Fragment based protein structure prediction. (c2013)

In recent years, the protein structure prediction problem has come under extensive investigation, and computational structure prediction methods are circumventing the time-consuming experimental methods by accelerating the prediction process. This work presents a fragment based protein tertiary stru...

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Main Author: Terzian, Meghrig Ohanes (author)
Format: masterThesis
Published: 2016
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Online Access:http://hdl.handle.net/10725/3265
https://doi.org/10.26756/th.2013.48
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author Terzian, Meghrig Ohanes
author_facet Terzian, Meghrig Ohanes
author_role author
dc.creator.none.fl_str_mv Terzian, Meghrig Ohanes
dc.date.none.fl_str_mv 2016-03-04T09:29:35Z
2016-03-04T09:29:35Z
2016-03-04
7/18/2013
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/3265
https://doi.org/10.26756/th.2013.48
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Lebanese American University
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Proteins -- Structure -- Mathematical models
Dissertations, Academic
Lebanese American University -- Dissertations
dc.title.none.fl_str_mv Fragment based protein structure prediction. (c2013)
dc.type.none.fl_str_mv Thesis
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/masterThesis
description In recent years, the protein structure prediction problem has come under extensive investigation, and computational structure prediction methods are circumventing the time-consuming experimental methods by accelerating the prediction process. This work presents a fragment based protein tertiary structure prediction method that provides suboptimal structures. In addition, it demonstrates the advantage of using the CHARMM36 energy model. The method is based on a two-phase Scatter Search metaheuristic that minimizes the energy function. Backbone fragments selections extracted from the Robetta server are followed by side chain selections, extracted from the Dunbrack Library. The results, evaluated on three proteins, show that the algorithm produces tertiary structures with promising root mean square deviations, within reasonable times.
eu_rights_str_mv openAccess
format masterThesis
id LAURepo_f13b0dd09a4c04cc77e11c367131eb33
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/3265
publishDate 2016
publisher.none.fl_str_mv Lebanese American University
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling Fragment based protein structure prediction. (c2013)Terzian, Meghrig OhanesProteins -- Structure -- Mathematical modelsDissertations, AcademicLebanese American University -- DissertationsIn recent years, the protein structure prediction problem has come under extensive investigation, and computational structure prediction methods are circumventing the time-consuming experimental methods by accelerating the prediction process. This work presents a fragment based protein tertiary structure prediction method that provides suboptimal structures. In addition, it demonstrates the advantage of using the CHARMM36 energy model. The method is based on a two-phase Scatter Search metaheuristic that minimizes the energy function. Backbone fragments selections extracted from the Robetta server are followed by side chain selections, extracted from the Dunbrack Library. The results, evaluated on three proteins, show that the algorithm produces tertiary structures with promising root mean square deviations, within reasonable times.N/A1 hard copy: xiii, 63 leaves.; ill.; 30 cm. available at RNL.Includes bibliographical references (leaves 59-63).Lebanese American University2016-03-04T09:29:35Z2016-03-04T09:29:35Z7/18/20132016-03-04Thesisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesishttp://hdl.handle.net/10725/3265https://doi.org/10.26756/th.2013.48eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/32652020-11-20T08:43:23Z
spellingShingle Fragment based protein structure prediction. (c2013)
Terzian, Meghrig Ohanes
Proteins -- Structure -- Mathematical models
Dissertations, Academic
Lebanese American University -- Dissertations
status_str publishedVersion
title Fragment based protein structure prediction. (c2013)
title_full Fragment based protein structure prediction. (c2013)
title_fullStr Fragment based protein structure prediction. (c2013)
title_full_unstemmed Fragment based protein structure prediction. (c2013)
title_short Fragment based protein structure prediction. (c2013)
title_sort Fragment based protein structure prediction. (c2013)
topic Proteins -- Structure -- Mathematical models
Dissertations, Academic
Lebanese American University -- Dissertations
url http://hdl.handle.net/10725/3265
https://doi.org/10.26756/th.2013.48