Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary infomration from profile bigrams

Dehzangi, Abdollah and Lopez, Y. and Lal, Sunil and Taherzadeh, G. and Sattar, A. and Tsunoda, T. and Sharma, Alokanand (2018) Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary infomration from profile bigrams. PLoS One, 13 (2). pp. 1-16. ISSN 1932-6203

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Abstract

Post-translational modification refers to the biological mechanism involved in the enzymatic modification of proteins after being translated in the ribosome. This mechanism comprises a wide range of structural modifications, which bring dramatic variations to the biological function of proteins. One of the recently discovered modifications is succinylation. Although succinylation can be detected through mass spectrometry, its current experimental detection turns out to be a timely process unable to meet the exponential growth of sequenced proteins. Therefore, the implementation of fast and accurate computational methods has emerged as a feasible solution. This paper proposes a novel classification approach, which effectively incorporates the secondary structure and evolutionary information of proteins through profile bigrams for succinylation prediction. The proposed predictor, abbreviated as SSEvol-Suc, made use of the above features for training an AdaBoost classifier and consequently predicting succinylated lysine residues. When SSEvol-Suc was compared with four benchmark predictors, it outperformed them in metrics such as sensitivity (0.909), accuracy (0.875) and Matthews correlation coefficient (0.75)

Item Type:	Journal Article
Subjects:	Q Science > Q Science (General) T Technology > T Technology (General)
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User:	Alokanand Sharma
Date Deposited:	09 Jun 2018 02:26
Last Modified:	09 Jun 2018 02:26
URI:	https://repository.usp.ac.fj/id/eprint/10775

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