ArticleBiophysical journal2026
An optimized contact map for GōMartini 3 enabling conformational changes in protein assemblies.
Article in Biophysical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- MartiniSurf: Automated Simulations of Surface-Immobilized Biomolecular Systems with Martini.Journal of chemical information and modeling · 2026Article
- Improving Conformational Ensembles of Folded Proteins in Go̅Martini.Journal of chemical theory and computation · 2026Article
- Mechanistic Determinants of Oriented Enzyme Immobilization from Martini Simulations.The journal of physical chemistry letters · 2026Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
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.
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