Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11.

ABSTRACT: Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The p

SUBMITTER: Cao R 

PROVIDER: S-EPMC4792798 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature