Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.

The Critical Assessment of techniques for protein Structure Prediction (or CASP) is a community-wide blind test experiment to reveal the best accomplishments of structure modeling. Assessors have been using the Global Distance Test (GDT_TS) measure to quantify prediction performance since CASP3 in 1...

Full description

Bibliographic Details
Main Authors: Wenlin Li, R Dustin Schaeffer, Zbyszek Otwinowski, Nick V Grishin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4858170?pdf=render
id doaj-3e8f5fa651b54b879cd526e253c1b15c
record_format Article
spelling doaj-3e8f5fa651b54b879cd526e253c1b15c2020-11-25T01:55:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01115e015478610.1371/journal.pone.0154786Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.Wenlin LiR Dustin SchaefferZbyszek OtwinowskiNick V GrishinThe Critical Assessment of techniques for protein Structure Prediction (or CASP) is a community-wide blind test experiment to reveal the best accomplishments of structure modeling. Assessors have been using the Global Distance Test (GDT_TS) measure to quantify prediction performance since CASP3 in 1998. However, identifying significant score differences between close models is difficult because of the lack of uncertainty estimations for this measure. Here, we utilized the atomic fluctuations caused by structure flexibility to estimate the uncertainty of GDT_TS scores. Structures determined by nuclear magnetic resonance are deposited as ensembles of alternative conformers that reflect the structural flexibility, whereas standard X-ray refinement produces the static structure averaged over time and space for the dynamic ensembles. To recapitulate the structural heterogeneous ensemble in the crystal lattice, we performed time-averaged refinement for X-ray datasets to generate structural ensembles for our GDT_TS uncertainty analysis. Using those generated ensembles, our study demonstrates that the time-averaged refinements produced structure ensembles with better agreement with the experimental datasets than the averaged X-ray structures with B-factors. The uncertainty of the GDT_TS scores, quantified by their standard deviations (SDs), increases for scores lower than 50 and 70, with maximum SDs of 0.3 and 1.23 for X-ray and NMR structures, respectively. We also applied our procedure to the high accuracy version of GDT-based score and produced similar results with slightly higher SDs. To facilitate score comparisons by the community, we developed a user-friendly web server that produces structure ensembles for NMR and X-ray structures and is accessible at http://prodata.swmed.edu/SEnCS. Our work helps to identify the significance of GDT_TS score differences, as well as to provide structure ensembles for estimating SDs of any scores.http://europepmc.org/articles/PMC4858170?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Wenlin Li
R Dustin Schaeffer
Zbyszek Otwinowski
Nick V Grishin
spellingShingle Wenlin Li
R Dustin Schaeffer
Zbyszek Otwinowski
Nick V Grishin
Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.
PLoS ONE
author_facet Wenlin Li
R Dustin Schaeffer
Zbyszek Otwinowski
Nick V Grishin
author_sort Wenlin Li
title Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.
title_short Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.
title_full Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.
title_fullStr Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.
title_full_unstemmed Estimation of Uncertainties in the Global Distance Test (GDT_TS) for CASP Models.
title_sort estimation of uncertainties in the global distance test (gdt_ts) for casp models.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description The Critical Assessment of techniques for protein Structure Prediction (or CASP) is a community-wide blind test experiment to reveal the best accomplishments of structure modeling. Assessors have been using the Global Distance Test (GDT_TS) measure to quantify prediction performance since CASP3 in 1998. However, identifying significant score differences between close models is difficult because of the lack of uncertainty estimations for this measure. Here, we utilized the atomic fluctuations caused by structure flexibility to estimate the uncertainty of GDT_TS scores. Structures determined by nuclear magnetic resonance are deposited as ensembles of alternative conformers that reflect the structural flexibility, whereas standard X-ray refinement produces the static structure averaged over time and space for the dynamic ensembles. To recapitulate the structural heterogeneous ensemble in the crystal lattice, we performed time-averaged refinement for X-ray datasets to generate structural ensembles for our GDT_TS uncertainty analysis. Using those generated ensembles, our study demonstrates that the time-averaged refinements produced structure ensembles with better agreement with the experimental datasets than the averaged X-ray structures with B-factors. The uncertainty of the GDT_TS scores, quantified by their standard deviations (SDs), increases for scores lower than 50 and 70, with maximum SDs of 0.3 and 1.23 for X-ray and NMR structures, respectively. We also applied our procedure to the high accuracy version of GDT-based score and produced similar results with slightly higher SDs. To facilitate score comparisons by the community, we developed a user-friendly web server that produces structure ensembles for NMR and X-ray structures and is accessible at http://prodata.swmed.edu/SEnCS. Our work helps to identify the significance of GDT_TS score differences, as well as to provide structure ensembles for estimating SDs of any scores.
url http://europepmc.org/articles/PMC4858170?pdf=render
work_keys_str_mv AT wenlinli estimationofuncertaintiesintheglobaldistancetestgdttsforcaspmodels
AT rdustinschaeffer estimationofuncertaintiesintheglobaldistancetestgdttsforcaspmodels
AT zbyszekotwinowski estimationofuncertaintiesintheglobaldistancetestgdttsforcaspmodels
AT nickvgrishin estimationofuncertaintiesintheglobaldistancetestgdttsforcaspmodels
_version_ 1724982747041103872