Improving the quality of protein structure models by selecting from alignment alternatives.

ABSTRACT:

Background

In the area of protein structure prediction, recently a lot of effort has gone into the development of Model Quality Assessment Programs (MQAPs). MQAPs distinguish high quality protein structure models from inferior models. Here, we propose a new method to use an MQAP to improve the quality of models. With a given target sequence and template structure, we construct a number of different alignments and corresponding models for the sequence. The quality of these models is scored with an MQAP and used to choose the most promising model. An SVM-based selection scheme is suggested for combining MQAP partial potentials, in order to optimize for improved model selection.

Results

The approach has been tested on a representative set of proteins. The ability of the method

SUBMITTER: Sommer I 

PROVIDER: S-EPMC1579234 | biostudies-literature | 2006 Jul

REPOSITORIES: biostudies-literature