A Novel Statistical Potential for Protein Beta-Sheets Prediction

dc.contributor.advisorMa, Jianpengen_US
dc.contributor.committeeMemberNordlander, Peter J.en_US
dc.contributor.committeeMemberRaphael, Robert M.en_US
dc.creatorYu, Linglinen_US
dc.date.accessioned2014-10-16T18:08:35Zen_US
dc.date.available2014-10-16T18:08:35Zen_US
dc.date.created2014-05en_US
dc.date.issued2014-04-25en_US
dc.date.submittedMay 2014en_US
dc.date.updated2014-10-16T18:08:35Zen_US
dc.description.abstractOne of the most long-term challenging problems in biophysics studies for both computational scientists and experimentalists is protein structure prediction, whose goal is to obtain three-dimensional native protein structure from one-dimensional sequence. In protein structure prediction problems, a fundamental problem is Beta-sheets structure prediction. Though more than 85% of experimentally solved proteins contain Beta-sheet structures, limited methods have been found to rapidly and accurately predict the folded conformations. In this study, we proposed a novel statistical potential, named NP-Beta, to predict the protein Beta-sheet structure only based on the sequence information. We included three kinds of potential terms in NP-Beta, i.e. the self-packing term, the pair interacting term and the lattice term. The number of hydrogen bonds in Beta-sheets is also considered as a potential component, corresponding to a global penalty of the potential function. Computational tests show that the new statistical potential has an outstanding performance on native structure recognition from decoys comparing to the Beta-sheet specific potentials in literature. We will apply the potential to improve the prediction of Beta-strand arrangement and registration for beta proteins.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationYu, Linglin. "A Novel Statistical Potential for Protein Beta-Sheets Prediction." (2014) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/77586">https://hdl.handle.net/1911/77586</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/77586en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectStatistical potentialen_US
dc.subjectBeta-Sheetsen_US
dc.titleA Novel Statistical Potential for Protein Beta-Sheets Predictionen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentApplied Physicsen_US
thesis.degree.disciplineNatural Sciencesen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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