacts has experienced amazingly rapid progresses recently, with prediction accuracy approaching impressively high levels in the past two years. In this work, we introduce a second version of our residue contact predictor, DeepConPred2, which exhibits substantially improved performance and sufficiently reduced running time after model re-optimization and feature updates. When testing on the CASP12 free modeling targets, our program reaches at least the same level of prediction accuracy as the best contact predictors so far and provides information complementary to other state-of-the-art methods in contact-assisted folding.
Journal	Computational and Structural Biotechnology Journal
Volume Number	16
PubMed Central reference number	PMC6247404
PubMed reference number	30505403
e-ISSN	20010370
DOI	10.1016/j.csbj.2018.10.009
Language	English
Publisher	Research Network of Computational and Structural Biotechnology
Publisher Date	2018-11-10
Access Restriction	Open
Rights License	This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). © 2018 The Authors
Subject Keyword	Residue contact prediction Web server Protein structure prediction Contact-assisted folding Machine learning
Content Type	Text
Resource Type	Article
Subject	Biochemistry Genetics Biophysics Biotechnology Structural Biology Computer Science Applications