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Abstract:
Advances in structural biology, particularly cryo-electron microscopy, have enabled high-resolution characterization of complex protein assemblies. These developments underscore the need for computational approaches capable of describing biologically relevant conformational changes over extended timescales. GōMartini 3 is a coarse-grained approach that demonstrates computational efficiency and versatility across several systems, from membrane-binding proteins and soluble proteins to intrinsically disordered proteins, while preserving key physicochemical features. In this work, we introduce an optimized approach that integrates dynamic contact information from all-atom molecular dynamics (AA-MD) simulations to refine the contact map in GōMartini simulations and select the AA-MD structure consistent with the refined map. Specifically, we define high-frequency contacts, which reduce the number of original Gō contact set by ≈20%–30%, thereby improving the representation of conformational states beyond the original approach in Martini 3. Benchmarking different contact selection criteria revealed that including intra- and interchain high-frequency contacts in protein assemblies captures structural flexibility and domain dynamics. The method was tested on single-chain globular proteins and on the SARS-CoV-2 spike protein. Overall, the optimized contact map improves sampling efficiency and expands the accessible conformational landscape. The full framework is available as an open-source tool for large-scale simulations of protein assemblies.

Keywords:
GōMartini 3 , Molecular Simulation, Proteins, Biomolecular Ensemble, Free Energy, Coarse-graining, cryo-electron microscopy