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Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology

Chemical cross-linking combined with mass spectrometry has proven useful for studying protein-protein interactions and protein structure, however the low density of cross-link data has so far precluded its use in determining structures de novo. Cross-linking density has been typically limited by the...

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Autores principales: Belsom, Adam, Schneider, Michael, Fischer, Lutz, Brock, Oliver, Rappsilber, Juri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Biochemistry and Molecular Biology 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4813692/
https://www.ncbi.nlm.nih.gov/pubmed/26385339
http://dx.doi.org/10.1074/mcp.M115.048504
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author Belsom, Adam
Schneider, Michael
Fischer, Lutz
Brock, Oliver
Rappsilber, Juri
author_facet Belsom, Adam
Schneider, Michael
Fischer, Lutz
Brock, Oliver
Rappsilber, Juri
author_sort Belsom, Adam
collection PubMed
description Chemical cross-linking combined with mass spectrometry has proven useful for studying protein-protein interactions and protein structure, however the low density of cross-link data has so far precluded its use in determining structures de novo. Cross-linking density has been typically limited by the chemical selectivity of the standard cross-linking reagents that are commonly used for protein cross-linking. We have implemented the use of a heterobifunctional cross-linking reagent, sulfosuccinimidyl 4,4′-azipentanoate (sulfo-SDA), combining a traditional sulfo-N-hydroxysuccinimide (sulfo-NHS) ester and a UV photoactivatable diazirine group. This diazirine yields a highly reactive and promiscuous carbene species, the net result being a greatly increased number of cross-links compared with homobifunctional, NHS-based cross-linkers. We present a novel methodology that combines the use of this high density photo-cross-linking data with conformational space search to investigate the structure of human serum albumin domains, from purified samples, and in its native environment, human blood serum. Our approach is able to determine human serum albumin domain structures with good accuracy: root-mean-square deviation to crystal structure are 2.8/5.6/2.9 Å (purified samples) and 4.5/5.9/4.8Å (serum samples) for domains A/B/C for the first selected structure; 2.5/4.9/2.9 Å (purified samples) and 3.5/5.2/3.8 Å (serum samples) for the best out of top five selected structures. Our proof-of-concept study on human serum albumin demonstrates initial potential of our approach for determining the structures of more proteins in the complex biological contexts in which they function and which they may require for correct folding. Data are available via ProteomeXchange with identifier PXD001692.
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spelling pubmed-48136922016-04-11 Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology Belsom, Adam Schneider, Michael Fischer, Lutz Brock, Oliver Rappsilber, Juri Mol Cell Proteomics Regular Articles Chemical cross-linking combined with mass spectrometry has proven useful for studying protein-protein interactions and protein structure, however the low density of cross-link data has so far precluded its use in determining structures de novo. Cross-linking density has been typically limited by the chemical selectivity of the standard cross-linking reagents that are commonly used for protein cross-linking. We have implemented the use of a heterobifunctional cross-linking reagent, sulfosuccinimidyl 4,4′-azipentanoate (sulfo-SDA), combining a traditional sulfo-N-hydroxysuccinimide (sulfo-NHS) ester and a UV photoactivatable diazirine group. This diazirine yields a highly reactive and promiscuous carbene species, the net result being a greatly increased number of cross-links compared with homobifunctional, NHS-based cross-linkers. We present a novel methodology that combines the use of this high density photo-cross-linking data with conformational space search to investigate the structure of human serum albumin domains, from purified samples, and in its native environment, human blood serum. Our approach is able to determine human serum albumin domain structures with good accuracy: root-mean-square deviation to crystal structure are 2.8/5.6/2.9 Å (purified samples) and 4.5/5.9/4.8Å (serum samples) for domains A/B/C for the first selected structure; 2.5/4.9/2.9 Å (purified samples) and 3.5/5.2/3.8 Å (serum samples) for the best out of top five selected structures. Our proof-of-concept study on human serum albumin demonstrates initial potential of our approach for determining the structures of more proteins in the complex biological contexts in which they function and which they may require for correct folding. Data are available via ProteomeXchange with identifier PXD001692. The American Society for Biochemistry and Molecular Biology 2016-03 2015-09-18 /pmc/articles/PMC4813692/ /pubmed/26385339 http://dx.doi.org/10.1074/mcp.M115.048504 Text en © 2016 by The American Society for Biochemistry and Molecular Biology, Inc. Author's Choice—Final version free via Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0) .
spellingShingle Regular Articles
Belsom, Adam
Schneider, Michael
Fischer, Lutz
Brock, Oliver
Rappsilber, Juri
Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology
title Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology
title_full Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology
title_fullStr Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology
title_full_unstemmed Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology
title_short Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology
title_sort serum albumin domain structures in human blood serum by mass spectrometry and computational biology
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4813692/
https://www.ncbi.nlm.nih.gov/pubmed/26385339
http://dx.doi.org/10.1074/mcp.M115.048504
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