Staff View
Comparing two NMR structure refinement methods

Descriptive

TitleInfo
Title
Comparing two NMR structure refinement methods
Name (type = personal)
NamePart (type = family)
Yao
NamePart (type = given)
Yisha
DisplayForm
Yisha Yao
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Montelione
NamePart (type = given)
Gaetano
DisplayForm
Gaetano Montelione
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2017
DateOther (qualifier = exact); (type = degree)
2017-10
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2017
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
High throughput and automatic procedures for NMR structure determination are under intensive study in the current era of structural genomics. The major steps include data collection, data processing, resonance assignment with validation, derivation of structural restraints, generation of 20 conformers satisfying the structural restraints (the ensemble), and refinement of the conformers. The final step structure refinement typically refers to further energy minimization based on certain force fields. Refinement could improve the structure quality to a large extent due to the sparseness of NMR experimental measurements. A scientific and robust refinement methodology is desired as a vital part of the standard protocols of automatic NMR structure determination. In this study, we compare the performances of two refinement methods, CNS refinement and AMBER refinement. The core algorithm of CNS refinement is simulated annealing with gradient descent while AMBER uses molecular dynamics simulated annealing. Eight protein targets are chosen randomly from the NESG depository and the two refinement methods tested on these targets. All the targets have chemical shifts and NOESY peak lists available, and 4 of them also have RDC data. Using the available NMR experiment data, initial coarse structures are generated by ASDP-CYANA. These coarse structures further go through CNS refinement and AMBER refinement. Then the CNS-refined and AMBER-refined structures are evaluated in terms of RMSD (reference to X-ray PDB structure) and DP score. We find that AMBER refinement achieves better results than CNS on 7 out of 8 targets—AMBER refined structures have smaller average RMSDs and higher ensemble-average DP scores. The differentiated performance of the two refinement methods could stem from the different algorithms and force fields implemented.
Subject (authority = RUETD)
Topic
Biochemistry
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8390
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (viii, 69 p. : ill.)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Nuclear magnetic resonance
Note (type = statement of responsibility)
by Yisha Yao
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3FF3WJP
Genre (authority = ExL-Esploro)
ETD graduate
Back to the top

Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Yao
GivenName
Yisha
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-09-23 19:16:19
AssociatedEntity
Name
Yisha Yao
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top

Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
CreatingApplication
Version
1.4
ApplicationName
Mac OS X 10.11.6 Quartz PDFContext
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2017-09-23T23:14:09
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2017-09-23T23:14:09
Back to the top
Version 8.5.5
Rutgers University Libraries - Copyright ©2024