Molecular determinants of protein evolvability
2023; Elsevier BV; Volume: 48; Issue: 9 Linguagem: Inglês
10.1016/j.tibs.2023.05.009
ISSN1362-4326
AutoresKarol Buda, C.M. Miton, Xingyu Cara Fan, Nobuhiko Tokuriki,
Tópico(s)Microbial Metabolic Engineering and Bioproduction
ResumoThe evolvability of proteins stems from their underlying biochemical, biophysical, and genetic properties. Initial states appear to drive the adaptability of proteins.There is mounting evidence, from evolutionary trajectories, that the availability of adaptive mutations is greatly influenced by epistasis. The underlying molecular mechanisms remain largely unexplored, however.Emerging techniques in single-molecule studies are revolutionizing the exploration of molecular heterogeneity in protein ensembles, a cryptic determinant of evolvability, providing a better understanding of this phenomenon. The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein’s initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration. The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein’s initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration. The evolution of new protein functions enables organisms to adapt to environmental changes. For billions of years, nature has continuously evolved new proteins, expanding their functional repertoire. While the BRENDA database encompasses over 8000 different enzyme functions, many more remain to be uncovered [1.Chang A. et al.BRENDA, the ELIXIR core data resource in 2021: new developments and updates.Nucleic Acids Res. 2020; 49: D498-D508Crossref Scopus (240) Google Scholar]. The past decades saw the discovery of enzymes able to utilize anthropogenic compounds as their primary substrate, demonstrating that novel enzyme functions are constantly evolving [2.Testa B. et al.Reactions and enzymes in the metabolism of drugs and other xenobiotics.Drug Discov. Today. 2012; 17: 549-560Crossref PubMed Scopus (168) Google Scholar,3.Janssen D.B. et al.Bacterial degradation of xenobiotic compounds: evolution and distribution of novel enzyme activities: bacterial degradation of xenobiotic compounds.Environ. Microbiol. 2005; 7: 1868-1882Crossref PubMed Scopus (187) Google Scholar]. However, the key molecular mechanisms governing protein evolvability (see Glossary), the ability to adopt a new function with minimal mutational change, remain elusive. This mechanistic ambiguity stems from the inherent stochasticity and complexity of evolution [4.Lenormand T. et al.Stochasticity in evolution.Trends Ecol. Evol. 2009; 24: 157-165Abstract Full Text Full Text PDF PubMed Scopus (132) Google Scholar]. Biologists have been grappling with this question for a long time: in his book, Wonderful life, Stephen Jay Gould wondered whether replaying the tape of life would always result in the same outcome [5.Gould S.J. Wonderful Life: The Burgess Shale and the Nature of History. W.W. Norton & Co, 1989Google Scholar]. Gould also questioned how seemingly minor variations in initial states could give rise to different evolutionary scenarios. These fundamental questions have significant implications for the evolution of new protein functions: are evolutionary outcomes determined by a protein’s initial state, or rather, by the stochastic nature of the evolutionary processes themselves [6.Orgogozo V. Replaying the tape of life in the twenty-first century.Interface Focus. 2015; 520150057Crossref PubMed Scopus (51) Google Scholar, 7.Xie V.C. et al.Contingency and chance erase necessity in the experimental evolution of ancestral proteins.eLife. 2021; 10e67336Crossref Scopus (16) Google Scholar, 8.Monod J. Chance and Necessity: An Essay on the Natural Philosophy of Biology. Random House Trade Paperbacks, 1972Google Scholar, 9.Blount Z.D. et al.Contingency and determinism in evolution: replaying life’s tape.Science. 2018; 362eaam5979Crossref PubMed Scopus (275) Google Scholar]? One extreme scenario posits that evolutionary outcomes will always be identical, regardless of the initial states, implying that evolution is deterministic (Figure 1A ). On the other end of the spectrum, multiple parallel evolutionary trials conducted under the same condition from a single starting sequence will always result in distinct evolutionary outcomes, rendering evolution highly stochastic (Figure 1B,C). Such stochasticity can exist at the phenotypic (Figure 1B) and genotypic levels (Figure 1C). If the accessible phenotypic optima are equal, genotypic differences in initial states will result in the same evolutionary outcomes. If the optima differ, however, initial states will strongly dictate the outcomes. Of course, most evolutionary scenarios will unfold within this spectrum of possibilities, in the sense that evolutionary outcomes are likely influenced by initial states and their inherent constraints, in addition to constraints exerted by selection [7.Xie V.C. et al.Contingency and chance erase necessity in the experimental evolution of ancestral proteins.eLife. 2021; 10e67336Crossref Scopus (16) Google Scholar,10.Dickinson B.C. et al.Experimental interrogation of the path dependence and stochasticity of protein evolution using phage-assisted continuous evolution.Proc. Natl. Acad. Sci. U. S. A. 2013; 110: 9007-9012Crossref PubMed Scopus (76) Google Scholar]. To date, extensive experimental evolution and ancestral sequence reconstruction (ASR) have been carried out to dissect natural and laboratory trajectories in an attempt to unravel the evolutionary dynamics and molecular mechanisms underlying functional evolution [11.Kaltenbach M. Tokuriki N. Dynamics and constraints of enzyme evolution.J. Exp. Zool. Part B Mol. Dev. Evol. 2014; 322: 468-487Crossref PubMed Scopus (57) Google Scholar, 12.Trudeau D.L. Tawfik D.S. Protein engineers turned evolutionists—the quest for the optimal starting point.Curr. Opin. Biotechnol. 2019; 60: 46-52Crossref PubMed Scopus (68) Google Scholar, 13.Spence M.A. et al.Ancestral sequence reconstruction for protein engineers.Curr. Opin. Struct. Biol. 2021; 69: 131-141Crossref PubMed Scopus (50) Google Scholar, 14.Hochberg G.K.A. Thornton J.W. Reconstructing ancient proteins to understand the causes of structure and function.Annu. Rev. Biophys. 2016; 46: 1-23Google Scholar]. These studies converge toward the emerging view that initial states strongly dictate the evolutionary outcomes of proteins. For example, the same starting sequence evolved in parallel experiments tends to acquire similar subsets of mutations [9.Blount Z.D. et al.Contingency and determinism in evolution: replaying life’s tape.Science. 2018; 362eaam5979Crossref PubMed Scopus (275) Google Scholar]. By contrast, protein sequences evolved from different initial states can be influenced by epistasis (i.e., arising from mutational interactions). Indeed, epistasis introduces a certain degree of stochasticity at various stages of evolution, which results in different evolutionary outcomes [15.Zheng J. et al.Cryptic genetic variation accelerates evolution by opening access to diverse adaptive peaks.Science. 2019; 365: 347-353Crossref PubMed Scopus (64) Google Scholar, 16.Khanal A. et al.Differential effects of a mutation on the normal and promiscuous activities of orthologs: implications for natural and directed evolution.Mol. Biol. Evol. 2015; 32: 100-108Crossref PubMed Scopus (48) Google Scholar, 17.Baier F. et al.Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes.eLife. 2019; 8e40789Crossref PubMed Scopus (26) Google Scholar]. Thus, the incredible genetic diversity found in nature constitutes a vast arsenal of initial states, from which novel protein functions may evolve (Box 1). The identification of relevant differences between these initial states is challenging, however. How many mutations are necessary and sufficient to alter the evolvability of two homologous sequences? What key molecular features differentiate the evolvability of various initial states? Recent studies have begun to untangle the importance of these determinants, including the biochemical, biophysical, and genetic properties, that govern protein evolvability. Note that many definitions of evolvability exist [18.Payne J.L. Wagner A. The causes of evolvability and their evolution.Nat. Rev. Genet. 2018; 20: 1-15Google Scholar,19.Pigliucci M. Is evolvability evolvable?.Nat. Rev. Genet. 2008; 9: 75-82Crossref PubMed Scopus (397) Google Scholar]; they are well-suited for broad biological discussions and tailored to different fields of evolutionary biology [20.de la Rosa L.N. Computing the extended synthesis: mapping the dynamics and conceptual structure of the evolvability research front.J. Exp. Zool. Part B Mol. Dev. Evol. 2017; 328: 395-411Crossref PubMed Scopus (21) Google Scholar]. Here, we rather adopt a protein-centric definition [21.Tokuriki N. Tawfik D.S. Protein dynamism and evolvability.Science. 2009; 324: 203-207Crossref PubMed Scopus (661) Google Scholar] to explore this problem through a biophysical lens. In this review, we will outline the key molecular determinants of protein evolvability and discuss their role in driving protein evolution, emphasizing the lessons learnt from protein experimental evolution and ASR.Box 1Evolution of new enzymes and microbial diversityIf the initial states of proteins strongly dictate evolvability, how does nature leverage this phenomenon to successfully co-opt evolvable starting points and generate new enzymes so swiftly? In the past decades, numerous novel enzymes have evolved the ability to degrade xenobiotic compounds, such as pesticides, plastics, or various anthropogenic chemicals [85.Copley S.D. Evolution of efficient pathways for degradation of anthropogenic chemicals.Nat. Chem. Biol. 2009; 5: 559-566Crossref PubMed Scopus (143) Google Scholar]. A recurring aspect of xenobiotic degradation is the emergence of a single (or a few) enzyme(s) to degrade the novel substrate and the subsequent dissemination of this essential gene across microbial populations via horizontal gene transfer [3.Janssen D.B. et al.Bacterial degradation of xenobiotic compounds: evolution and distribution of novel enzyme activities: bacterial degradation of xenobiotic compounds.Environ. Microbiol. 2005; 7: 1868-1882Crossref PubMed Scopus (187) Google Scholar]. These examples of xenobiotic-degrading enzyme evolution may reflect the strong influence of the initial state on the evolvability of proteins and constitute an archetype of how the most evolvable starting points may be selected by nature. In a given gram of soil, there are trillions of cells, consisting of thousands of distinct microbial species [86.Torsvik V. Øvreås L. Microbial diversity and function in soil: from genes to ecosystems.Curr. Opin. Microbiol. 2002; 5: 240-245Crossref PubMed Scopus (1315) Google Scholar]. Assuming that these microbes harbor billions of distinct genes [87.Serres M.H. et al.A functional update of the Escherichia coli K-12 genome.Genome Biol. 2001; 2research0035.1Crossref PubMed Google Scholar], encoding proteins represented by several thousands of unique orthologous sequences, these microenvironments constitute a massive reservoir of initial states that could foster the evolution of new enzyme functions. Note that this number can be further multiplied when taking promiscuous activities into account [88.Copley S.D. Shining a light on enzyme promiscuity.Curr. Opin. Struct. Biol. 2017; 47: 167-175Crossref PubMed Scopus (108) Google Scholar] (Box 2). Thus, even if the majority of these initial states are not evolvable toward a particular chemical reaction, nature will eventually select the most promising candidate from the immense pool of initial states harbored by a microbial community. Indeed, the unique and specialized xenobiotic-degrading enzymes uncovered thus far likely originate from a few highly evolvable ancestral starting points that have disseminated across many microbial populations. If the initial states of proteins strongly dictate evolvability, how does nature leverage this phenomenon to successfully co-opt evolvable starting points and generate new enzymes so swiftly? In the past decades, numerous novel enzymes have evolved the ability to degrade xenobiotic compounds, such as pesticides, plastics, or various anthropogenic chemicals [85.Copley S.D. Evolution of efficient pathways for degradation of anthropogenic chemicals.Nat. Chem. Biol. 2009; 5: 559-566Crossref PubMed Scopus (143) Google Scholar]. A recurring aspect of xenobiotic degradation is the emergence of a single (or a few) enzyme(s) to degrade the novel substrate and the subsequent dissemination of this essential gene across microbial populations via horizontal gene transfer [3.Janssen D.B. et al.Bacterial degradation of xenobiotic compounds: evolution and distribution of novel enzyme activities: bacterial degradation of xenobiotic compounds.Environ. Microbiol. 2005; 7: 1868-1882Crossref PubMed Scopus (187) Google Scholar]. These examples of xenobiotic-degrading enzyme evolution may reflect the strong influence of the initial state on the evolvability of proteins and constitute an archetype of how the most evolvable starting points may be selected by nature. In a given gram of soil, there are trillions of cells, consisting of thousands of distinct microbial species [86.Torsvik V. Øvreås L. Microbial diversity and function in soil: from genes to ecosystems.Curr. Opin. Microbiol. 2002; 5: 240-245Crossref PubMed Scopus (1315) Google Scholar]. Assuming that these microbes harbor billions of distinct genes [87.Serres M.H. et al.A functional update of the Escherichia coli K-12 genome.Genome Biol. 2001; 2research0035.1Crossref PubMed Google Scholar], encoding proteins represented by several thousands of unique orthologous sequences, these microenvironments constitute a massive reservoir of initial states that could foster the evolution of new enzyme functions. Note that this number can be further multiplied when taking promiscuous activities into account [88.Copley S.D. Shining a light on enzyme promiscuity.Curr. Opin. Struct. Biol. 2017; 47: 167-175Crossref PubMed Scopus (108) Google Scholar] (Box 2). Thus, even if the majority of these initial states are not evolvable toward a particular chemical reaction, nature will eventually select the most promising candidate from the immense pool of initial states harbored by a microbial community. Indeed, the unique and specialized xenobiotic-degrading enzymes uncovered thus far likely originate from a few highly evolvable ancestral starting points that have disseminated across many microbial populations. The determinants that enable us to distinguish evolvable initial states from potential dead-ends are rooted in molecular and biophysical properties. While these aspects have been independently explored in other reviews [12.Trudeau D.L. Tawfik D.S. Protein engineers turned evolutionists—the quest for the optimal starting point.Curr. Opin. Biotechnol. 2019; 60: 46-52Crossref PubMed Scopus (68) Google Scholar,21.Tokuriki N. Tawfik D.S. Protein dynamism and evolvability.Science. 2009; 324: 203-207Crossref PubMed Scopus (661) Google Scholar, 22.Matsumura I. Patrick W.M. Dan Tawfik’s lessons for protein engineers about enzymes adapting to new substrates.Biochemistry. 2022; 62: 158-162Crossref PubMed Scopus (1) Google Scholar, 23.Tokuriki N. Tawfik D.S. Stability effects of mutations and protein evolvability.Curr. Opin. Struct. Biol. 2009; 19: 596-604Crossref PubMed Scopus (523) Google Scholar, 24.Khersonsky O. Tawfik D.S. Enzyme promiscuity: a mechanistic and evolutionary perspective.Annu. Rev. Biochem. 2010; 79: 471-505Crossref PubMed Scopus (988) Google Scholar], we contextualize these simple molecular determinants in light of protein evolvability. The evolution of a new protein function often starts by recruiting and optimizing a promiscuous function (Box 2). Hence, the initial level of new function is likely to influence protein evolvability. In principle, a protein function will only provide a selective advantage to the host organism if its activity level exceeds a physiologically relevant threshold, otherwise, the protein cannot be recruited for further evolution (Figure 2A ) [24.Khersonsky O. Tawfik D.S. Enzyme promiscuity: a mechanistic and evolutionary perspective.Annu. Rev. Biochem. 2010; 79: 471-505Crossref PubMed Scopus (988) Google Scholar,25.O’Brien P.J. Herschlag D. Catalytic promiscuity and the evolution of new enzymatic activities.Chem. Biol. 1999; 6: R91-R105Abstract Full Text PDF PubMed Scopus (644) Google Scholar]. It is reasonable to assume that proteins with higher functional levels require fewer mutational steps to confer maximum fitness to their host. Thus, a simple argument posits that initial states with higher levels of new function are more evolvable starting points (Figure 2A).Box 2The evolvability of promiscuous enzyme networksThe evolution of new enzyme functions is generally thought to originate from the recruitment and adaptation of promiscuous enzymes carrying a latent secondary activity [89.Jensen R.A. Enzyme recruitment in evolution of new function.Annu. Rev. Microbiol. 1976; 30: 409-425Crossref PubMed Scopus (856) Google Scholar]. In the past decade, the extensive biochemical characterization of several enzyme superfamilies has revealed that diverged protein sequences remain ‘connected’, genetically and chemically [90.Baier F. et al.Evolution of enzyme superfamilies: comprehensive exploration of sequence–function relationships.Biochemistry. 2016; 55: 6375-6388Crossref PubMed Scopus (48) Google Scholar]. In fact, they often exhibit crosswise promiscuity, where the main catalytic function of an enzyme is the promiscuous function of another member [91.Mohamed M.F. Hollfelder F. Efficient, crosswise catalytic promiscuity among enzymes that catalyze phosphoryl transfer.Biochim. Biophys. Acta Proteins Proteomics. 2013; 1834: 417-424Crossref Scopus (45) Google Scholar]. Promiscuous enzymes have been shown to constitute evolvable starting points [24.Khersonsky O. Tawfik D.S. Enzyme promiscuity: a mechanistic and evolutionary perspective.Annu. Rev. Biochem. 2010; 79: 471-505Crossref PubMed Scopus (988) Google Scholar,92.Aharoni A. et al.The “evolvability” of promiscuous protein functions.Nat. Genet. 2005; 37: 73-76Crossref PubMed Scopus (665) Google Scholar,93.Bloom J.D. et al.Neutral genetic drift can alter promiscuous protein functions, potentially aiding functional evolution.Biol. Direct. 2007; 2: 17Crossref PubMed Scopus (140) Google Scholar]. Akin to fold evolvability, the number and magnitude of promiscuous functions carried by a protein superfamily could reflect their evolvability. This evolvability is likely intertwined with the attributes giving rise to promiscuity: (i) inherent active site reactivity [e.g., provided by cofactors and metal ions (see ‘Molecular heterogeneity’)] [78.Babtie A. et al.What makes an enzyme promiscuous?.Curr. Opin. Chem. Biol. 2010; 14: 200-207Crossref PubMed Scopus (164) Google Scholar]; (ii) versatile active site architectures promoting multiple distinct binding modes (see ‘Refinement of the active site’); (iii) unique folds that support rapid structural rearrangements (see ‘Protein fold’); and, in some cases, (iv) conformational diversity creating functional heterogeneity (see ‘Molecular heterogeneity’).‘Catalytic landscapes’ depict the relationship between catalytic activities and sequence space, enabling the visualization of highly interconnected functional networks, hidden within enzyme superfamilies (Figure I). This network view exposes unique regions of the sequence space where catalytic landscapes intersect: they contain promiscuous genotypes able to catalyze multiple catalytic activities (Figure I, dashed area) [90.Baier F. et al.Evolution of enzyme superfamilies: comprehensive exploration of sequence–function relationships.Biochemistry. 2016; 55: 6375-6388Crossref PubMed Scopus (48) Google Scholar,94.Baier F. Tokuriki N. Connectivity between catalytic landscapes of the metallo-β-lactamase superfamily.J. Mol. Biol. 2014; 426: 2442-2456Crossref PubMed Scopus (80) Google Scholar]. Such connectivity suggests that enzymes may evolve, from one function to another, through a continuous network of functional sequence space. Consequently, the extent of functional connectivity in a protein superfamily could reflect its evolvability. Yet, the emergence of a given function could be restricted to particular progenitor enzymes: in these superfamilies, two functions may only be connected through a third, intermediary one, effectively restricting the initial genotypes that could evolve. Furthermore, the level and spectrum of promiscuous functions substantially differ between proteins, even among orthologous sequences that share the same native function [16.Khanal A. et al.Differential effects of a mutation on the normal and promiscuous activities of orthologs: implications for natural and directed evolution.Mol. Biol. Evol. 2015; 32: 100-108Crossref PubMed Scopus (48) Google Scholar,17.Baier F. et al.Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes.eLife. 2019; 8e40789Crossref PubMed Scopus (26) Google Scholar,95.Huang H. et al.Panoramic view of a superfamily of phosphatases through substrate profiling.Proc. Natl. Acad. Sci. U. S. 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Other molecular determinants, such as epistasis, could eventually undermine the benefits of these interconnected networks and lead to dead ends (Figure I, grey path to local optima).Figure 2The evolvability of a starting point is conditioned by its initial level of function and/or stability.Show full caption(A) Unlike native functions, promiscuous enzyme functions emerge serendipitously and may only become physiologically relevant when their catalytic activity surpasses a certain threshold. This threshold depends on the cost/benefit of recruiting the promiscuous function, the host environment, and environmental conditions. For example, states 1 and 2 both exceed the physiological relevance level, thus are likely to be recruited and to evolve new functions. Due to its higher activity level, state 1 requires fewer mutational steps to confer maximum fitness to its host than state 2; as a result, 1 appears more evolvable. By contrast, state 3 requires the accumulation of many beneficial mutations to become physiologically relevant and is thus unlikely to evolve further. (B) An excess level of stability in a starting state and compensatory mutations can both enhance a protein’s tolerance to destabilizing mutations. For example, initial state 1 appears more evolvable than state 2 because it can acquire function-enhancing mutations (red arrows) without destabilizing its native structure. Compensatory mutations (blue arrows) subsequently rescue and sustain the stability of the evolving protein.View Large Image Figure ViewerDownload Hi-res image Download (PPT) The evolution of new enzyme functions is generally thought to originate from the recruitment and adaptation of promiscuous enzymes carrying a latent secondary activity [89.Jensen R.A. Enzyme recruitment in evolution of new function.Annu. Rev. Microbiol. 1976; 30: 409-425Crossref PubMed Scopus (856) Google Scholar]. In the past decade, the extensive biochemical characterization of several enzyme superfamilies has revealed that diverged protein sequences remain ‘connected’, genetically and chemically [90.Baier F. et al.Evolution of enzyme superfamilies: comprehensive exploration of sequence–function relationships.Biochemistry. 2016; 55: 6375-6388Crossref PubMed Scopus (48) Google Scholar]. In fact, they often exhibit crosswise promiscuity, where the main catalytic function of an enzyme is the promiscuous function of another member [91.Mohamed M.F. Hollfelder F. Efficient, crosswise catalytic promiscuity among enzymes that catalyze phosphoryl transfer.Biochim. Biophys. Acta Proteins Proteomics. 2013; 1834: 417-424Crossref Scopus (45) Google Scholar]. Promiscuous enzymes have been shown to constitute evolvable starting points [24.Khersonsky O. Tawfik D.S. Enzyme promiscuity: a mechanistic and evolutionary perspective.Annu. Rev. Biochem. 2010; 79: 471-505Crossref PubMed Scopus (988) Google Scholar,92.Aharoni A. et al.The “evolvability” of promiscuous protein functions.Nat. Genet. 2005; 37: 73-76Crossref PubMed Scopus (665) Google Scholar,93.Bloom J.D. et al.Neutral genetic drift can alter promiscuous protein functions, potentially aiding functional evolution.Biol. Direct. 2007; 2: 17Crossref PubMed Scopus (140) Google Scholar]. Akin to fold evolvability, the number and magnitude of promiscuous functions carried by a protein superfamily could reflect their evolvability. This evolvability is likely intertwined with the attributes giving rise to promiscuity: (i) inherent active site reactivity [e.g., provided by cofactors and metal ions (see ‘Molecular heterogeneity’)] [78.Babtie A. et al.What makes an enzyme promiscuous?.Curr. Opin. Chem. Biol. 2010; 14: 200-207Crossref PubMed Scopus (164) Google Scholar]; (ii) versatile active site architectures promoting multiple distinct binding modes (see ‘Refinement of the active site’); (iii) unique folds that support rapid structural rearrangements (see ‘Protein fold’); and, in some cases, (iv) conformational diversity creating functional heterogeneity (see ‘Molecular heterogeneity’). ‘Catalytic landscapes’ depict the relationship between catalytic activities and sequence space, enabling the visualization of highly interconnected functional networks, hidden within enzyme superfamilies (Figure I). This network view exposes unique regions of the sequence space where catalytic landscapes intersect: they contain promiscuous genotypes able to catalyze multiple catalytic activities (Figure I, dashed area) [90.Baier F. et al.Evolution of enzyme superfamilies: comprehensive exploration of sequence–function relationships.Biochemistry. 2016; 55: 6375-6388Crossref PubMed Scopus (48) Google Scholar,94.Baier F. Tokuriki N. Connectivity between catalytic landscapes of the metallo-β-lactamase superfamily.J. Mol. Biol. 2014; 426: 2442-2456Crossref PubMed Scopus (80) Google Scholar]. Such connectivity suggests that enzymes may evolve, from one function to another, through a continuous network of functional sequence space. Consequently, the extent of functional connectivity in a protein superfamily could reflect its evolvability. Yet, the emergence of a given function could be restricted to particular progenitor enzymes: in these superfamilies, two functions may only be connected through a third, intermediary one, effectively restricting the initial genotypes that could evolve. Furthermore, the level and spectrum of promiscuous functions substantially differ between proteins, even among orthologous sequences that share the same native function [16.Khanal A. et al.Differential effects of a mutation on the normal and promiscuous activities of orthologs: implications for natural and directed evolution.Mol. Biol. Evol. 2015; 32: 100-108Crossref PubMed Scopus (48) Google Scholar,17.Baier F. et al.Crypti
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