Linked Life Data

17407093

Source:http://linkedlifedata.com/resource/pubmed/id/17407093

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2007-6-28
pubmed:abstractText
Recent work has shown that physics-based, all-atom energy functions (AMBER, CHARMM, OPLS-AA) and local minimization, when used in scoring, are able to discriminate among native and decoy structures. Yet, there have been only few instances reported of the successful use of physics based potentials in the actual refinement of protein models from a starting conformation to one that ends in structures, which are closer to the native state. An energy function that has a global minimum energy in the protein's native state and a good correlation between energy and native-likeness should be able to drive model structures closer to their native structure during a conformational search. Here, the possible reasons for the discrepancy between the scoring and refinement results for the case of AMBER potential are examined. When the conformational search via molecular dynamics is driven by the AMBER potential for a large set of 150 nonhomologous proteins and their associated decoys, often the native minimum does not appear to be the lowest free energy state. Ways of correcting the potential function in order to make it more suitable for protein model refinement are proposed.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0192-8651
pubmed:author
pubmed:copyrightInfo
Copyright 2007 Wiley Periodicals, Inc.
pubmed:issnType
Print
pubmed:volume
28
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2059-66
pubmed:dateRevised
2007-12-3
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Can a physics-based, all-atom potential find a protein's native structure among misfolded structures? I. Large scale AMBER benchmarking.
pubmed:affiliation
Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, Georgia 30318, USA.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural