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Structure and thermodynamics of transient protein-protein complexes by chemometric decomposition of SAXS datasets.

Authors :
Sagar, Amin
Herranz-Trillo, Fátima
Langkilde, Annette Eva
Vestergaard, Bente
Bernadó, Pau
Source :
Structure. Sep2021, Vol. 29 Issue 9, p1074-1074. 1p.
Publication Year :
2021

Abstract

Transient biomolecular interactions play crucial roles in many cellular signaling and regulation processes. However, deciphering the structure of these assemblies is challenging owing to the difficulties in isolating complexes from the individual partners. The additive nature of small-angle X-ray scattering (SAXS) data allows for probing the species present in these mixtures, but decomposition into structural and thermodynamic information is difficult. We present a chemometric approach enabling the decomposition of titration SAXS data into species-specific information. Using extensive synthetic SAXS data, we demonstrate that robust decomposition can be achieved for titrations with a maximum fraction of complex of 0.5 that can be extended to 0.3 when two orthogonal titrations are simultaneously analyzed. The effect of the structural features, titration points, relative concentrations, and noise are thoroughly analyzed. The validation of the strategy with experimental data highlights the power of the approach to provide unique insights into this family of biomolecular assemblies. [Display omitted] • Polydispersity hampers the structure elucidation of transient biomolecular complexes • COSMiCS enables the chemometric decomposition of multiple-titration SAXS datasets • Complexes reaching molar fractions of 0.3 are reliably decomposed with two titrations • Method robust to the number of SAXS curves, signal-to-noise, and structural features Despite their biological relevance, structural details of transient biomolecular complexes are difficult to obtain. Sagar et al. present COSMiCS, a chemometric routine to decompose titration SAXS datasets and derive the structure and thermodynamic information of weak complexes. Analyses of experimental and synthetic data define its power and limits. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09692126
Volume :
29
Issue :
9
Database :
Academic Search Index
Journal :
Structure
Publication Type :
Academic Journal
Accession number :
152162185
Full Text :
https://doi.org/10.1016/j.str.2021.03.017