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Evaluation of protein dihedral angle prediction methods.

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title Evaluation of protein dihedral angle prediction methods.
 
Creator Singh, Harinder
Singh, Sandeep
Raghava, G.P.S.
 
Description Tertiary structure prediction of a protein from its amino acid sequence is one of the major challenges in the field of bioinformatics. Hierarchical approach is one of the persuasive techniques used for predicting protein tertiary structure, especially in the absence of homologous protein structures. In hierarchical approach, intermediate states are predicted like secondary structure, dihedral angles, Cα-Cα distance bounds, etc. These intermediate states are used to restraint the protein backbone and assist its correct folding. In the recent years, several methods have been developed for predicting dihedral angles of a protein, but it is difficult to conclude which method is better than others. In this study, we benchmarked the performance of dihedral prediction methods ANGLOR and SPINE X on various datasets, including independent datasets. TANGLE dihedral prediction method was not benchmarked (due to unavailability of its standalone) and was compared with SPINE X and ANGLOR on only ANGLOR dataset on which TANGLE has reported its results. It was observed that SPINE X performed better than ANGLOR and TANGLE, especially in case of prediction of dihedral angles of glycine and proline residues. The analysis suggested that angle shifting was the foremost reason of better performance of SPINE X. We further evaluated the performance of the methods on independent ccPDB30 dataset and observed that SPINE X performed better than ANGLOR.
 
Publisher San Francisco, CA : Public Library of Science
 
Date 2014
 
Type Article
PeerReviewed
 
Relation http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0105667
http://crdd.osdd.net/open/1567/
 
Identifier Singh, Harinder and Singh, Sandeep and Raghava, G.P.S. (2014) Evaluation of protein dihedral angle prediction methods. PloS one, 9 (8). e105667. ISSN 1932-6203