2026/06/04 by Carl G. Henning Hansen, Simone Orioli, Kresten Lindorff‐Larsen +1 · 1 voice
Biochemistry, Genetics and Molecular Biology · Chemistry · Computer Science · Materials Science · #Advanced Physical and Chemical Molecular Interactions #Computational Drug Discovery Methods #Enzyme Structure and Function #Metabolomics and Mass Spectrometry Studies #Protein Structure and Dynamics #Various Chemistry Research Topics
paper · doi:10.1021/acsphyschemau.6c00050
openalex publication_date 2026/06/04 · openalex created_date 2026/06/05 · openalex updated_date 2026/07/27
Time-resolved experiments can provide unique insights into dynamic 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 three-dimensional 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 measurements about the process of protein unfolding.