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dc.contributor.authorLopez, Yosvany
dc.contributor.authorDehzangi, Abdollah
dc.contributor.authorLal, Sunil Pranit
dc.contributor.authorTaherzadeh, Ghazaleh
dc.contributor.authorMichaelson, Jacob
dc.contributor.authorSattar, Abdul
dc.contributor.authorTsunoda, Tatsuhiko
dc.contributor.authorSharma, Alok
dc.date.accessioned2017-07-03T01:18:32Z
dc.date.available2017-07-03T01:18:32Z
dc.date.issued2017
dc.identifier.issn0003-2697
dc.identifier.doi10.1016/j.ab.2017.03.021
dc.identifier.urihttp://hdl.handle.net/10072/341147
dc.description.abstractPost-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.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofpagefrom24
dc.relation.ispartofpageto32
dc.relation.ispartofjournalAnalytical Biochemistry
dc.relation.ispartofvolume527
dc.subject.fieldofresearchBiochemistry and Cell Biology not elsewhere classified
dc.subject.fieldofresearchAnalytical Chemistry
dc.subject.fieldofresearchOther Chemical Sciences
dc.subject.fieldofresearchBiochemistry and Cell Biology
dc.subject.fieldofresearchcode060199
dc.subject.fieldofresearchcode0301
dc.subject.fieldofresearchcode0399
dc.subject.fieldofresearchcode0601
dc.titleSucStruct: Prediction of succinylated lysine residues by using structural properties of amino acids
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.hasfulltextNo Full Text
gro.griffith.authorSattar, Abdul
gro.griffith.authorSharma, Alok
gro.griffith.authorTaherzadeh, Ghazaleh


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