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

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

doi:10.1371/journal.pone.0152517

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

Journal Article · Tue Apr 05 00:00:00 EDT 2016 · PLoS ONE

DOI:https://doi.org/10.1371/journal.pone.0152517· OSTI ID:2469804

Fischer, Axel W. ^[1]; Heinze, Sten ^[1]; Putnam, Daniel K. ^[1]; Li, Bian ^[1]; Pino, James C. ^[1]; Xia, Yan ^[1]; Lopez, Carlos F. ^[1]; Meiler, Jens ^[1]

Vanderbilt University, Nashville, TN (United States)

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.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 2469804

Journal Information:: PLoS ONE, Journal Name: PLoS ONE Journal Issue: 4 Vol. 11; ISSN 1932-6203

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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