Protein wild-type and mutant ensemble database

dc.contributor.advisor Guang Song
dc.contributor.author Zhang, Ce
dc.contributor.department Computer Science
dc.date 2018-08-11T16:36:34.000
dc.date.accessioned 2020-06-30T03:08:20Z
dc.date.available 2020-06-30T03:08:20Z
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>Protein structures have been determined and deposited into Protein Data Bank at an increasing rate. In this work, we organize all the protein structures in the PDB and form a wild type and mutant structure database. The database groups the wild type and mutant structures of the same protein together. One direct benefit of the database is thus the easy accessibility of the structure ensembles of all the proteins. Such ensembles are known to be highly useful for representing the native states of proteins and for understanding their functions. For each protein, mutants are sorted by the number of mutations and the location(s) of the mutations. What distinguishes our work from other mutation databases is that it is structure-based and includes all the existing structures of the PDB. Synchronization with the PDB database will be maintained. As an application, we carry out an experimental structure-based statistical analysis of the effects of mutations, on both protein structure and protein dynamics. A key question we address in this work is: is it valid to use mutant structures (or variants from different species) to represent a native state sample of a given protein? Our results indicate that mutations can cause significant structure changes and dynamics changes, more than commonly expected. This implies that cautions must be taken when mutation structures are considered to be included as representative samples of the conformation space of a given protein.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/etd/16048/
dc.identifier.articleid 7055
dc.identifier.contextkey 11169620
dc.identifier.doi https://doi.org/10.31274/etd-180810-5675
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath etd/16048
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/30231
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/etd/16048/Zhang_iastate_0097M_16222.pdf|||Fri Jan 14 20:54:20 UTC 2022
dc.subject.disciplines Bioinformatics
dc.subject.disciplines Biology
dc.subject.disciplines Computer Sciences
dc.subject.keywords database
dc.subject.keywords effects
dc.subject.keywords ensemble
dc.subject.keywords mutants
dc.subject.keywords protein
dc.subject.keywords wild-type
dc.title Protein wild-type and mutant ensemble database
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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