Henning Hansen, C. G. | Search bioRxiv

bioRxiv2025

A Bayesian approach to interpret time-resolved experiments using molecular simulations

Time-resolved experiments can provide unique insights into dynamical processes such as protein folding, ligand binding, and many other molecular processes. These experiments are, however, difficult to interpret at the molecular level because they generally report on signals that are averaged over multiple configurational states, and because they often report on processes that are well beyond what can be studied using most simulation methods. Here we describe an approach to use molecular simulations to model and interpret time-resolved experiments. The method, which we term trBME (time-resolved Bayesian/Maximum Entropy), is based on combining a model for the dynamics of the system, with 3D structural models of the protein that can be compared to the experiments. We illustrate the utility of the model using synthetic time-resolved small-angle X-ray scattering data and show how it can be used to extract detailed information from the experimental data on the process of protein unfolding.

biophysics↗

bioRxiv2020

Ab-initio determination of the shape of membrane proteins in a nanodisc

We introduce a new software, called Marbles, that employs SAXS intensities to predict the shape of membrane proteins embedded into membrane nanodiscs. To gain computational speed and efficient convergence, the strategy is based on a hybrid approach that allows one to account for the nanodisc contribution to the SAXS intensity through a semi-analytical model, while the embedded membrane protein is treated as set of beads, similarly to well known ab-initio methods. The code, implemented in C++ with a Python user interface, provides a good performance and includes the possibility to systematically treat unstructured domains. We prove the reliability and flexibility of our approach by benchmarking the code on a toy model and two proteins of very different geometry and size.

biophysics↗