Linked Life Data

10816018

Source:http://linkedlifedata.com/resource/pubmed/id/10816018

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3-4
pubmed:dateCreated
2000-6-15
pubmed:abstractText
We present a global optimization strategy that incorporates predicted restraints in both a local optimization context and as directives for global optimization approaches, to predict protein tertiary structure for alpha-helical proteins. Specifically, neural networks are used to predict the secondary structure of a protein, restraints are defined as manifestations of the network with a predicted secondary structure and the secondary structure is formed using local minimizations on a protein energy surface, in the presence of the restraints. Those residues predicted to be coil, by the network, define a conformational sub-space that is subject to optimization using a global approach known as stochastic perturbation that has been found to be effective for Lennard-Jones clusters and homo-polypeptides. Our energy surface is an all-atom 'gas phase' molecular mechanics force field, that is combined with a new solvation energy function that penalizes hydrophobic group exposure. This energy function gives the crystal structure of four different alpha-helical proteins as the lowest energy structure relative to other conformations, with correct secondary structure but incorrect tertiary structure. We demonstrate this global optimization strategy by determining the tertiary structure of the A-chain of the alpha-helical protein, uteroglobin and of a four-helix bundle, DNA binding protein.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0097-8485
pubmed:author
pubmed:issnType
Print
pubmed:volume
24
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
489-97
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
A global optimization strategy for predicting alpha-helical protein tertiary structure.
pubmed:affiliation
Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, 94720 California, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.