USP Electronic Research Repository

SucStruct: prediction of succinylated lysine residues by using structural properties of amino acids

López, Y. and Dehzangi, A. and Lal, S.P. and Taherzadeh, G. and Michaelson, J. and Sattar, A. and Tsunoda, T. and Sharma, Alokanand (2017) SucStruct: prediction of succinylated lysine residues by using structural properties of amino acids. Analytical Biochemistry, 527 . pp. 24-32. ISSN ‎0003-2697

Full text not available from this repository. (Request a copy)

Abstract

Post-Translational Modification (PTM) is a biological reaction which contributes to diversify the proteome. Despite many modifications with important roles in cellular activity, lysine succinylation has recently emerged as an important PTM mark. It alters the chemical structure of lysines, leading to remarkable changes in the structure and function of proteins. In contrast to the huge amount of proteins being sequenced in the post-genome era, the experimental detection of succinylated residues remains expensive, inefficient and time-consuming. Therefore, the development of computational tools for accurately predicting succinylated lysines is an urgent necessity. To date, several approaches have been proposed but their sensitivity has been reportedly poor. In this paper, we propose an approach that utilizes structural features of amino acids to improve lysine succinylation prediction. Succinylated and non-succinylated lysines were first retrieved from 670 proteins and characteristics such as accessible surface area, backbone torsion angles and local structure conformations were incorporated. We used the k-nearest neighbors cleaning treatment for dealing with class imbalance and designed a pruned decision tree for classification. Our predictor, referred to as SucStruct (Succinylation using Structural features), proved to significantly improve performance when compared to previous predictors, with sensitivity, accuracy and Mathew's correlation coefficient equal to 0.7334-0.7946, 0.7444-0.7608 and 0.4884-0.5240, respectively.

Item Type: Journal Article
Uncontrolled Keywords: Amino acids; Lysine succinylation; Prediction; Protein sequences; Structural features
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
Depositing User: USP RSC Assistant
Date Deposited: 15 Jan 2018 03:47
Last Modified: 15 Jan 2018 03:47
URI: https://repository.usp.ac.fj/id/eprint/10512

Actions (login required)

View Item View Item