MSBack: Multiscale Backmapping of Highly Coarse-Grained Proteins Using Constrained Diffusion
Curt Waltmann1, Yihang Wang1, Chengxi Yang
1Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, Illinois 60637, United States.
Journal of Chemical Theory and Computation
|June 2, 2025
Summary
We developed MSBack, a novel diffusion model method to reconstruct all-atom protein structures from coarse-grained models. This advances biomolecular simulation and structural analysis for complexes like viruses.
Area of Science:
- Biophysics
- Computational Biology
- Structural Biology
Background:
- Coarse-grained (CG) molecular dynamics simulates biomolecular behavior but loses structural detail.
- Backmapping CG models to all-atom resolution is challenging, especially at low resolutions (less than one site per residue).
- Low-resolution CG models are crucial for simulating large complexes like viruses (e.g., SARS-CoV-2, HIV-1).
Purpose of the Study:
- To develop a method for accurate all-atom reconstruction from highly coarse-grained protein structures.
- To address the unmet challenge of backmapping proteins at resolutions below one site per residue.
- To enable detailed structural analysis of large biomolecular complexes.
Main Methods:
- Proposed MSBack, a diffusion model approach for backmapping.
- Constrained the diffusion process to fit all-atom coordinates to CG coordinates.
- Utilized perturbation of existing all-atom structures without retraining.
- Integrated physics-based methods for fine-grained backmapping.
Main Results:
- MSBack stochastically generates alpha-carbon traces matching CG coordinates.
- Successfully demonstrated full backmapping of a mature HIV-1 capsid.
- Achieved 1 Å resolution for the backmapped HIV-1 capsid structure.
- The method is applicable to proteins simulated at resolutions necessary for large complexes.
Conclusions:
- MSBack effectively reconstructs all-atom protein structures from low-resolution CG models.
- This method overcomes limitations in current backmapping techniques.
- Enables detailed structural insights into large biomolecular systems and their interactions.
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