Investigating the effects of different force fields on spring-based normal mode analysis

dc.contributor.advisor Guang Song
dc.contributor.author Song, Jaekyun
dc.contributor.department Computer Science
dc.date 2018-08-11T14:48:42.000
dc.date.accessioned 2020-06-30T03:06:37Z
dc.date.available 2020-06-30T03:06:37Z
dc.date.copyright Fri Jan 01 00:00:00 UTC 2016
dc.date.embargo 2001-01-01
dc.date.issued 2016-01-01
dc.description.abstract <p>Classical normal mode analysis (CNMA) has been widely acknowledged as one of the most useful simulation tools for studying protein dynamics. CNMA uses a fine-grained all-atom model of proteins and a complex empirical potential. In addition, CNMA requires a structure that must be energetically minimized, which makes the method cumbersome to use, especially for large proteins. In contrast, elastic network models (ENM) use coarse-grained protein models and adopt a simplified potential function. ENM is much faster than CNMA but is less accurate. To take the advantages of both CNMA and ENM, the spring-based normal mode analysis (sbNMA) was developed. It uses a fine-grained all-atom model for proteins and an all-atom empirical force field to maintain accuracy while reducing the computing complexity by eliminating the minimization step. In the previous work on sbNMA, only the CHARMM force field was explored. In this work, we extend the analyses to AMBER, another widely-used force field. We investigate the dependence of sbNMA's performance on force fields. This work provides also insightful understandings of the differences between CHARMM and AMBER.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/15812/
dc.identifier.articleid 6819
dc.identifier.contextkey 11165373
dc.identifier.doi https://doi.org/10.31274/etd-180810-5440
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/15812
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/29995
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/15812/Song_iastate_0097M_16009.pdf|||Fri Jan 14 20:47:04 UTC 2022
dc.subject.disciplines Bioinformatics
dc.subject.disciplines Biophysics
dc.subject.disciplines Computer Sciences
dc.subject.keywords AMBER
dc.subject.keywords ENM
dc.subject.keywords NMA
dc.subject.keywords Normal mode analysis
dc.subject.keywords sbNMA
dc.subject.keywords Vibrational spectrum
dc.title Investigating the effects of different force fields on spring-based normal mode analysis
dc.type article
dc.type.genre thesis
dspace.entity.type Publication
relation.isOrgUnitOfPublication f7be4eb9-d1d0-4081-859b-b15cee251456
thesis.degree.discipline Computer Science
thesis.degree.level thesis
thesis.degree.name Master of Science
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