A Correspondence Between Solution-State Dynamics of an Individual Protein and the Sequence and Conformational Diversity of its Family

Abstract

Conformational ensembles are increasingly recognized as a useful representation to describe fundamental relationships between protein structure, dynamics and function. Here we present an ensemble of ubiquitin in solution that is created by sampling conformational space without experimental information using “Backrub” motions inspired by alternative conformations observed in sub-Angstrom resolution crystal structures. Backrub-generated structures are then selected to produce an ensemble that optimizes agreement with nuclear magnetic resonance (NMR) Residual Dipolar Couplings (RDCs). Using this ensemble, we probe two proposed relationships between properties of protein ensembles: (i) a link between native-state dynamics and the conformational heterogeneity observed in crystal structures, and (ii) a relation between dynamics of an individual protein and the conformational variability explored by its natural family. We show that the Backrub motional mechanism can simultaneously explore protein native-state dynamics measured by RDCs, encompass the conformational variability present in ubiquitin complex structures and facilitate sampling of conformational and sequence variability matching those occurring in the ubiquitin protein family. Our results thus support an overall relation between protein dynamics and conformational changes enabling sequence changes in evolution. More practically, the presented method can be applied to improve protein design predictions by accounting for intrinsic native-state dynamics.

Author Summary

Knowledge of protein properties is essential for enhancing the understanding and engineering of biological functions. One key property of proteins is their flexibility—their intrinsic ability to adopt different conformations. This flexibility can be measured experimentally but the measurements are indirect and computational models are required to interpret them. Here we develop a new computational method for interpreting these measurements of flexibility and use it to create a model of flexibility of the protein ubiquitin. We apply our results to show relationships between the flexibility of one protein and the diversity of structures and amino acid sequences of the protein's evolutionary family. Thus, our results show that more accurate computational modeling of protein flexibility is useful for improving prediction of a broader range of amino acid sequences compatible with a given protein. Our method will be helpful for advancing methods to rationally engineer protein functions by enabling sampling of conformational and sequence diversity similar to that of a protein's evolutionary family.