Predicting local quality of a sequence-structure alignment

Xin Gao, Jinbo Xu, Shuai Cheng Li, Ming Li*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Although protein structure prediction has made great progress in recent years, a protein model derived from automated prediction methods is subject to various errors. As methods for structure prediction develop, a continuing problem is how to evaluate the quality of a protein model, especially to identify some well-predicted regions of the model, so that the structural biology community can benefit from the automated structure prediction. It is also important to identify badly-predicted regions in a model so that some refinement measurements can be applied to it. We present two complementary techniques, FragQA and PosQA, to accurately predict local quality of a sequence-structure (i.e. sequence-template) alignment generated by comparative modeling (i.e. homology modeling and threading). FragQA and PosQA predict local quality from two different perspectives. Different from existing methods, FragQA directly predicts cRMSD between a continuously aligned fragment determined by an alignment and the corresponding fragment in the native structure, while PosQA predicts the quality of an individual aligned position. Both FragQA and PosQA use an SVM (Support Vector Machine) regression method to perform prediction using similar information extracted from a single given alignment. Experimental results demonstrate that FragQA performs well on predicting local fragment quality, and PosQA outperforms two top-notch methods, ProQres and ProQprof. Our results indicate that (1) local quality can be predicted well; (2) local sequence evolutionary information (i.e. sequence similarity) is the major factor in predicting local quality; and (3) structural information such as solvent accessibility and secondary structure helps to improve the prediction performance.

Original languageEnglish (US)
Pages (from-to)789-810
Number of pages22
JournalJournal of Bioinformatics and Computational Biology
Volume7
Issue number5
DOIs
StatePublished - Oct 9 2009

Keywords

  • CASP7
  • Local quality assessment
  • Protein structure prediction
  • SVM regression
  • Sequence-structure alignment

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Predicting local quality of a sequence-structure alignment'. Together they form a unique fingerprint.

Cite this