An optimized contact map for GōMartini 3 enabling conformational changes in protein assemblies

Advances in structural biology, particularly through cryo-electron microscopy (cryo-EM), have enabled the high-resolution characterization of increasingly complex biomolecular assemblies. These developments underscore the need for computational methods capable of capturing biologically relevant conformationalchanges over extended timescales. While atomistic molecular dynamics (MD) simulations offer detailed insights at atomic resolution, it is inherently limited to local structural fluctuations and often fails to capture the large-scale transitions commonly observed in biological systems. G ¯oMartini 3 is a coarse-grained (CG) approach that enables the simulation of protein–membrane interactions, protein folding or unfolding under mechanical forces, and intrinsically disordered proteins. This method is well-validated for small protein systems, such as those composed of one or two well-structured chains, but its application to large macromolecular assemblies remains limited. Here, we present an enhanced approach that integrates dynamic contact information from atomistic MD to better capture long-timescale dynamics. Benchmarking different contact selection criteria revealed that incorporating both high-frequency intra- and interchain contacts significantly improves structural flexibility and dynamics of inter-protein domains that is consistent with experiments. We show the capability of this approach in case of SARS-CoV-2 spike protein, composed of ∼3000 residues. The full framework is available as an open-source resource, offering a scalable tool for simulating complex biomolecular assemblies comprising thousands of residuesover timescales reaching hundreds of microseconds. Note: all data generated in this study is presented in this repostory. The trajectories has been saved every 200 ps.