Linked Life Data

20329755

Source:http://linkedlifedata.com/resource/pubmed/id/20329755

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2010-5-7
pubmed:abstractText
The design of an ideal scoring function for protein-protein docking that would also predict the binding affinity of a complex is one of the challenges in structural proteomics. Such a scoring function would open the route to in silico, large-scale annotation and prediction of complete interactomes. Here we present a protein-protein binding affinity benchmark consisting of binding constants (K(d)'s) for 81 complexes. This benchmark was used to assess the performance of nine commonly used scoring algorithms along with a free-energy prediction algorithm in their ability to predicting binding affinities. Our results reveal a poor correlation between binding affinity and scores for all algorithms tested. However, the diversity and validity of the benchmark is highlighted when binding affinity data are categorized according to the methodology by which they were determined. By further classifying the complexes into low, medium and high affinity groups, significant correlations emerge, some of which are retained after dividing the data into more classes, showing the robustness of these correlations. Despite this, accurate prediction of binding affinity remains outside our reach due to the large associated standard deviations of the average score within each group. All the above-mentioned observations indicate that improvements of existing scoring functions or design of new consensus tools will be required for accurate prediction of the binding affinity of a given protein-protein complex. The benchmark developed in this work will serve as an indispensable source to reach this goal.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1535-3907
pubmed:author
pubmed:issnType
Electronic
pubmed:day
7
pubmed:volume
9
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2216-25
pubmed:dateRevised
2011-3-7
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Are scoring functions in protein-protein docking ready to predict interactomes? Clues from a novel binding affinity benchmark.
pubmed:affiliation
Bijvoet Center for Biomolecular Research, Science Faculty, Utrecht University, 3584CH, Utrecht, The Netherlands.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't