Improving the quality of protein structure models by selecting from alignment alternatives |
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| Authors: | Ingolf Sommer Stefano Toppo Oliver Sander Thomas Lengauer Silvio CE Tosatto |
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| Affiliation: | (1) Department of Computational Biology and Applied Algorithmics, Max-Planck-lnstitute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbr?cken, Germany;(2) Department of Biological Chemistry, University of Padova, via U. Bassi 58/b, 1-35121, Padova, Italy;(3) Department of Biology, CRIBI Biotechnology Centre University of Padova, V.le G. Colombo 3, I-35131 Padova, Italy |
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| 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. |
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