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Investigating Homology between Proteins using Energetic Profiles

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  • James O Wrabl
  • Vincent J Hilser

Abstract

Accumulated experimental observations demonstrate that protein stability is often preserved upon conservative point mutation. In contrast, less is known about the effects of large sequence or structure changes on the stability of a particular fold. Almost completely unknown is the degree to which stability of different regions of a protein is generally preserved throughout evolution. In this work, these questions are addressed through thermodynamic analysis of a large representative sample of protein fold space based on remote, yet accepted, homology. More than 3,000 proteins were computationally analyzed using the structural-thermodynamic algorithm COREX/BEST. Estimated position-specific stability (i.e., local Gibbs free energy of folding) and its component enthalpy and entropy were quantitatively compared between all proteins in the sample according to all-vs.-all pairwise structural alignment. It was discovered that the local stabilities of homologous pairs were significantly more correlated than those of non-homologous pairs, indicating that local stability was indeed generally conserved throughout evolution. However, the position-specific enthalpy and entropy underlying stability were less correlated, suggesting that the overall regional stability of a protein was more important than the thermodynamic mechanism utilized to achieve that stability. Finally, two different types of statistically exceptional evolutionary structure-thermodynamic relationships were noted. First, many homologous proteins contained regions of similar thermodynamics despite localized structure change, suggesting a thermodynamic mechanism enabling evolutionary fold change. Second, some homologous proteins with extremely similar structures nonetheless exhibited different local stabilities, a phenomenon previously observed experimentally in this laboratory. These two observations, in conjunction with the principal conclusion that homologous proteins generally conserved local stability, may provide guidance for a future thermodynamically informed classification of protein homology.Author Summary: Protein structure and function are fundamentally determined by thermodynamics. However, for technical as well as historical reasons, current evolutionary classification schemes and bioinformatics tools do not fully utilize thermodynamic information to describe or analyze proteins. In this work, we address this deficiency by computationally estimating the position-specific thermodynamic quantities of stability (ΔG), enthalpy (ΔH), and entropy (TΔS) for a large and diverse representative sample of protein structures. The sample was drawn from an expertly curated database, such that accepted evolutionary relationships existed for all protein pairs. Importantly, trivial relationships between pairs highly similar in amino acid sequence were explicitly excluded. We found that all position-specific thermodynamic quantities ΔG, ΔH, and TΔS were more similar between proteins that were evolutionarily related (i.e., homologous), and were less similar between proteins that were not evolutionarily related (i.e., non-homologous), with stability being particularly similar between homologous proteins. However, interesting statistically significant exceptions to these trends were observed, exceptions that could indicate novel processes of functional adaptation or evolutionary fold change, mediated by thermodynamics, for the proteins involved. Taken together, these results expand our understanding of the role of thermodynamics in protein evolution and suggest an organizational framework for a future thermodynamically-informed classification of protein homology.

Suggested Citation

  • James O Wrabl & Vincent J Hilser, 2010. "Investigating Homology between Proteins using Energetic Profiles," PLOS Computational Biology, Public Library of Science, vol. 6(3), pages 1-17, March.
  • Handle: RePEc:plo:pcbi00:1000722
    DOI: 10.1371/journal.pcbi.1000722
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    References listed on IDEAS

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    1. Alberto Pascual-García & David Abia & Ángel R Ortiz & Ugo Bastolla, 2009. "Cross-Over between Discrete and Continuous Protein Structure Space: Insights into Automatic Classification and Networks of Protein Structures," PLOS Computational Biology, Public Library of Science, vol. 5(3), pages 1-20, March.
    2. Katherine A. Henzler-Wildman & Ming Lei & Vu Thai & S. Jordan Kerns & Martin Karplus & Dorothee Kern, 2007. "A hierarchy of timescales in protein dynamics is linked to enzyme catalysis," Nature, Nature, vol. 450(7171), pages 913-916, December.
    3. Andrew L. Lee & A. Joshua Wand, 2001. "Microscopic origins of entropy, heat capacity and the glass transition in proteins," Nature, Nature, vol. 411(6836), pages 501-504, May.
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