Dan S. Tawfik

Kemp elimination catalysts by computational enzyme design

The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination—a model reaction for proton transfer from carbon—with measured rate enhancements of up to 105 and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a >200-fold increase in kcat/Km (kcat/Km of 2,600 M-1s-1 and kcat/kuncat of >106). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future.

Enzyme Promiscuity: A Mechanistic and Evolutionary Perspective

Many, if not most, enzymes can promiscuously catalyze reactions, or act on substrates, other than those for which they evolved. Here, we discuss the structural, mechanistic, and evolutionary implications of this manifestation of infidelity of molecular recognition. We define promiscuity and related phenomena and also address their generality and physiological implications. We discuss the mechanistic enzymology of promiscuity--how enzymes, which generally exert exquisite specificity, catalyze other, and sometimes barely related, reactions. Finally, we address the hypothesis that promiscuous enzymatic activities serve as evolutionary starting points and highlight the unique evolutionary features of promiscuous enzyme functions.

The 'evolvability' of promiscuous protein functions

How proteins with new functions (e.g., drug or antibiotic resistance or degradation of man-made chemicals) evolve in a matter of months or years is still unclear. This ability is dependent on the induction of new phenotypic traits by a small number of mutations (plasticity). But mutations often have deleterious effects on functions that are essential for survival. How are these seemingly conflicting demands met at the single-protein level? Results from directed laboratory evolution experiments indicate that the evolution of a new function is driven by mutations that have little effect on the native function but large effects on the promiscuous functions that serve as starting point. Thus, an evolving protein can initially acquire increased fitness for a new function without losing its original function. Gene duplication and the divergence of a completely new protein may then follow.

Protein Dynamism and Evolvability

The traditional view that proteins possess absolute functional specificity and a single, fixed structure conflicts with their marked ability to adapt and evolve new functions and structures. We consider an alternative, “avant-garde view” in which proteins are conformationally dynamic and exhibit functional promiscuity. We surmise that these properties are the foundation stones of protein evolvability; they facilitate the divergence of new functions within existing folds and the evolution of entirely new folds. Packing modes of proteins also affect their evolvability, and poorly packed, disordered, and conformationally diverse proteins may exhibit high evolvability. This dynamic view of protein structure, function, and evolvability is extrapolated to describe hypothetical scenarios for the evolution of the early proteins and future research directions in the area of protein dynamism and evolution.

Stability effects of mutations and protein evolvability

The past several years have seen novel insights at the interface of protein biophysics and evolution. The accepted paradigm that proteins can tolerate nearly any amino acid substitution has been replaced by the view that the deleterious effects of mutations, and especially their tendency to undermine the thermodynamic and kinetic stability of protein, is a major constraint on protein evolvability--the ability of proteins to acquire changes in sequence and function. We summarize recent findings regarding how mutations affect protein stability, and how stability affects protein evolution. We describe ways of predicting and analyzing stability effects of mutations, and mechanisms that buffer or compensate for these destabilizing effects and thereby promote protein evolvabilty, in nature and in the laboratory.

Amplification of complex gene libraries by emulsion PCR

1MRC Laboratory of Molecular Biology, Hills Road, Cambridge, CB2 2QH, UK. 2Department of Biological Chemistry, Weizmann Institute of Science, Rehovot 76100, Israel. 3Institut de Science et d’Ingénierie Supramoléculaires (ISIS), 8 allée Gaspard Monge, BP 70028, 67083 Strasbourg Cedex, France. 4Casali Institute of Applied Chemistry, The Hebrew University of Jerusalem, Givat Ram, 91904, Jerusalem, Israel. Correspondence should be addressed to A.D.G. (griffiths@isis.u-strasbg.fr) or D.S.T. (tawfik@weizmann.ac.il).

Directed evolution of an extremely fast phosphotriesterase by in vitro compartmentalization.

We describe the selection of a phosphotriesterase with a very fast kcat (over 105 s−1), 63 times higher than the already very efficient wild‐type enzyme. The enzyme was selected from a library of 3.4 × 107 mutated phosphotriesterase genes using a novel strategy based on linking genotype and phenotype by in vitro compartmentalization (IVC) using water‐in‐oil emulsions. First, microbeads, each displaying a single gene and multiple copies of the encoded protein, are formed by compartmentalized in vitro translation. These microbeads can then be selected for catalysis or binding. To select for catalysis the microbeads are re‐emulsified in a reaction buffer of choice with a soluble substrate. The product and any unreacted substrate are coupled to the beads when the reaction is finished. Product‐coated beads, displaying active enzymes and the genes that encode them, are detected with anti‐product antibodies and selected using flow cytometry. This completely in vitro process selects for all enzymatic features simultaneously (substrate recognition, product formation, rate acceleration and turnover) and single enzyme molecules can be detected.

How protein stability and new functions trade off.

Numerous studies have noted that the evolution of new enzymatic specificities is accompanied by loss of the proteins thermodynamic stability (ΔΔG), thus suggesting a tradeoff between the acquisition of new enzymatic functions and stability. However, since most mutations are destabilizing (ΔΔG>0), one should ask how destabilizing mutations that confer new or altered enzymatic functions relative to all other mutations are. We applied ΔΔG computations by FoldX to analyze the effects of 548 mutations that arose from the directed evolution of 22 different enzymes. The stability effects, location, and type of function-altering mutations were compared to ΔΔG changes arising from all possible point mutations in the same enzymes. We found that mutations that modulate enzymatic functions are mostly destabilizing (average ΔΔG = +0.9 kcal/mol), and are almost as destabilizing as the “average” mutation in these enzymes (+1.3 kcal/mol). Although their stability effects are not as dramatic as in key catalytic residues, mutations that modify the substrate binding pockets, and thus mediate new enzymatic specificities, place a larger stability burden than surface mutations that underline neutral, non-adaptive evolutionary changes. How are the destabilizing effects of functional mutations balanced to enable adaptation? Our analysis also indicated that many mutations that appear in directed evolution variants with no obvious role in the new function exert stabilizing effects that may compensate for the destabilizing effects of the crucial function-altering mutations. Thus, the evolution of new enzymatic activities, both in nature and in the laboratory, is dependent on the compensatory, stabilizing effect of apparently “silent” mutations in regions of the protein that are irrelevant to its function.

Chaperonin overexpression promotes genetic variation and enzyme evolution

Most protein mutations, and mutations that alter protein functions in particular, undermine stability and are therefore deleterious. Chaperones, or heat-shock proteins, are often implicated in buffering mutations, and could thus facilitate the acquisition of neutral genetic diversity and the rate of adaptation. We examined the ability of the Escherichia coli GroEL/GroES chaperonins to buffer destabilizing and adaptive mutations. Here we show that mutational drifts performed in vitro with four different enzymes indicated that GroEL/GroES overexpression doubled the number of accumulating mutations, and promoted the folding of enzyme variants carrying mutations in the protein core and/or mutations with higher destabilizing effects (destabilization energies of >3.5 kcal mol-1, on average, versus ∼1 kcal mol-1 in the absence of GroEL/GroES). The divergence of modified enzymatic specificity occurred much faster under GroEL/GroES overexpression, in terms of the number of adapted variants (≥2-fold) and their improved specificity and activity (≥10-fold). These results indicate that protein stability is a major constraint in protein evolution, and buffering mechanisms such as chaperonins are key in alleviating this constraint.

Robustness-epistasis link shapes the fitness landscape of a randomly drifting protein.

The distribution of fitness effects of protein mutations is still unknown. Of particular interest is whether accumulating deleterious mutations interact, and how the resulting epistatic effects shape the protein’s fitness landscape. Here we apply a model system in which bacterial fitness correlates with the enzymatic activity of TEM-1 β-lactamase (antibiotic degradation). Subjecting TEM-1 to random mutational drift and purifying selection (to purge deleterious mutations) produced changes in its fitness landscape indicative of negative epistasis; that is, the combined deleterious effects of mutations were, on average, larger than expected from the multiplication of their individual effects. As observed in computational systems, negative epistasis was tightly associated with higher tolerance to mutations (robustness). Thus, under a low selection pressure, a large fraction of mutations was initially tolerated (high robustness), but as mutations accumulated, their fitness toll increased, resulting in the observed negative epistasis. These findings, supported by FoldX stability computations of the mutational effects, prompt a new model in which the mutational robustness (or neutrality) observed in proteins, and other biological systems, is due primarily to a stability margin, or threshold, that buffers the deleterious physico-chemical effects of mutations on fitness. Threshold robustness is inherently epistatic—once the stability threshold is exhausted, the deleterious effects of mutations become fully pronounced, thereby making proteins far less robust than generally assumed.