Enzyme Evolution

Abstract

Life involves an enormous diversity of coupled chemical reactions, almost none of which would occur in a biologically relevant time scale without catalysis. Enzymes are life catalysts, capable of enhancing the rates of biochemical reactions by many orders of magnitude. Modern natural enzymes are the complex outcome of evolution operating over a vast expanse of time. Plausibly, the overall process started ∼4 billion years ago when polypeptides that possibly served as cofactors of ribozymes in the RNA world acquired the capability to catalyse simple reactions. Likely, primordial enzymes were generalists that could catalyse various reactions with moderate efficiency. Diversification, specialisation and optimisation occurred subsequently over evolutionary history, probably coupled to successive gene duplication events. Advances in protein engineering and laboratory evolution have allowed some of the main stages in this evolutionary narrative to be reproduced in the laboratory and have demonstrated the fundamental role of conformational diversity in enzyme evolution.

Key Concepts

  • Modern natural enzymes are the complex outcome of evolution operating over ∼4 billion years.
  • Most modern natural enzymes evolved from previously existing enzymes.
  • To avoid detrimental effects on organismal fitness, the emergence of new enzymes from old enzymes is likely coupled to gene duplication.
  • Directed evolution experiments allow the transformation of an old enzyme into a new enzyme to be reproduced in the laboratory.
  • The evolutionary transformation of an old enzyme into a new enzyme likely occurs trough multifunctional intermediates.
  • Unless we accept panspermia as an explanation for the origin of life on Earth, we must admit that, at some very early stage of life evolution on this planet, primordial enzymes emerged de novo in noncatalytic scaffolds.
  • Recent work has shown that single mutations can generate emerging enzyme functionalities in previously noncatalytic scaffolds.
  • Proteins in solution are best envisioned as ensembles of different conformations.
  • Experimental and computational studies support that conformational diversity underlies enzyme ‘evolvability’, that is, the capability to evolve towards new functionalities.
  • Our current understanding of enzyme evolution is not detailed enough to provide a reliable basis for rational enzyme design.

Keywords: Enzyme evolution; enzyme promiscuity; de novo enzymes; protein evolvability; gene duplication; laboratory directed evolution; conformational diversity; structural dynamics

Figure 1. General model of enzyme evolution mediated by gene duplication and conformational diversity. (a) The protein populates an ensemble of different conformations. The major conformer binds the native substrate (yellow) and is responsible for the original function. (b) A minor alternative conformer can bind a different substrate (pink) and is responsible for a low‐level promiscuous activity. Mutations that shift the conformational equilibria towards the alternative conformer will enhance the promiscuous activity but will impair the original activity, thus compromising organismal fitness. (c) Gene duplication avoids such detrimental effects on organismal fitness, as one copy of the gene maintains the old function while the other copy accepts mutations that shift the conformational equilibria and evolves towards increasing levels of the new function. James and Tawfik . Reproduced with permission from Elsevier.
Figure 2. Native versus promiscuous enzyme activities. A natural phosphotriesterase capable to efficiently degrade paraoxon (a) also displays a low‐level promiscuous arylesterase activity and is able to degrade, although rather inefficiently, 2‐naphthyl hexanoate (b).
Figure 3. Laboratory directed evolution of an arylesterase (new function) from a paraoxonase (old function) (Tokuriki et al., ). See Figure for the structures of the substrates involved. (a) Catalytic efficiencies for the two activities for purified enzyme variants over the several rounds of the laboratory evolution experiment. It is clear that the initial and final states of the experiment correspond to specialist enzymes. On the other hand, the enzymes at some intermediate states are multifunctional and show moderately efficient catalysis for both reactions. (b) Plot of paraoxonase activity versus arylesterase activity over the rounds of the laboratory evolution experiment. Trade‐off between the two activities is not observed in the first few rounds. Eventually, however, increases in arylesterase activity bring about a strong decrease in the native, paraoxonase activity. In a natural evolution scenario, gene duplication (Figure ) would be required to avoid detrimental effects on organismal fitness.
Figure 4. A common benchmark in the de novo enzyme design. (a) Kemp elimination of 5‐nitrobenzioxazole showing the catalytic base and a proposed transition state structure. Kemp elimination is a simple model of proton abstraction from carbon, a fundamental process in chemistry and biochemistry, and has been extensively used as benchmark in de novo enzyme design. (b) Tryptophan. (c) 5(6)‐Nitrobenzotriazole, a transition‐state analogue for Kemp elimination. (d) Indole, the tryptophan side chain. Risso et al. . Licensed under CC BY 4.0.
Figure 5. Structures of de novo Kemp eliminases generated using a single‐mutation, minimalist design. Since the Kemp substrate has a shape similar to that of tryptophan side chain (Figure ), replacing W229 with aspartate generates, both a suitable cavity and a catalytic base at its bottom. (a) and (b) show the structures of two catalytic W229D variants with a bound transition‐state analogue superimposed with the structures of their corresponding background scaffolds. Displacement of two alpha‐helices is required to allow transition state binding. The background scaffold in (b) is pre‐organised and displays the required displacement before the catalysis generating mutation has been introduced. This is more clearly seen in the comparison between the two background scaffolds shown in (c). (d) and (e) show blow‐ups of the de novo active site regions for the Kemp eliminases in (a) and (b). Risso et al. . Licensed under CC BY 4.0.
close

References

Bar‐Even A, Noor E, Savir Y, et al. (2011) The moderately efficient enzyme: evolutionary and physicochemical trends shaping enzyme parameters. Biochemistry 50: 4402–44410.

Benner SA, Sassi SO and Gaucher EA (2007) Molecular paleoscience: system biology from the past. Advances in Enzymology and Related Areas of Molecular Biology 75: 1–132.

Bornberg‐Bauer E and Heames B (2019) Becoming a de novo gene. Nature Ecology and Evolution 3: 524–525.

Campbell E, Kaltenbach M, Correy GC, et al. (2016) The role of protein dynamics in the evolution of new enzyme function. Nature Chemical Biology 12: 944–950.

Chao FA, Morelli A, Haugner JC, et al. (2013) Structure and dynamics of a primordial catalytic fold generated by in vitro evolution. Nature Chemical Biology 9: 81–83.

Clifton BE, Kaczmarski JA, Carr PD, et al. (2018) Evolution of cyclohexadienyl dehydratase from an ancestral solute‐binding protein. Nature Chemical Biology 14: 542–547.

Copley SD (2017) Shining a light on enzyme promiscuity. Current Opinion in Structural Biology 47: 167–175.

Cortina GA and Kasson PM (2016) Excess positional mutual information predicts both local allosteric mutations affecting beta lactamase drug resistance. Bioinformatics 32: 3420–3427.

Drummond AD and Wilke CO (2009) The evolutionary consequences of erroneous protein synthesys. Nature Reviews. Genetics 10: 715–724.

Goldsmith M and Tawfik DS (2009) Potential role of phenotypic mutations in the evolution of protein expression and stability. Proceedings of the National Academy of Sciences of the USA 106: 6197–6202.

Hong N, Petrovic D, Lee R, et al. (2018) The evolution of multiple active site configurations in a designed enzyme. Nature Communications 9: 3900.

Innan H and Kondrashov F (2010) The evolution of gene duplications: classifying and distinguishing between models. Nature Reviews. Genetics 11: 97–108.

Isom DG, Cannon BR, Castañeda CA, Robinson A and Garcia‐Moreno B (2008) High tolerance for ionizable residues in the hydrophobic interior of proteins. Proceedings of the National Academy of Sciences of the USA 105: 17784–17788.

James LC and Tawfik DS (2003) Conformational diversity and protein evolution – a 60‐year‐old hypothesis revisited. Trends in Biochemical Sciences 28: 361–368.

Jensen RA (1976) Enzyme recruitment in evolution of new function. Annual Review of Microbiology 30: 409–425.

Jiang L, Althoff EA, Clemente FR, et al. (2008) De novo computational design of retro‐aldol enzymes. Science 319: 1387–1391.

Kaltenbach M, Burke JR, Dindo M, et al. (2018) Evolution of a chalcone isomerase from a noncatalytic ancestor. Nature Chemical Biology 14: 548–555.

Kamerlin SC and Warshel A (2010) At the dawn of the 21st century: is dynamics the missing link for understanding enzyme catalysis? Proteins: Structure, Function, and Bioinformatics 78: 1339–1375.

Kamerlin SC, Mavri J and Warshel A (2010) Examining the case for the effect of barrier compression on tunneling, vibrationally enhanced catalysis, catalytic entropy and related issues. FEBS Letters 584: 2759–2766.

Klinman JP and Kohen A (2014) Evolutionary aspects of enzyme dynamics. Journal of Biological Chemistry 289: 30205–30212.

Kohen A (2015) Role of dynamics in enzyme catalysis: substantial versus semantic controversies. Accounts of Chemical Research 42: 466–473.

Korendovych IV, Kulp DW, Wu Y, et al. (2011) Design of a switchable eliminase. Proceedings of the National Academy of Sciences of the USA 108: 6823–6827.

Ma H, Szeler K, Kamerlin SCL and Widersten M (2016) Linking coupled motions and entropic effects to the catalytic activity of 5‐deoxyribose‐5‐phosphate aldolase (DERA). Chemical Science 7: 1415–1421.

Menger FM (2005) An alternative view of enzyme catalysis. Pure and Applied Chemistry 77: 1873–1886.

Moroz YS, Dunston TT, Makhlynets OV, et al. (2015) New tricks for old proteins: single mutations in a nonenzymatic protein give rise to various enzymatic activities. Journal of the American Chemical Society 137: 14905–14911.

Ohno S (1970) Evolution by Gene Duplication. Springer: New York.

Ouzounis CA, Kunin V, Darzentas N and Goldovsky L (2006) A minimal estimate for the gene content of the last universal common ancestor – exobiology from a terrestrial perspective. Research in Microbiology 157: 57–68.

Pabis A, Risso VA, Sanchez‐Ruiz JM and Kamerlin SCL (2018) Cooperativity and flexibility in enzyme evolution. Current Opinion in Structural Biology 48: 83–92.

Pauling L (1946) Molecular architecture and biological reactions. Chemical and Engineering News 10: 1375–1377.

Petrovic D, Frank D, Kamerlin SCL, Hoffman K and Strodel B (2017) Shuffling active site substate populations affects catalytic activity: the case of glucose oxidase. ACS Catalysis 7: 6188–6197.

Petrovic D, Risso VA, Kamerlin SCL and Sanchez‐Ruiz JM (2018) Conformational dynamics and enzyme evolution. Journal of the Royal Society Interface 15: 20180330.

Pey AL, Rodriguez‐Larrea D, Gavira JA, Garcia‐Moreno B and Sanchez‐Ruiz JM (2010) Modulation of buried ionizable groups in proteins with engineered surface charge. Journal of the American Chemical Society 132: 1218–1219.

Risso VA, Martinez‐Rodriguez S, Candel AM, et al. (2017) De novo active sites for resurrected Precambrian enzymes. Nature Communications 8: 16113.

Risso VA, Sanchez‐Ruiz JM and Ozkan SB (2018) Biotechnological and protein‐engineering implications of ancestral protein resurrection. Current Opinion in Structural Biology 51: 106–115.

Romero‐Romero ML, Rabin A and Tawfik DS (2016) Functional proteins from short peptides: Dayhoff's hypothesis turns 50. Angewnadte Chemie Intermational Edition 55: 15966–15971.

Romero‐Romero ML, Yang F, Yu‐Ru L, et al. (2019) Simple yet functional phosphate‐loop proteins. Proceedings of the National Academy of Sciences of the USA 115: E11943–E11950.

Romero‐Rivera A, Garcia‐Borras M and Osuna M (2017) Role of conformational dynamics in the evolution of retro‐aldolase activity. ACS Catalysis 7: 8524–8532.

Röthlisberger D, Khersonsky O, Wollacott AM, et al. (2008) Kemp elimination catalysis by computational enzyme design. Nature 453: 190–195.

Schramm VL (2018) Enzymatic transition states and drug design. Chemical Reviews 118: 11194–11258.

Seelig B and Szostak JW (2007) Selection and evolution of enzymes from a partially randomized non‐catalytic scaffold. Nature 448: 828–831.

Siddiq MA, Hochberg GK and Thornton JW (2017) Evolution of protein specificity: insights from ancestral protein reconstruction. Current Opinion in Structural Biology 47: 113–122.

Siegel JB, Zanghellini A, Lovick HM, et al. (2010) Computational design of an enzyme catalyst for a stereoselective bimolecular Diels‐Alder reaction. Science 329: 309–313.

Tokuriki N, Jackson CJ, Afriat‐Jurnou L, et al. (2012) Diminishing returns and tradeoffs constrain the laboratory optimization of an enzyme. Nature Communications 3: 1257.

Villali J and Kern D (2010) Choreographing an enzyme's dance. Current Opinion in Chemical Biology 14: 636–643.

Weiss MC, Sousa FL, Mrnjavac N, et al. (2016) The physiology and habitat of the last universal common ancestor. Nature Microbiology 1: 16116.

Whitehead DJ, Wilke CO, Vernazobres D and Bornberg‐Bauer E (2008) The look‐ahead effect of phenotypic mutations. Biology Direct 3: 18.

Wolf YL and Koonin EV (2007) On the origin of the translation system and the genetic code in the RNA world by means of natural selection, exaptation and subfunctionalization. Biology Direct 2: 14.

Wolfenden R (2006) Degrees of difficulty of water‐consuming reactions in the absence of enzymes. Chemical Reviews 106: 3379–3396.

Yamniuk AP and Vogel HJ (2004) Calmodulin's flexibility allows for promiscuity in its interactions with target proteins and peptides. Molecular Biotechnology 27: 33–57.

Zanghellini A, Jiang L, Wollacott AM, et al. (2006) New algorithms and an in silico benchmark for computational enzyme design. Protein Science 15: 2785–2794.

Zou T, Risso VA, Gavira JA, Sanchez‐Ruiz JM and Ozkan SB (2015) Evolution of conformational dynamics determines the conversion of a promiscuous generalist into a specialist enzyme. Molecular Biology and Evolution 32: 132–143.

Further Reading

Gumulya Y and Gillam EMJ (2017) Exploring the past and the future of protein evolution with ancestral sequence reconstruction. Biochemical Journal 474: 1–19.

Korendovych IV and DeGrado WF (2014) Catalytic efficiency of designed catalytic proteins. Current Opinion in Structural Biology 27: 113–121.

Newton MS, Arcus VL, Gerth ML and Patrick WM (2018) Enzyme evolution: innovation is easy, optimization is complicated. Current Opinion in Structural Biology 48: 110–116.

O'Brian PJ and Herschlag D (1999) Catalytic promiscuity and the evolution of new enzymatic activities. Chemistry and Biology 6: R91–R105.

Petrovic D and Kamerlin SCL (2018) Molecular modelling of conformational dynamics and its role in enzyme evolution. Current Opinion in Structural Biology 52: 50–57.

Starr TN, Picton LK and Thornton JW (2017) Alternative evolutionary histories in the sequence space of an ancient protein. Nature 549: 409–413.

Tokuriki N and Tawfik DS (2009) Protein dynamism and evolvability. Science 324: 203–207.

Trudeau DL and Tawfik DS (2019) Protein engineers turned evolutionists – the quest for the optimal starting point. Current Opinion in Biotechnology 60C: 46–52.

Tyzack JD, Furnham N, Sillitoe I, Orengo CM and Thornton JM (2017) Understanding enzyme function evolution from a computational perspective. Current Opinion in Structural Biology 47: 131–139.

Zeymer C and Hilvert D (2018) Directed evolution of protein catalysts. Annual Review of Biochemistry 87: 131–157.

Contact Editor close
Submit a note to the editor about this article by filling in the form below.

* Required Field

How to Cite close
Sanchez‐Ruiz, Jose M(Oct 2019) Enzyme Evolution. In: eLS. John Wiley & Sons Ltd, Chichester. http://www.els.net [doi: 10.1002/9780470015902.a0028797]