Affordable Access

deepdyve-link
Publisher Website

Model quality assessment using distance constraints from alignments.

Authors
  • Paluszewski, Martin
  • Karplus, Kevin
Type
Published Article
Journal
Proteins: Structure, Function, and Bioinformatics
Publisher
Wiley
Publication Date
May 15, 2009
Volume
75
Issue
3
Pages
540–549
Identifiers
DOI: 10.1002/prot.22262
PMID: 19003987
Source
Medline
License
Unknown

Abstract

Given a set of alternative models for a specific protein sequence, the model quality assessment (MQA) problem asks for an assignment of scores to each model in the set. A good MQA program assigns these scores such that they correlate well with real quality of the models, ideally scoring best that model which is closest to the true structure. In this article, we present a new approach for addressing the MQA problem. It is based on distance constraints extracted from alignments to templates of known structure, and is implemented in the Undertaker program for protein structure prediction. One novel feature is that we extract noncontact constraints as well as contact constraints. We describe how the distance constraint extraction is done and we show how they can be used to address the MQA problem. We have compared our method on CASP7 targets and the results show that our method is at least comparable with the best MQA methods that were assessed at CASP7. We also propose a new evaluation measure, Kendall's tau, that is more interpretable than conventional measures used for evaluating MQA methods (Pearson's r and Spearman's rho). We show clear examples where Kendall's tau agrees much more with our intuition of a correct MQA, and we therefore propose that Kendall's tau be used for future CASP MQA assessments.

Report this publication

Statistics

Seen <100 times