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In silico platform for predicting and initiating β-turns in a protein at desired locations.

DIR@IMTECH: CSIR-Institute of Microbial Technology

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Title In silico platform for predicting and initiating β-turns in a protein at desired locations.
 
Creator Singh, Harinder
Singh, Sandeep
Raghava, G.P.S.
 
Subject QR Microbiology
 
Description Numerous studies have been performed for analysis and prediction of β-turns in a protein. This study focuses on analyzing, predicting, and designing of β-turns to understand the preference of amino acids in β-turn formation. We analyzed around 20,000 PDB chains to understand the preference of residues or pair of residues at different positions in β-turns. Based on the results, a propensity-based method has been developed for predicting β-turns with an accuracy of 82%. We introduced a new approach entitled "Turn level prediction method," which predicts the complete β-turn rather than focusing on the residues in a β-turn. Finally, we developed BetaTPred3, a Random forest based method for predicting β-turns by utilizing various features of four residues present in β-turns. The BetaTPred3 achieved an accuracy of 79% with 0.51 MCC that is comparable or better than existing methods on BT426 dataset. Additionally, models were developed to predict β-turn types with better performance than other methods available in the literature. In order to improve the quality of prediction of turns, we developed prediction models on a large and latest dataset of 6376 nonredundant protein chains. Based on this study, a web server has been developed for prediction of β-turns and their types in proteins. This web server also predicts minimum number of mutations required to initiate or break a β-turn in a protein at specified location of a protein.
 
Publisher Wiley
 
Date 2015-05
 
Type Article
PeerReviewed
 
Relation http://onlinelibrary.wiley.com/doi/10.1002/prot.24783/epdf
http://crdd.osdd.net/open/1658/
 
Identifier Singh, Harinder and Singh, Sandeep and Raghava, G.P.S. (2015) In silico platform for predicting and initiating β-turns in a protein at desired locations. Proteins, 83 (5). pp. 910-21. ISSN 1097-0134