Analysis of Protein Structure by Cross-Linking Combined with Mass Spectrometry

2014 ◽  
pp. 447-463 ◽  
Author(s):  
Evgeniy V. Petrotchenko ◽  
Karl A. T. Makepeace ◽  
Jason J. Serpa ◽  
Christoph H. Borchers
Keyword(s):  
Mass Spectrometry ◽  
Protein Structure ◽  
Cross Linking

In plantachemical cross-linking and mass spectrometry analysis of protein structure and interaction in Arabidopsis

PROTEOMICS ◽  
2016 ◽  
Vol 16 (13) ◽  
pp. 1915-1927 ◽  
Author(s):  
Xinliang Zhu ◽  
Fengchao Yu ◽  
Zhu Yang ◽  
Shichang Liu ◽  
Chen Dai ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Structure ◽  
Mass Spectrometry Analysis ◽  
Cross Linking ◽  
Spectrometry Analysis

scholarly journals Blind testing cross-linking/mass spectrometry under the auspices of the 11th critical assessment of methods of protein structure prediction (CASP11)

2016 ◽  
Vol 1 ◽  
pp. 24 ◽  
Author(s):  
Adam Belsom ◽  
Michael Schneider ◽  
Lutz Fischer ◽  
Mahmoud Mabrouk ◽  
Kolja Stahl ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Structure ◽  
Crystal Structures ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Hybrid Approach ◽  
Critical Assessment ◽  
Cross Linking ◽  
Blind Test ◽  
Contact Data

Determining the structure of a protein by any method requires various contributions from experimental and computational sides. In a recent study, high-density cross-linking/mass spectrometry (HD-CLMS) data in combination with ab initio structure prediction determined the structure of human serum albumin (HSA) domains, with an RMSD to X-ray structure of up to 2.5 Å, or 3.4 Å in the context of blood serum. This paper reports the blind test on the readiness of this technology through the help of Critical Assessment of protein Structure Prediction (CASP). We identified between 201-381 unique residue pairs at an estimated 5% FDR (at link level albeit with missing site assignment precision evaluation), for four target proteins. HD-CLMS proved reliable once crystal structures were released. However, improvements in structure prediction using cross-link data were slight. We identified two reasons for this. Spread of cross-links along the protein sequence and the tightness of the spatial constraints must be improved. However, for the selected targets even ideal contact data derived from crystal structures did not allow modellers to arrive at the observed structure. Consequently, the progress of HD-CLMS in conjunction with computational modeling methods as a structure determination method, depends on advances on both arms of this hybrid approach.

scholarly journals Blind testing cross-linking/mass spectrometry under the auspices of the 11th critical assessment of methods of protein structure prediction (CASP11)

2016 ◽  
Author(s):  
Adam Belsom ◽  
Michael Schneider ◽  
Lutz Fischer ◽  
Oliver Brock ◽  
Juri Rappsilber
Keyword(s):  
Mass Spectrometry ◽  
Protein Structure ◽  
Human Serum Albumin ◽  
Serum Albumin ◽  
Human Serum ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Critical Assessment ◽  
Conformational Space ◽  
Cross Linking

SummaryDetermining the structure of a protein by any method requires varies contributions from experimental and computational sides. In a recent study, high-density cross-linking/mass spectrometry data in combination with ab initio structure prediction by conformational space search determined the structure of human serum albumin (HSA) domains, with an RMSD to X-ray structure of up to 2.53 Å, or 3.38 Å in the context of blood serum. This paper reports the blind test on the readiness of this technology through the help of Critical Assessment of protein Structure Prediction (CASP). We identified between 201-381 unique residue pairs at an estimated 5% FDR (at link level albeit with missing site assignment precision evaluation), for the four proteins that we provided data for. This equates to between 0.63-1.20 proximal residues per residue, which is comparable to that obtained in the HSA study (0.85 links per residue at 5% FDR). Nevertheless, initial results of CASP11 have suggested that improvements in structure prediction using cross-link data are slight. Most significantly, however, CASP11 revealed to us some of the current limitations of cross-linking, spelling out areas in which the method must develop in future: links spread unevenly over sequence and beta sheets both lacked links and suffered from weak definition of observed links over structure. With CASP12 taking place this year and biannually in the future, blind testing low-resolution structure analysis tools is a worthwhile and feasible undertaking. Data are available via ProteomeXchange with identifier PXD003643.The abbreviations used areCLMScross-linking/mass spectrometry;NHSN-hydroxysuccinimide;NMRnuclear magnetic resonance;sulfo-SDAsulfo-NHSdiazirine, sulfosuccinimidyl 4,4’-azipentanoate;FDRfalse discovery rate;MBSmodel-based search;HSAhuman serum albumin;RMSDroot-mean-square deviation;CASPCritical Assessment of protein Structure Prediction;Tristris(hydroxymethyl)aminomethane;PESpolyethersulphone;IAAiodoacetamide;LTQlinear trap quadrupole;MS2tandem MS scan;LC-MSliquid chromatography mass spectrometry;FMfree modelling.

Statistical Force-Field for Structural Modeling Using Chemical Cross-Linking/mass Spectrometry Distance Constraints

2018 ◽  
Author(s):  
Allan J. R. Ferrari ◽  
Fabio C. Gozzo ◽  
Leandro Martinez
Keyword(s):  
Mass Spectrometry ◽  
Amino Acid ◽  
Force Field ◽  
Protein Structures ◽  
Protein Structure Determination ◽  
Structural Modeling ◽  
Cross Linking ◽  
Amino Acid Residues ◽  
Distance Constraints ◽  
Chemical Cross Linking

<div><p>Chemical cross-linking/Mass Spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues, which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms. Here, a force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. The force-field can be easily incorporated into current modeling methods and software. In this work, the force-field was implemented within the Rosetta ab initio relax protocol. We show a significant improvement in the quality of the models obtained relative to current strategies for constraint representation. This force-field contributes to the long-desired goal of obtaining the tertiary structures of proteins using XLMS data. Force-field parameters and usage instructions are freely available at http://m3g.iqm.unicamp.br/topolink/xlff <br></p></div><p></p><p></p>

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