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dc.contributor.authorHeffernan, Rhys
dc.contributor.authorDehzangi, Abdollah
dc.contributor.authorLyons, James
dc.contributor.authorPaliwal, Kuldip
dc.contributor.authorSharma, Alok
dc.contributor.authorWang, Jihua
dc.contributor.authorSattar, Abdul
dc.contributor.authorZhou, Yaoqi
dc.contributor.authorYang, Yuedong
dc.date.accessioned2017-11-21T05:36:59Z
dc.date.available2017-11-21T05:36:59Z
dc.date.issued2016
dc.identifier.issn1367-4803
dc.identifier.doi10.1093/bioinformatics/btv665
dc.identifier.urihttp://hdl.handle.net/10072/125244
dc.description.abstractMotivation: Solvent exposure of amino acid residues of proteins plays an important role in understanding and predicting protein structure, function and interactions. Solvent exposure can be characterized by several measures including solvent accessible surface area (ASA), residue depth (RD) and contact numbers (CN). More recently, an orientation-dependent contact number called half-sphere exposure (HSE) was introduced by separating the contacts within upper and down half spheres defined according to the Cα-Cβ (HSEβ) vector or neighboring Cα-Cα vectors (HSEα). HSEα calculated from protein structures was found to better describe the solvent exposure over ASA, CN and RD in many applications. Thus, a sequence-based prediction is desirable, as most proteins do not have experimentally determined structures. To our best knowledge, there is no method to predict HSEα and only one method to predict HSEβ. Results: This study developed a novel method for predicting both HSEα and HSEβ (SPIDER-HSE) that achieved a consistent performance for 10-fold cross validation and two independent tests. The correlation coefficients between predicted and measured HSEβ (0.73 for upper sphere, 0.69 for down sphere and 0.76 for contact numbers) for the independent test set of 1199 proteins are significantly higher than existing methods. Moreover, predicted HSEα has a higher correlation coefficient (0.46) to the stability change by residue mutants than predicted HSEβ (0.37) and ASA (0.43). The results, together with its easy Cα-atom-based calculation, highlight the potential usefulness of predicted HSEα for protein structure prediction and refinement as well as function prediction.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherOxford University Press
dc.relation.ispartofpagefrom843
dc.relation.ispartofpageto849
dc.relation.ispartofissue6
dc.relation.ispartofjournalBioinformatics
dc.relation.ispartofvolume32
dc.subject.fieldofresearchBioinformatics
dc.subject.fieldofresearchStructural Biology (incl. Macromolecular Modelling)
dc.subject.fieldofresearchPattern Recognition and Data Mining
dc.subject.fieldofresearchMathematical Sciences
dc.subject.fieldofresearchBiological Sciences
dc.subject.fieldofresearchInformation and Computing Sciences
dc.subject.fieldofresearchcode060102
dc.subject.fieldofresearchcode060112
dc.subject.fieldofresearchcode080109
dc.subject.fieldofresearchcode01
dc.subject.fieldofresearchcode06
dc.subject.fieldofresearchcode08
dc.titleHighly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.hasfulltextNo Full Text
gro.griffith.authorSattar, Abdul
gro.griffith.authorPaliwal, Kuldip K.
gro.griffith.authorSharma, Alok
gro.griffith.authorLyons, James
gro.griffith.authorHeffernan, Rhys
gro.griffith.authorDehzangi, Iman
gro.griffith.authorZhou, Yaoqi
gro.griffith.authorYang, Yuedong


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