DeepConPred2: An Improved Method for the Prediction of Protein Residue Contacts
| Autor: | Wenzhi Mao, Wenze Ding, Wenxuan Zhang, Haipeng Gong, Di Shao |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Computer science lcsh:Biotechnology Biophysics Improved method Biochemistry 03 medical and health sciences Structural Biology lcsh:TP248.13-248.65 Web server Machine learning Genetics Conformational sampling Residue contact prediction Residue (complex analysis) Protein structure prediction Short Review Computer Science Applications Running time Improved performance 030104 developmental biology De novo protein structure prediction Protein folding Contact-assisted folding Algorithm Biotechnology |
| Zdroj: | Computational and Structural Biotechnology Journal Computational and Structural Biotechnology Journal, Vol 16, Iss, Pp 503-510 (2018) |
| ISSN: | 2001-0370 |
| Popis: | 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. Keywords: Residue contact prediction, Web server, Protein structure prediction, Contact-assisted folding, Machine learning |
| Databáze: | OpenAIRE |
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