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

Content Provider	IEEE Xplore Digital Library
Author	Jianlin Cheng Zheng Wang Eickholt, J. Xin Deng
Copyright Year	2011
Description	Author affiliation: Department of Computer Science, University of Missouri, Columbia, MO 65211, USA (Zheng Wang; Eickholt, J.; Xin Deng) \|\| Department of Computer Science, Informatics, Institute, C. Bond Life Science Center, University of Missouri, Columbia, MO 65211, USA (Jianlin Cheng)
Abstract	After decades of research, protein structure prediction remains a very challenging problem. In order to address the different levels of complexity of modeling structure, 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.
Starting Page	352
Ending Page	357
File Size	841992
Page Count	6
File Format	PDF
ISBN	9781457716126
e-ISBN	9781457716133
DOI	10.1109/BIBMW.2011.6112398
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Proteins Computer science CASP9 Protein engineering Computational modeling template-free modeling Predictive models recursive protein modeling Servers protein structure prediction Assembly template-based modeling
Content Type	Text
Resource Type	Article

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