Evolution of Minimal Specificity and Promiscuity in Steroid Hormone Receptors

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Most proteins are regulated by physical interactions with other molecules; some are highly specific, but others interact with many partners. Despite much speculation, we know little about how and why specificity/promiscuity evolves in natural proteins. It is widely assumed that specific proteins evolved from more promiscuous ancient forms and that most proteins' specificity has been tuned to an optimal state by selection. Here we use ancestral protein reconstruction to trace the evolutionary history of ligand recognition in the steroid hormone receptors (SRs), a family of hormone-regulated animal transcription factors. We resurrected the deepest ancestral proteins in the SR family and characterized the structure-activity relationships by which they distinguished among ligands. We found that that the most ancient split in SR evolution involved a discrete switch from an ancient receptor for aromatized estrogens—including xenobiotics—to a derived receptor that recognized non-aromatized progestagens and corticosteroids. The family's history, viewed in relation to the evolution of their ligands, suggests that SRs evolved according to a principle of minimal specificity: at each point in time, receptors evolved ligand recognition criteria that were just specific enough to parse the set of endogenous substances to which they were exposed. By studying the atomic structures of resurrected SR proteins, we found that their promiscuity evolved because the ancestral binding cavity was larger than the primary ligand and contained excess hydrogen bonding capacity, allowing adventitious recognition of larger molecules with additional functional groups. Our findings provide an historical explanation for the sensitivity of modern SRs to natural and synthetic ligands—including endocrine-disrupting drugs and pollutants—and show that knowledge of history can contribute to ligand prediction. They suggest that SR promiscuity may reflect the limited power of selection within real biological systems to discriminate between perfect and “good enough.”

Vyšlo v časopise: Evolution of Minimal Specificity and Promiscuity in Steroid Hormone Receptors. PLoS Genet 8(11): e32767. doi:10.1371/journal.pgen.1003072
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1003072

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Zdroje

1. Alberts B (2002) Molecular biology of the cell. New York: Garland Science. xxxiv, [1548] p.

2. BhattacharyyaRP, RemenyiA, YehBJ, LimWA (2006) Domains, motifs, and scaffolds: the role of modular interactions in the evolution and wiring of cell signaling circuits. Annu Rev Biochem 75: 655–680.

3. RohsR, JinX, WestSM, JoshiR, HonigB, et al. (2010) Origins of specificity in protein-DNA recognition. Annu Rev Biochem 79: 233–269.

4. LefkowitzRJ (2000) The superfamily of heptahelical receptors. Nat Cell Biol 2: E133–6.

5. CopleySD (2003) Enzymes with extra talents: moonlighting functions and catalytic promiscuity. Curr Opin Chem Biol 7: 265–272.

6. GoreAC (2007) Endocrine-disrupting chemicals: from basic research to clinical practice.

7. JensenRA (1976) Enzyme recruitment in evolution of new function. Annu Rev Microbiol 30: 409–425.

8. O'BrienPJ, HerschlagD (1999) Catalytic promiscuity and the evolution of new enzymatic activities. Chem Biol 6: R91–R105.

9. KhersonskyO, TawfikDS (2010) Enzyme promiscuity: a mechanistic and evolutionary perspective. Annu Rev Biochem 79: 471–505.

10. TawfikDS (2010) Messy biology and the origins of evolutionary innovations. Nat Chem Biol 6: 692–696.

11. YoshikuniY, FerrinTE, KeaslingJD (2006) Designed divergent evolution of enzyme function. Nature 440: 1078–1082.

12. LiberlesDA, TisdellMD, GrahnenJA (2011) Binding constraints on the evolution of enzymes and signalling proteins: the important role of negative pleiotropy. Proc Biol Sci 278: 1930–1935.

13. BershteinS, GoldinK, TawfikDS (2008) Intense neutral drifts yield robust and evolvable consensus proteins. Journal of molecular biology 379: 1029–1044.

14. BloomJD, RomeroPA, LuZ, ArnoldFH (2007) Neutral genetic drift can alter promiscuous protein functions, potentially aiding functional evolution. Biol Direct 2: 17.

15. BloomJD, ArnoldFH (2009) In the light of directed evolution: pathways of adaptive protein evolution. Proc Natl Acad Sci U S A 106 Suppl 1: 9995–10000.

16. KeiserMJ, SetolaV, IrwinJJ, LaggnerC, AbbasAI, et al. (2009) Predicting new molecular targets for known drugs. Nature 462: 175–181.

17. GronemeyerH, GustafssonJA, LaudetV (2004) Principles for modulation of the nuclear receptor superfamily. Nat Rev Drug Discov 3: 950–964.

18. EickGN, ThorntonJW (2011) Evolution of steroid receptors from an estrogen-sensitive ancestral receptor. Mol Cell Endocrinol 334: 31–38.

19. KatzenellenbogenJA (1995) The structural pervasiveness of estrogenic activity. Environ Health Perspect 103 Suppl 7: 99–101.

20. Orchinik M, Propper CR (2006) Hormone Action on Receptors. In: Norris DO, Carr JA, editors. Endocrine Disruption: Biological Basis for Health Effects in Wildlife and Humans. New York: Oxford University Press. pp. 28–57.

21. ThorntonJW (2004) Resurrecting ancient genes: experimental analysis of extinct molecules. Nat Rev Genet 5: 366–375.

22. LiberlesDA (2008) Ancestral Sequence Reconstruction.

23. ThorntonJW, NeedE, CrewsD (2003) Resurrecting the ancestral steroid receptor: ancient origin of estrogen signaling. Science 301: 1714–1717.

24. BridghamJT, BrownJE, Rodriguez-MariA, CatchenJM, ThorntonJW (2008) Evolution of a new function by degenerative mutation in cephalochordate steroid receptors. PLoS Genet 4: e1000191.

25. GellerDS, FarhiA, PinkertonN, FradleyM, MoritzM, et al. (2000) Activating mineralocorticoid receptor mutation in hypertension exacerbated by pregnancy. Science 289: 119–123.

26. VeldscholteJ, BerrevoetsCA, Ris-StalpersC, KuiperGG, JensterG, et al. (1992) The androgen receptor in LNCaP cells contains a mutation in the ligand binding domain which affects steroid binding characteristics and response to antiandrogens. J Steroid Biochem Mol Biol 41: 665–669.

27. ZhaoXY, MalloyPJ, KrishnanAV, SwamiS, NavoneNM, et al. (2000) Glucocorticoids can promote androgen-independent growth of prostate cancer cells through a mutated androgen receptor. Nat Med 6: 703–706.

28. ThorntonJW (2001) Evolution of vertebrate steroid receptors from an ancestral estrogen receptor by ligand exploitation and serial genome expansions. Proc Natl Acad Sci U S A 98: 5671–5676.

29. DuboisD, PradeH (1987) The principle of mimimum specificity as a basis for evidentiary reasoning. Lecture Notes in Computer Science 286: 75–84.

30. MizutaT, AsahinaK, SuzukiM, KubokawaK (2008) In vitro conversion of sex steroids and expression of sex steroidogenic enzyme genes in amphioxus ovary. J Exp Zool A Ecol Genet Physiol 309: 83–93.

31. D'AnielloA, Di CosmoA, Di CristoC, AssisiL, BotteV, et al. (1996) Occurrence of sex steroid hormones and their binding proteins in Octopus vulgaris lam. Biochem Biophys Res Commun 227: 782–788.

32. CloseDA, YunSS, McCormickSD, WildbillAJ, LiW (2010) 11-deoxycortisol is a corticosteroid hormone in the lamprey. Proc Natl Acad Sci U S A 107: 13942–13947.

33. TavernaDM, GoldsteinRA (2002) Why are proteins so robust to site mutations? 1. Journal of molecular biology 315: 479–484.

34. RyanMJ, FoxJH, WilczynskiW, RandAS (1990) Sexual selection for sensory exploitation in the frog Physalaemus pustulosus. Nature 343: 66–67.

35. Wickler W (1968) Mimicry in Plants and Animals. New York: McGraw-Hill.

36. EdwardsDP, WuDW (2007) The roles of sensory traps in the origin, maintenance and breakdown of mutualism. Behav Ecol Sociobiol 61: 1321–1327.

37. EdgarRC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792–1797.

38. GuindonS, GascuelO (2003) A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol 52: 696–704.

39. AnisimovaM, GascuelO (2006) Approximate likelihood-ratio test for branches: A fast, accurate, and powerful alternative. Systematic biology 55: 539–552.

40. YangZ, KumarS, NeiM (1995) A new method of inference of ancestral nucleotide and amino acid sequences. Genetics 141: 1641–1650.

41. YangZ (1997) PAML: a program package for phylogenetic analysis by maximum likelihood. Comput Appl Biosci 13: 555–556.

42. Hanson-SmithV, KolaczkowskiB, ThorntonJW (2010) Robustness of ancestral sequence reconstruction to phylogenetic uncertainty. Mol Biol Evol 27: 1988–1999.

43. PicardD, YamamotoKR (1987) Two signals mediate hormone-dependent nuclear localization of the glucocorticoid receptor. EMBO J 6: 3333–3340.

44. KeayJ, BridghamJT, ThorntonJW (2006) The Octopus vulgaris estrogen receptor is a constitutive transcriptional activator: evolutionary and functional implications. Endocrinology 147: 3861–3869.

45. BridghamJT, CarrollSM, ThorntonJW (2006) Evolution of hormone-receptor complexity by molecular exploitation. Science 312: 97–101.

46. ClinckemalieL, VanderschuerenD, Boonen…S (2012) The hinge region in androgen receptor control. Molecular and cellular …

47. BridghamJT, EickGN, LarrouxC, DeshpandeK, HarmsMJ, et al. (2010) Protein evolution by molecular tinkering: diversification of the nuclear receptor superfamily from a ligand-dependent ancestor. PLoS Biol 8

48. AdamsPD, AfoninePV, BunkocziG, ChenVB, DavisIW, et al. (2010) PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr D Biol Crystallogr 66: 213–221.

49. EmsleyP, CowtanK (2004) Coot: model-building tools for molecular graphics. Acta Crystallogr D Biol Crystallogr 60: 2126–2132.

50. EswarN, EramianD, WebbB, ShenMY, SaliA (2008) Protein structure modeling with MODELLER. Methods Mol Biol 426: 145–159.

51. LovellSC, DavisIW, ArendallWBr, de BakkerPI, WordJM, et al. (2003) Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins 50: 437–450.

52. KleywegtGJ, JonesTA (1994) Detection, delineation, measurement and display of cavities in macromolecular structures. Acta Crystallogr D Biol Crystallogr 50: 178–185.