Disentangling polydisperse biomolecular systems by Chemometrics decomposition of SAS data

The structural characterization of polydisperse systems consisting of multiple coexisting species or conformations is very challenging or impossible with classical approaches. As a consequence, the structural bases of relevant questions related to protein folding, transient partner recognition, conformational transitions or fibrillation remain poorly understood. Small-Angle Scattering (SAS) techniques structurally probe species present in solution in a population-weighted manner, enabling the inspection of polydisperse systems. However, decomposition of these data to derive the contribution of individual components is not straightforward and requires the acquisition of large SAS datasets and adapted mathematical tools. Here, we present a detailed procedure for the usage of the program COSMiCS for the decomposition of SAS datasets. COSMiCS adapts the popular MCR-ALS chemometrics routine to the specificities of scattering data. Through the use of multiple SAS representations, the appropriate scaling of the data and the possibility to simultaneously decompose multiple orthogonal datasets, COSMiCS efficiently disentangles mixtures and provides species-specific structural and thermodynamic/kinetic information of the process under investigation. Although exemplified for a transient biomolecular interaction, our chemometrics strategy can be applied to many other biological processes that can be straightforwardly probed in last generation SAS beamlines. Indeed, recent experimental setups, including microfluidics and stop-flow devices, coupled to fast-reading detectors can yield large concentration or time-dependent datasets that can be decomposed with COSMiCS. Importantly, as an open-source code, previously known features of the system of interest can be introduced as constraints in the optimization, producing robust solutions for biological systems of increasing complexity.