QAcon: single model quality assessment using protein structural and contact information with machine learning techniques.

ABSTRACT:

Motivation

Protein model quality assessment (QA) plays a very important role in protein structure prediction. It can be divided into two groups of methods: single model and consensus QA method. The consensus QA methods may fail when there is a large portion of low quality models in the model pool.

Results

In this paper, we develop a novel single-model quality assessment method QAcon utilizing structural features, physicochemical properties, and residue contact predictions. We apply residue-residue contact information predicted by two protein contact prediction methods PSICOV and DNcon to generate a new score as feature for quality assessment. This novel feature and other 11 features are used as input to train a two-layer neural network on CASP9 datasets to predict the qualit

SUBMITTER: Cao R 

PROVIDER: S-EPMC6041872 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature