skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Protein structure prediction guided by crosslinking restraints – A systematic evaluation of the impact of the crosslinking spacer length

Abstract

Recent development of high-resolution mass spectrometry (MS) instruments enables chemical crosslinking (XL) to become a high-throughput method for obtaining structural information about proteins. Restraints derived from XL-MS experiments have been used successfully for structure refinement and protein–protein docking. However, one formidable question is under which circumstances XL-MS data might be sufficient to determine a protein’s tertiary structure de novo? Answering this question will not only include understanding the impact of XL-MS data on sampling and scoring within a de novo protein structure prediction algorithm, it must also determine an optimal crosslinker type and length for protein structure determination. While a longer crosslinker will yield more restraints, the value of each restraint for protein structure prediction decreases as the restraint is consistent with a larger conformational space. In this study, the number of crosslinks and their discriminative power was systematically analyzed in silico on a set of 2055 non-redundant protein folds considering Lys–Lys, Lys–Asp, Lys–Glu, Cys–Cys, and Arg–Arg reactive crosslinkers between 1 and 60 Å. Depending on the protein size a heuristic was developed that determines the optimal crosslinker length. Next, simulated restraints of variable length were used to de novo predict the tertiary structure of fifteen proteins using the BCL::Foldmore » algorithm. The results demonstrate that a distinct crosslinker length exists for which information content for de novo protein structure prediction is maximized. The sampling accuracy improves on average by 1.0 Å and up to 2.2 Å in the most prominent example. XL-MS restraints enable consistently an improved selection of native-like models with an average enrichment of 2.1.« less

Authors:
; ; ;
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); UT-Battelle LLC/ORNL, Oak Ridge, TN (Unted States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1565442
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Journal Article
Journal Name:
Methods
Additional Journal Information:
Journal Volume: 89; Journal Issue: C; Journal ID: ISSN 1046-2023
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
Biochemistry & Molecular Biology

Citation Formats

Hofmann, Tommy, Fischer, Axel W., Meiler, Jens, and Kalkhof, Stefan. Protein structure prediction guided by crosslinking restraints – A systematic evaluation of the impact of the crosslinking spacer length. United States: N. p., 2015. Web. doi:10.1016/j.ymeth.2015.05.014.
Hofmann, Tommy, Fischer, Axel W., Meiler, Jens, & Kalkhof, Stefan. Protein structure prediction guided by crosslinking restraints – A systematic evaluation of the impact of the crosslinking spacer length. United States. doi:10.1016/j.ymeth.2015.05.014.
Hofmann, Tommy, Fischer, Axel W., Meiler, Jens, and Kalkhof, Stefan. Sun . "Protein structure prediction guided by crosslinking restraints – A systematic evaluation of the impact of the crosslinking spacer length". United States. doi:10.1016/j.ymeth.2015.05.014.
@article{osti_1565442,
title = {Protein structure prediction guided by crosslinking restraints – A systematic evaluation of the impact of the crosslinking spacer length},
author = {Hofmann, Tommy and Fischer, Axel W. and Meiler, Jens and Kalkhof, Stefan},
abstractNote = {Recent development of high-resolution mass spectrometry (MS) instruments enables chemical crosslinking (XL) to become a high-throughput method for obtaining structural information about proteins. Restraints derived from XL-MS experiments have been used successfully for structure refinement and protein–protein docking. However, one formidable question is under which circumstances XL-MS data might be sufficient to determine a protein’s tertiary structure de novo? Answering this question will not only include understanding the impact of XL-MS data on sampling and scoring within a de novo protein structure prediction algorithm, it must also determine an optimal crosslinker type and length for protein structure determination. While a longer crosslinker will yield more restraints, the value of each restraint for protein structure prediction decreases as the restraint is consistent with a larger conformational space. In this study, the number of crosslinks and their discriminative power was systematically analyzed in silico on a set of 2055 non-redundant protein folds considering Lys–Lys, Lys–Asp, Lys–Glu, Cys–Cys, and Arg–Arg reactive crosslinkers between 1 and 60 Å. Depending on the protein size a heuristic was developed that determines the optimal crosslinker length. Next, simulated restraints of variable length were used to de novo predict the tertiary structure of fifteen proteins using the BCL::Fold algorithm. The results demonstrate that a distinct crosslinker length exists for which information content for de novo protein structure prediction is maximized. The sampling accuracy improves on average by 1.0 Å and up to 2.2 Å in the most prominent example. XL-MS restraints enable consistently an improved selection of native-like models with an average enrichment of 2.1.},
doi = {10.1016/j.ymeth.2015.05.014},
journal = {Methods},
issn = {1046-2023},
number = C,
volume = 89,
place = {United States},
year = {2015},
month = {11}
}