Abstract

Protein evolution is most commonly studied by analyzing related protein sequences and generating ancestral sequences through Bayesian and Maximum Likelihood methods, and/or by resurrecting ancestral proteins in the lab and performing ligand binding studies to determine function. Structural and dynamic evolution have largely been left out of molecular evolution studies. Here we incorporate both structure and dynamics to elucidate the molecular principles behind the divergence in the evolutionary path of the steroid receptor proteins. We determine the likely structure of three evolutionarily diverged ancestral steroid receptor proteins using the Zipping and Assembly Method with FRODA (ZAMF). Our predictions are within ∼2.7 Å all-atom RMSD of the respective crystal structures of the ancestral steroid receptors. Beyond static structure prediction, a particular feature of ZAMF is that it generates protein dynamics information. We investigate the differences in conformational dynamics of diverged proteins by obtaining the most collective motion through essential dynamics. Strikingly, our analysis shows that evolutionarily diverged proteins of the same family do not share the same dynamic subspace, while those sharing the same function are simultaneously clustered together and distant from those, that have functionally diverged. Dynamic analysis also enables those mutations that most affect dynamics to be identified. It correctly predicts all mutations (functional and permissive) necessary to evolve new function and ∼60% of permissive mutations necessary to recover ancestral function.

Highlights

  • Proteins are effective and efficient machines that carry out a wide range of essential biochemical functions in the cell

  • Biochemical diversity has grown over time via molecular evolution

  • The one sequence - one structure - one function paradigm is being extended to a new view: an ensemble of different conformations in equilibrium can evolve new function and the analysis of inherent structural dynamics is crucial to give a more complete understanding of protein evolution

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Summary

Introduction

Proteins are effective and efficient machines that carry out a wide range of essential biochemical functions in the cell. Beyond being robust and efficient, the outstanding property of proteins is that they can evolve and they show a remarkable capacity to acquire new functions and structures. The emergence of drug resistance and enzymes with the capacity to degrade new chemicals indicates the ongoing contemporary evolution of proteins [1,2,3,4,5,6,7]. Understanding the mechanism by which mutations lead to functional diversity is critical in many aspects from protein engineering to drug design and personalized medicine. There are computational bioinformatics-based tools based on evolutionary information aspects to identify mutations leading to functional loss or disease [15,16,17]

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