Centre de Biologie Structurale (CBS), Université de Montpellier, INSERM, CNRS, Montpellier, France.
Methods Enzymol. 2022;677:531-555. doi: 10.1016/bs.mie.2022.08.038. Epub 2022 Oct 26.
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.
多分散体系由多种共存的物种或构象组成,其结构特征用经典方法来表征极具挑战性甚至是不可能的。因此,与蛋白质折叠、瞬态伴侣识别、构象转变或纤维形成相关的问题的结构基础仍了解甚少。小角散射 (SAS) 技术以群体加权的方式在溶液中探测存在的物种,从而能够检测多分散体系。然而,要从这些数据中分解出各个组分的贡献并不容易,需要获取大量的 SAS 数据集和适应性的数学工具。在这里,我们提供了一个详细的程序,介绍如何使用程序 COSMiCS 来分解 SAS 数据集。COSMiCS 将流行的 MCR-ALS 化学计量学例程适配到散射数据的特点上。通过使用多个 SAS 表示、数据的适当缩放以及同时分解多个正交数据集的可能性,COSMiCS 可以有效地分离混合物,并提供所研究过程的特定物种的结构和热力学/动力学信息。尽管该程序是针对瞬态生物分子相互作用进行了举例说明,但我们的化学计量学策略可以应用于许多其他可以在最新一代 SAS 光束线上直接探测的生物学过程。事实上,包括微流控和停流装置在内的最新实验装置,与快速读取探测器相结合,可以产生大浓度或时变数据集,这些数据集可以用 COSMiCS 来分解。重要的是,作为一个开源代码,系统中已知的特征可以作为优化中的约束条件引入,从而为越来越复杂的生物系统产生稳健的解决方案。