# Residue Interactions Guide Translational Diffusion of Proteins

## TL;DR

This paper introduces a new method to predict how proteins diffuse in a solution by analyzing their molecular structure and chemical properties.

## Contribution

A novel approach for estimating translational diffusion coefficients using residue-level chemical information and surface area calculations.

## Key findings

- The new method produces diffusion coefficient predictions comparable to explicit molecular simulations.
- The approach outperforms statistical mass-based predictions by incorporating chemical identity.
- It can distinguish diffusivity differences in structures that are indistinguishable by mass alone.

## Abstract

Diffusion at the molecular level involves random collisions
between
particles, the structure of local microscopic environments, and interactions
among the molecules involved. Sampling all of these aspects, along
with correcting for finite-size effects, can make the calculation
of infinitely dilute diffusion coefficients computationally difficult.
We present a new approach for estimating the translational diffusion
coefficient of biomolecular structures by encapsulating these driving
forces of diffusion through piecewise assembly of the component residues
of the protein structure. By linking the local chemistry of a solvent-exposed
patch of a molecule to its contribution to the overall hydrodynamic
radius, an accurate prediction of the computationally and experimentally
comparable diffusion coefficients can be constructed following a solvent-excluded
surface area calculation. We demonstrate that the resulting predictions
for diffusion coefficients from peptides through to protein structures
are comparable to explicit molecular simulations and improve on statistical
mass-based predictions, which tend to rely on limited training data.
As this approach uses the chemical identity of molecular structures,
we find that it is able to predict and identify differences in diffusivity
for structures that would be indistinguishable by mass information
alone.