# Predicting evolutionary site variability from structure in viral proteins: buriedness, flexibility, and design

## TL;DR

This study shows that buriedness and packing density in viral protein structures better predict evolutionary sequence variation than other structural properties like flexibility.

## Contribution

The study compares multiple structural properties to determine which best predict evolutionary site variability in viral proteins.

## Key findings

- Buriedness and packing density are better predictors of evolutionary variation than structural flexibility.
- Variability in designed structures is a weaker predictor than buriedness or packing density.
- Dynamic simulations and homologous structure ensembles provide less predictive power than simple buriedness measures.

## Abstract

Several recent works have shown that protein structure can predict site-specific evolutionary sequence variation. In particular, sites that are buried and/or have many contacts with other sites in a structure have been shown to evolve more slowly, on average, than surface sites with few contacts. Here, we present a comprehensive study of the extent to which numerous structural properties can predict sequence variation. The structural properties we considered include buriedness (relative solvent accessibility and contact number), structural flexibility (B factors, root-mean-square fluctuations, and variation in dihedral angles), and variability in designed structures. We obtained structural flexibility measures both from molecular dynamics simulations performed on 9 non-homologous viral protein structures and from variation in homologous variants of those proteins, where available. We obtained measures of variability in designed structures from flexible-backbone design in the Rosetta software. We found that most of the structural properties correlate with site variation in the majority of structures, though the correlations are generally weak (correlation coefficients of 0.1 to 0.4). Moreover, we found that measures of buriedness were better predictors of evolutionary variation than were measures of structural flexibility. Finally, variability in designed structures was a weaker predictor of evolutionary variability than was buriedness, but was comparable in its predictive power to the best structural flexibility measures. We conclude that simple measures of buriedness are better predictors of evolutionary variation than are more complicated predictors obtained from dynamic simulations, ensembles of homologous structures, or computational protein design.