MSBack: Multiscale Backmapping of Highly Coarse-grained Proteins Using Constrained Diffusion

Coarse-grained (CG)molecular dynamics is a powerful tool for simulating the collective behavior of biomolecules. However, the structural information lost during coarse-graining prevents the CG configurations from being more widely useful (e.g., for ligand binding). Regenerating the lost allatom coordinates, or backmapping, is an unmet challenge for proteins CG at resolutions lower than one coarse-grain site or bead per amino acid residue. This low resolution is computationally necessary to simulate many protein complexes including viruses like SARS-CoV-2 and HIV-1. We propose, MSBack, a method to backmap highly CG proteins using a diffusion model for the all-atom coordinates constrained to fit the CG coordinates. This diffusion process works by perturbing a known all-atom structure and does not require re-training. We show this stochastically generates a distribution of alpha carbon traces which match the CG coordinates. By combining this with physics-based methods for smaller length backmapping, we fully backmap a mature HIV-1 capsid bound with the small molecule inositol hexakisophosphate at 1Å resolution.