Recursive protein modeling: A divide and conquer strategy for protein structure prediction and its case study in CASP9

Jianlin Cheng, Jesse Eickholt, Zheng Wang, Xin Deng

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of structural modeling, two types of modeling techniques - template-based modeling and template-free modeling - have been developed. Template-based modeling can often generate a moderate- to high-resolution model when a similar, homologous template structure is found for a query protein but fails if no template or only incorrect templates are found. Template-free modeling, such as fragment-based assembly, may generate models of moderate resolution for small proteins of low topological complexity. Seldom have the two techniques been integrated together to improve protein modeling. Here we develop a recursive protein modeling approach to selectively and collaboratively apply template-based and template-free modeling methods to model template-covered (i.e. certain) and template-free (i.e. uncertain) regions of a protein. A preliminary implementation of the approach was tested on a number of hard modeling cases during the 9th Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and successfully improved the quality of modeling in most of these cases. Recursive modeling can significantly reduce the complexity of protein structure modeling and integrate template-based and template-free modeling to improve the quality and efficiency of protein structure prediction.

Original languageEnglish (US)
Article number1242003
JournalJournal of Bioinformatics and Computational Biology
Volume10
Issue number3
DOIs
StatePublished - Jun 1 2012
Externally publishedYes

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Keywords

  • CASP
  • Protein structure prediction
  • recursive protein modeling
  • template-based modeling
  • template-free modeling

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Computer Science Applications

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