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Frontiers of Engineering Reports on Leading-Edge Engineering from the 2007 Symposium (2008) / Chapter Skim
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The Evolutionary Design of Proteins--Rama Ranganathan
Pages 33-38

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From page 33...
... This curious mixture of robustness at many sites and fragility at a few sites is interesting since it suggests that despite homogeneously good atomic packing, strong heterogeneity exists in the energetic interactions between amino acids that underlie structural stability and function. A major advance in our understanding of proteins would come with the development of methods to systematically map and then mechanistically understand the global architecture of amino acid interactions.
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From page 34...
... However, the problem is truly complex; amino acids make unequal and cooperative contributions to protein structure and function, and these contributions are generally not obvious in even high-resolution atomic structures. For example, studies of the interaction between the human growth hormone and its receptor show that the binding interface contains "hot spots" of favorable energetic interactions embedded within an overall environment of neutral interactions (Clarkson and Wells, 1995)
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From page 35...
... the strongly co-evolving residues are spatially organized into physically connected networks linking distant functional sites in the structure through packing interactions. Importantly, mutagenesis experiments directed by the SCA mapping show strong correlations between the predictions and experimental measurements, implicating the co-evolving networks as hot spots for functional mechanism.
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From page 36...
... CC45 shows 35 percent mean identity and 61 percent top-hit identity with natural WW domains. two conserved tryptophan residues, the computational method produces artificial sequences that in fact efficiently fold into the characteristic WW domain structure (Figure 2)
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From page 37...
... why is the SCA-predicted architecture a good solution for specifying protein structure and function through evolution? In essence the goal is to ultimately connect the mechanism-free description of statistical interactions between amino acids with a mechanistic model for the physics of these interactions and with an underlying evolutionary theory.
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Key Terms

  • acid interactions
  • amino acids
  • protein family
  • artificial sequences
  • protein structure

  • protein families
  • evolutionary design
  • computational method
  • evolutionarily coupled
  • designed sequences

  • energetic interactions
  • characteristic function
  • order statistics
  • information extracted
  • signal transmission

  • sequence variation
  • crystal structure
  • global pattern
  • acid protein
  • estimating amino

  • artificial amino
  • binding studies
  • evolutionary theory
  • specific sequence
  • atomic packing

  • evolutionary process
  • energetic architecture
  • interactions revealed
  • neutral interactions
  • favorable energetic


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