Getting more from low-resolution methods: the combination of SAXS and atomistic molecular simulation

蛋白质的生物学功能不仅取决于原子的空间排列，还取决于其构象景观的动力学。高分辨率方法（X射线晶体学和cryoEM）的分子结构测定揭示了原子的细节，但往往隐藏了功能的关键动力学。另一方面，小角X射线散射（SAXS）提供溶液状态下的结构信息，但分辨率有限。在这个提议中，将开发方法和工具来将联合收割机原子分子模拟与SAXS数据相结合，以将来自SAXS实验的结构信息扩展到更高的分辨率。使用SAXS的蛋白质结构的从头计算建模无法提供完全理解生物功能所需的原子级分辨率的结构。这个建议解决了这个问题。一个重要的问题，影响常规MD模拟与SAXS有关的技术困难运行的计算。每个步骤都需要相关软件的经验。然而，自动化是可能的。我们的Protocaller软件可自动化蛋白质MD模拟的工作流程，以计算配体结合自由能。该软件已被纳入银河生物信息学平台，提高了分子模拟计算方法的可访问性，可共享性和再现性。在这里，我们将扩展该软件，以自动应用先进的MD模拟SAXS数据的结构分析。

A protein's biological function is not only determined by the spatial arrangement of atoms but also by the dynamics of its conformational landscape. Molecular structure determination from high-resolution methods (X-ray crystallography and cryoEM) reveal atomistic details but often hide the dynamics critical to function. Small angle X-ray scattering (SAXS), on the other hand, provides structural information in the solution state, but is limited in terms of resolution. In this proposal, methods and tools will be developed to combine atomistic molecular simulations with SAXS data, to extend the structural information from SAXS experiments to higher resolution. Ab initio modelling of protein structure using SAXS is unable to deliver structures with the atomistic-level resolution required to fully understand biological function. This proposal solves this problem. A significant problem affecting routine MD simulation with SAXS relates to the technical difficulties running the calculations. Each step requires experience in the relevant software. However, automation is possible. Our Protocaller software automates the workflow for protein MD simulations for calculating ligand binding free energies. This software has been incorporated into the Galaxy bioinformatics platform, improving the accessibility, shareability, and reproducibility of computational methods for molecular simulations. Here, we will extend this software to automate the application of advanced MD simulations to the structural analysis of SAXS data.