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
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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.
Item Type: | Article |
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Additional Information: | Copyright of this article belongs to Wiley Online Library. |
Uncontrolled Keywords: | analysis of beta turn residue; beta turn prediction; beta turn type prediction; designing of beta turn; statistical based beta turn prediction |
Subjects: | Q Science > QR Microbiology |
Depositing User: | Dr. K.P.S.Sengar |
Date Deposited: | 11 Jul 2015 05:32 |
Last Modified: | 11 Jul 2015 05:32 |
URI: | http://crdd.osdd.net/open/id/eprint/1658 |
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