Linked Life Data

20804770

Source:http://linkedlifedata.com/resource/pubmed/id/20804770

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2010-10-4
pubmed:abstractText
X-ray crystallography and NMR can provide detailed structural information of protein-protein complexes, but technical problems make their application challenging in the high-throughput regime. Other methods such as small-angle X-ray scattering (SAXS) are more promising for large-scale application, but at the cost of lower resolution, which is a problem that can be solved by complementing SAXS data with theoretical simulations. Here, we propose a novel strategy that combines SAXS data and accurate protein-protein docking simulations. The approach has been benchmarked on a large pool of known structures with synthetic SAXS data, and on three experimental examples. The combined approach (pyDockSAXS) provided a significantly better success rate (43% for the top 10 predictions) than either of the two methods alone. Further analysis of the influence of different docking parameters made it possible to increase the success rates for specific cases, and to define guidelines for improving the data-driven protein-protein docking protocols.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1089-8638
pubmed:author
pubmed:copyrightInfo
Copyright © 2010 Elsevier Ltd. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
22
pubmed:volume
403
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
217-30
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Structural characterization of protein-protein complexes by integrating computational docking with small-angle scattering data.
pubmed:affiliation
Life Sciences Department, Barcelona Supercomputing Center, Barcelona 08034, Spain.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Validation Studies