CATHER: a novel threading algorithm with predicted contacts
| Autor: | Zhenling Peng, Zongyang Du, Jianyi Yang, Qi Wu, Shuo Pan |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
0303 health sciences Computer science Protein contact map 030302 biochemistry & molecular biology Computational Biology Proteins Protein structure prediction Biochemistry Computer Science Applications 03 medical and health sciences Computational Mathematics Computational Theory and Mathematics Sequence Analysis Protein Threading (protein sequence) Molecular Biology Algorithm Algorithms Software 030304 developmental biology |
| Zdroj: | Bioinformatics. 36:2119-2125 |
| ISSN: | 1460-2059 1367-4803 |
| DOI: | 10.1093/bioinformatics/btz876 |
| Popis: | MotivationThreading is one of the most effective methods for protein structure prediction. In recent years, the increasing accuracy in protein contact map prediction opens a new avenue to improve the performance of threading algorithms. Several preliminary studies suggest that with predicted contacts, the performance of threading algorithms can be improved greatly. There is still much room to explore to make better use of predicted contacts.ResultsWe have developed a new contact-assisted threading algorithm named CATHER using both conventional sequential profiles and contact map predicted by a deep learning-based algorithm. Benchmark tests on an independent test set and the CASP12 targets demonstrated that CATHER made significant improvement over other methods which only use either sequential profile or predicted contact map. Our method was ranked at the Top 10 among all 39 participated server groups on the 32 free modeling targets in the blind tests of the CASP13 experiment. These data suggest that it is promising to push forward the threading algorithms by using predicted contacts.Availability and implementationhttp://yanglab.nankai.edu.cn/CATHER/.Supplementary informationSupplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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