A mechanistic view of enzyme evolution

Abstract

New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity‐enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.

Known Evolutionary Paths Are Accessible to Engineered ß-Lactamases Having Altered Protein Motions at the Timescale of Catalytic Turnover

“…Protein dynamics may thus promote non-additive interaction of mutations (Miton and Tokuriki, 2016). Increasing our understanding of the biophysical features that facilitate protein evolution finds practical applications in better directing protein engineering (Johansson and Lindorff-Larsen, 2018;Maria-Solano et al, 2018;Trudeau and Tawfik, 2019;Gardner et al, 2020;Yang et al, 2020).…”

“…Intragenic epistasis describes the non-additive effect of mutations on protein fitness. It has been shown to hinder predictability in protein engineering experiments (Carneiro and Hartl, 2010;Reetz, 2013;Meini et al, 2015;Miton and Tokuriki, 2016;Starr and Thornton, 2016;Yang et al, 2020), highlighting the need for investigation into its causes and effects. In recent years, deepmutational scanning has been applied to extensively investigate both the impact of single mutations on a given function (Firnberg et al, 2014;Shin and Cho, 2015;Klesmith et al, 2017) and, of particular interest with respect to intragenic epistasis, all possible combinations of double mutants (Olson et al, 2014).…”

“…Mutations that individually have a beneficial effect on fitness can act synergistically (positive epistasis) or can be deleterious when combined (negative sign epistasis); on the other hand, deleterious mutations can be beneficial when combined (positive sign epistasis; Starr and Thornton, 2016). The variety of epistatic interactions imposes constraints on mutational pathways leading to a new protein function: pathways that include a node with lower fitness are not evolutionarily accessible whereas specific pathways can be decided by early, positive epistatic effects in evolution (Poelwijk et al, 2007;Salverda et al, 2011;Meini et al, 2015;Miton and Tokuriki, 2016;Yang et al, 2020). Factors known to influence epistasis include direct inter-residue interactions as well as long-range interactions mediated by dynamic networks and protein stability (Miton and Tokuriki, 2016;Starr and Thornton, 2016).…”

“…Factors known to influence epistasis include direct inter-residue interactions as well as long-range interactions mediated by dynamic networks and protein stability (Miton and Tokuriki, 2016;Starr and Thornton, 2016). Despite increasing evidence that protein dynamics modulate function and fitness (Eisenmesser et al, 2002;Doucet et al, 2007;Osuna et al, 2015;Campbell et al, 2016;Duff et al, 2018;Maria-Solano et al, 2018;Yang et al, 2020), the impact of protein dynamics on intragenic epistasis is not well-understood.…”

Stability of ligand-induced protein conformation influences affinity in maltose-binding protein

“…We are no longer limited to static high-resolution structures but can also probe the conformational dynamics of a protein, for instance by single-molecule FRET. The simplest but somewhat naive way to explain ligand affinity deals with the architecture of the binding pocket, which needs to allow for enough protein-ligand interactions and proper orientation of the ligand (4,13,43,44). Differences in ligand affinity of homologous proteins have been explained by differences in binding pocket organization (38,45).…”