CASP11 – An Evaluation of a Modular BCL::Fold-Based Protein Structure Prediction Pipeline

Axel W Fischer, Sten Heinze, Daniel K Putnam, Bian Li, James C Pino, Yan Xia, Carlos F Lopez and Jens Meiler

PLOS ONE, 2016, vol. 11, issue 4, 1-19

Abstract: In silico prediction of a protein’s tertiary structure remains an unsolved problem. The community-wide Critical Assessment of Protein Structure Prediction (CASP) experiment provides a double-blind study to evaluate improvements in protein structure prediction algorithms. We developed a protein structure prediction pipeline employing a three-stage approach, consisting of low-resolution topology search, high-resolution refinement, and molecular dynamics simulation to predict the tertiary structure of proteins from the primary structure alone or including distance restraints either from predicted residue-residue contacts, nuclear magnetic resonance (NMR) nuclear overhauser effect (NOE) experiments, or mass spectroscopy (MS) cross-linking (XL) data. The protein structure prediction pipeline was evaluated in the CASP11 experiment on twenty regular protein targets as well as thirty-three ‘assisted’ protein targets, which also had distance restraints available. Although the low-resolution topology search module was able to sample models with a global distance test total score (GDT_TS) value greater than 30% for twelve out of twenty proteins, frequently it was not possible to select the most accurate models for refinement, resulting in a general decay of model quality over the course of the prediction pipeline. In this study, we provide a detailed overall analysis, study one target protein in more detail as it travels through the protein structure prediction pipeline, and evaluate the impact of limited experimental data.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0152517

DOI: 10.1371/journal.pone.0152517

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