Evolution of Protein Structure Degradation and Lessons for the Drug Designer

  • Ariel Fernández Stigliano


Proteins with common ancestry (homologs) typically share a common fold. This structural similarity introduces major problems for drug design since a therapeutic imperative in drug treatment is the control of specificity. As shown in this chapter, while the folding topology of the native structure is highly similar across homologs, the wrapping and expression regulation patterns tend to be different, offering an opportunity to funnel the impact of a drug solely on clinically relevant targets. The evolutionary root of the subtle dissimilarities across homologous proteins is dissected in this chapter both across species and within the human species. As anticipated in this chapter, the wrapping variations across homologs have profound consequences for drug design as we aim at engineering target-specific and species-specific therapeutic agents and build insightful animal models for disease and malignancy. In assessing the evolutionary forces that promote differences in the dehydron patterns across orthologous proteins (homologs from different species), we came across the surprising finding that random genetic drift plays a central role in causing dehydron enrichment. This type of structural degradation promotes higher protein interactivity and is more pronounced in species with low population, such as humans, where mildly deleterious mutations resulting from random drift have a higher probability of getting fixed in the population. The fitness consequences of nature’s evolutionary strategy are assessed for humans, and reveal the high exposure of the human species to fitness catastrophes resulting from aberrant protein aggregation.


Gene Duplication Deleterious Mutation Human Species Orthologous Protein Escape Route 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Fernández A, Scott R, Berry RS (2004) The nonconserved wrapping of conserved folds reveals a trend towards increasing connectivity in proteomic networks. Proc Natl Acad Sci USA 101:2823–2827CrossRefPubMedCentralPubMedGoogle Scholar
  2. 2.
    Fernández A, Berry RS (2004) Molecular dimension explored in evolution to promote proteomic complexity. Proc Natl Acad Sci USA 101:13460–13465CrossRefPubMedCentralPubMedGoogle Scholar
  3. 3.
    Lynch M, Conery JS (2003) The origins of genome complexity. Science 302:1401–1404CrossRefPubMedGoogle Scholar
  4. 4.
    Kondrashov FA, Koonin EV (2004) A common framework for understanding the origin of genetic dominance and evolutionary fates of gene duplications. Trends Genet 20:287–290CrossRefPubMedGoogle Scholar
  5. 5.
    Liang H, Rogale-Plazonic K, Chen J, Li WH, Fernández A (2008) Protein under-wrapping causes dosage sensitivity and decreases gene duplicability. PLoS Genet 4:e11CrossRefPubMedCentralPubMedGoogle Scholar
  6. 6.
    Papp B, Pal C, Hurst LD (2003) Dosage sensitivity and the evolution of gene families in yeast. Nature 424:194–197CrossRefPubMedGoogle Scholar
  7. 7.
    Fernández A, Scheraga H (2003) Insufficiently dehydrated hydrogen bonds as determinants for protein interactions. Proc Natl Acad Sci USA 100:113–118CrossRefPubMedCentralPubMedGoogle Scholar
  8. 8.
    Bartel D (2009) MicroRNAs: target recognition and regulatory functions. Cell 136:215–233CrossRefPubMedCentralPubMedGoogle Scholar
  9. 9.
    Fernández A, Chen J (2009) Human capacitance to dosage imbalance: coping with inefficient selection. Genome Res (in press)Google Scholar
  10. 10.
    Fernández A (2004) Keeping dry and crossing membranes. Nat Biotech 22:1081–1084CrossRefGoogle Scholar
  11. 11.
    Veitia RA (2002) Exploring the etiology of haploinsufficiency. BioEssays 24:175–184CrossRefPubMedGoogle Scholar
  12. 12.
    Veitia RA (2004) Gene dosage balance: deletions, duplications and dominance. Trends Genet 21:33–35CrossRefGoogle Scholar
  13. 13.
    Su AI, Wiltshire T, Batalov S et al (2004) A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci USA 101:6062–6067CrossRefPubMedCentralPubMedGoogle Scholar
  14. 14.
    Birney E, Andrews D, Caccamo M et al (2006) Ensembl 2006. Nucleic Acids Res 34:D556–D561CrossRefPubMedCentralPubMedGoogle Scholar
  15. 15.
    Yang Z, Nielsen R (2000) Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Mol Biol Evol 17:32–43CrossRefPubMedGoogle Scholar
  16. 16.
    Friedman RC, Farth KK, Burge CB, Bartel DP (2009) Most mammalian mRNAs are conserved targets of microRNAs. Genome Res 19:92–105CrossRefPubMedCentralPubMedGoogle Scholar
  17. 17.
    Lewis B, Burge C, Bartel D (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120:15–20CrossRefPubMedGoogle Scholar
  18. 18.
    Grimson A, Farth KK, Johnston WK et al (2007) MicroRNA target specificity in mammals: determinants beyond seed pairing. Mol Cell 27:91–105CrossRefPubMedCentralPubMedGoogle Scholar
  19. 19.
    Aloy P, Ceulemans H, Stark A, Russell RB (2003) The relationship between sequence and interaction divergence in proteins. J Mol Biol 332:989–998CrossRefPubMedGoogle Scholar
  20. 20.
    Gu Z, Nicolae D, Lu HH, Li W-H (2002) Rapid divergence in expression between duplicate genes inferred from microarray data. Trends Genet 18:609–613CrossRefPubMedGoogle Scholar
  21. 21.
    Chen F, Li W-H (2001) Genomic divergences between humans and other hominoids and the effective population size of the common ancestor of humans and chimpanzees. Am J Hum Genet 68:444–456CrossRefPubMedCentralPubMedGoogle Scholar
  22. 22.
    Gao L, Innan H (2004) Very low gene duplication rate in the yeast genome. Science 306:1367–1370CrossRefPubMedGoogle Scholar
  23. 23.
    Fernández A, Lynch M (2011) Nonadaptive origins of interactome complexity. Nature 474:502–505CrossRefPubMedCentralPubMedGoogle Scholar
  24. 24.
    Ball P (2011) The Achilles’ heel of biological complexity. Nature. doi: 10.1038/news.2011.294. Accessed 18 May 2011
  25. 25.
    Ball P (2011) Why are you so complex? Complicated protein interactions evolved to stave off mutations. Scientific American. Accessed 18 May 2011
  26. 26.
    Surmacz E, Bartucci M (2005) Role of estrogen receptor alpha in modulating IGF-I receptor signaling and function in breast cancer. J Exp Clin Cancer Res 23:385–394Google Scholar
  27. 27.
    Kimura M (2005) The neutral theory of molecular evolution. Cambridge University Press, CambridgeGoogle Scholar
  28. 28.
    Arnold FH, Meyerowitz JT (2014) News and views: evolving with purpose. Nature 509:166–167CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.National Research Council–CONICETBuenos AiresArgentina
  2. 2.Former Karl F. Hasselmann Endowed Chair Professor of BioengineeringRice UniversityHoustonUSA

Personalised recommendations