Cryo-electron microscopy can now routinely deliver atomic resolution structures for a variety of biological systems. The relevance and value of these structures is directly related to their ability to help rationalize experimental observables, which in turn depends on the quality of model built into the density map. Coupling traditional model building tools with physics-based methods, such as docking, simulation, and modern force fields, has been shown to improve the quality of the resulting structures. Here, we survey the landscape of these hybrid approaches, highlighting their usefulness for medium- and low-resolution datasets, as well as for structures of small molecules, and make the argument that the community stands to benefit from their inclusion in model building and refinement workflows.
@article{arxiv.2509.05517,
title = {Towards better structural models from cryo-electron microscopy data with physics-based methods},
author = {Hande Boyaci Selcuk and Gabriella Reggiano and Jacob Robson-Tull and Lichirui Zhang and João P. G. L. M. Rodrigues},
journal= {arXiv preprint arXiv:2509.05517},
year = {2025}
}