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

By Adam Belsom, Michael Schneider, L. Fischer, Oliver Brock, Juri Rappsilber. 2015

82 citations recorded by the source corpus.

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.

Subfields: Cell Biology, Spectroscopy

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cell Biology

In Spectroscopy

Citations in the corpus

Assessment of chemical-crosslink-assisted protein structure modeling in CASP13 (2019, methodology): “9 This approach provided the first experimental data in CASP history, in CASP11, in the form of high-density XL-MS (HD-XL-MS) data 4,10,23 and has been subsequently reused for targets in CASP12 11 and in the present study for CASP13.”
Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13 (2020, background): “This semispecificity has been shown to allow greater data density, which can be beneficial for protein structure prediction.(9) This approach provided the first experimental data in CASP history, in CASP11, in the form of high-density XL-MS (HD-XL-MS) data(4,10,23) and has been subsequently reused f”
Small angle X-ray scattering and cross-linking for data assisted protein structure prediction in CASP 12 with prospects for improved accuracy (2018, methodology): “10,11 This high-density CLMS data can then be combined with computational biology, to produce accurate protein structure models (up to 2.5 Å, RMSD to X-ray crystal structure).”
Blind testing of cross‐linking/mass spectrometry hybrid methods in CASP11 (2016, background): “In another study on human serum albumin, we find that using cross-links at 10–20% FDR leads to lower RMSD ensembles than 1–5% FDR.17 We speculate that structure prediction algorithms that are robust to noise would enable the use of cross-link restraints at even higher FDR, which would increase the n”