Improving the accuracy of template-based predictions by mixing and matching between initial models.

ABSTRACT:

Background

Comparative modeling is a technique to predict the three dimensional structure of a given protein sequence based primarily on its alignment to one or more proteins with experimentally determined structures. A major bottleneck of current comparative modeling methods is the lack of methods to accurately refine a starting initial model so that it approaches the resolution of the corresponding experimental structure. We investigate the effectiveness of a graph-theoretic clique finding approach to solve this problem.

Results

Our method takes into account the information presented in multiple templates/alignments at the three-dimensional level by mixing and matching regions between different initial comparative models. This method enables us to obtain an optimized confo

SUBMITTER: Liu T 

PROVIDER: S-EPMC2424052 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature