Paliwal, K.K. and Sharma, Alokanand and Lyons, J. and Dehzangi, A. (2014) Improving protein fold recognition using the amalgamation of evolutionary-based and structural-based information. BMC Bioinformatics, 15 (16). pp. 1-9. ISSN 1471-2105
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Abstract
Deciphering three dimensional structure of a protein sequence is a challenging task in biological science. Protein
fold recognition and protein secondary structure prediction are transitional steps in identifying the three
dimensional structure of a protein. For protein fold recognition, evolutionary-based information of amino acid
sequences from the position specific scoring matrix (PSSM) has been recently applied with improved results. On
the other hand, the SPINE-X predictor has been developed and applied for protein secondary structure prediction.
Several reported methods for protein fold recognition have only limited accuracy. In this paper, we have
developed a strategy of combining evolutionary-based information (from PSSM) and predicted secondary structure
using SPINE-X to improve protein fold recognition. The strategy is based on finding the probabilities of amino acid
pairs (AAP). The proposed method has been tested on several protein benchmark datasets and an improvement of
8.9% recognition accuracy has been achieved. We have achieved, for the first time over 90% and 75% prediction
accuracies for sequence similarity values below 40% and 25%, respectively. We also obtain 90.6% and 77.0%
prediction accuracies, respectively, for the Extended Ding and Dubchak and Taguchi and Gromiha benchmark
protein fold recognition datasets widely used for in the literature.
Item Type: | Journal Article |
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Subjects: | Q Science > QC Physics T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics |
Depositing User: | Repo Editor |
Date Deposited: | 05 Mar 2015 22:01 |
Last Modified: | 22 Sep 2016 04:43 |
URI: | https://repository.usp.ac.fj/id/eprint/8010 |
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