Linked Life Data

15910070

Source:http://linkedlifedata.com/resource/pubmed/id/15910070

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
17
pubmed:dateCreated
2005-5-24
pubmed:abstractText
Closely related to the "protein folding problem" is the issue of protein misfolding and aggregation. Protein aggregation has been associated with the pathologies of nearly 20 human diseases and presents serious difficulties during the manufacture of pharmaceutical proteins. Computational studies of multiprotein systems have recently emerged as a powerful complement to experimental efforts aimed at understanding the mechanisms of protein aggregation. We describe the thermodynamics of systems containing two lattice-model 64-mers. A parallel tempering algorithm abates problems associated with glassy systems and the weighted histogram analysis method improves statistical quality. The presence of a second chain has a substantial effect on single-chain conformational preferences. The melting temperature is substantially reduced, and the increase in the population of unfolded states is correlated with an increase in interactions between chains. The transition from two native chains to a non-native aggregate is entropically favorable. Non-native aggregates receive approximately 25% of their stabilizing energy from intraprotein contacts not found in the lowest-energy structure. Contact maps show that for non-native dimers, nearly 50% of the most probable interprotein contacts involve pairs of residues that form native contacts, suggesting that a domain-swapping mechanism is involved in self-association.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
0021-9606
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
122
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
174908
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Thermodynamics of folding and association of lattice-model proteins.
pubmed:affiliation
Department of Chemical Engineering, University of California, Berkeley, 94720, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.