How to generate improved potentials for protein tertiary structure prediction: A lattice model study
dc.contributor.author | Chiu, Ting-Lan | en_US |
dc.contributor.author | Goldstein, Richard A. | en_US |
dc.date.accessioned | 2006-04-19T14:01:53Z | |
dc.date.available | 2006-04-19T14:01:53Z | |
dc.date.issued | 2000-11-01 | en_US |
dc.identifier.citation | Chiu, Ting-Lan; Goldstein, Richard A. (2000)."How to generate improved potentials for protein tertiary structure prediction: A lattice model study." Proteins: Structure, Function, and Genetics 41(2): 157-163. <http://hdl.handle.net/2027.42/34971> | en_US |
dc.identifier.issn | 0887-3585 | en_US |
dc.identifier.issn | 1097-0134 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/34971 | |
dc.identifier.uri | http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=retrieve&db=pubmed&list_uids=10966569&dopt=citation | en_US |
dc.description.abstract | Success in the protein structure prediction problem relies heavily on the choice of an appropriate potential function. One approach toward extracting these potentials from a database of known protein structures is to maximize the Z -score of the database proteins, which represents the ability of the potential to discriminate correct from random conformations. These optimization methods model the entire distribution of alternative structures, reducing their ability to concentrate on the lowest energy structures most competitive with the native state and resulting in an unfortunate tendency to underestimate the repulsive interactions. This leads to reduced accuracy and predictive ability. Using a lattice model, we demonstrate how we can weight the distribution to suppress the contributions of the high-energy conformations to the Z -score calculation. The result is a potential that is more accurate and more likely to yield correct predictions than other Z -score optimization methods as well as potentials of mean force. Proteins 2000;41:157–163. © 2000 Wiley-Liss, Inc. | en_US |
dc.format.extent | 125506 bytes | |
dc.format.extent | 3118 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | John Wiley & Sons, Inc. | en_US |
dc.subject.other | Chemistry | en_US |
dc.subject.other | Biochemistry and Biotechnology | en_US |
dc.title | How to generate improved potentials for protein tertiary structure prediction: A lattice model study | en_US |
dc.type | Article | en_US |
dc.rights.robots | IndexNoFollow | en_US |
dc.subject.hlbsecondlevel | Molecular, Cellular and Developmental Biology | en_US |
dc.subject.hlbtoplevel | Health Sciences | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Chemistry, University of Michigan, Ann Arbor, Michigan | en_US |
dc.contributor.affiliationum | Department of Chemistry, University of Michigan, Ann Arbor, Michigan ; Biophysics Research Division, University of Michigan, Ann Arbor, Michigan ; Department of Chemistry, Biophysics Research Division, University of Michigan, Ann Arbor, MI 48109-1055 | en_US |
dc.identifier.pmid | 10966569 | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/34971/1/10_ftp.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1002/1097-0134(20001101)41:2<157::AID-PROT10>3.0.CO;2-W | en_US |
dc.identifier.source | Proteins: Structure, Function, and Genetics | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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