High-resolution coarse-grained modeling using oriented coarse-grained sites

TL;DR

This paper presents a high-resolution coarse-grained protein modeling method that retains nearly atomistic detail by assigning orientations to coarse-grained sites, enabling accurate backmapping with minimal information loss.

Contribution

The authors introduce an oriented coarse-grained modeling approach that significantly improves resolution and accuracy in protein simulations compared to traditional methods.

Findings

Heavy atoms move only 0.051 Å on average during backmapping.

Hydrogens move only 0.179 Å on average, indicating high accuracy.

The method achieves a 4:1 reduction in degrees of freedom with minimal loss of detail.

Abstract

We introduce a method to bring nearly atomistic resolution to coarse-grained models, and we apply the method to proteins. Using a small number of coarse-grained sites (about one per eight atoms) but assigning an independent three-dimensional orientation to each site, we preferentially integrate out stiff degrees of freedom (bond lengths and angles, as well as dihedral angles in rings) that are accurately approximated by their average values, while retaining soft degrees of freedom (unconstrained dihedral angles) mostly responsible for conformational variability. We demonstrate that our scheme retains nearly atomistic resolution by mapping all experimental protein configurations in the Protein Data Bank onto coarse-grained configurations, then analytically backmapping those configurations back to all-atom configurations. This roundtrip mapping throws away all information associated with the eliminated (stiff) degrees of freedom except for their average values, which we use to construct optimal backmapping functions. Despite the 4:1 reduction in the number of degrees of freedom, we find that heavy atoms move only 0.051 angstroms on average during the roundtrip mapping, while hydrogens move 0.179 angstroms on average, an unprecedented combination of efficiency and accuracy among coarse-grained protein models. We discuss the advantages of such a high-resolution model for parameterizing effective interactions and accurately calculating observables through direct or multiscale simulations.