Fast Knoevenagel Condensations Catalyzed by an Artificial Schiff-Base-Forming Enzyme

DABCO-catalyzed Knoevenagel condensation of aldehydes with ethyl cyanoacetate using hydroxy ionic liquid as a promoter

N-(2-Hydroxy-ethyl)-pyridinium chloride ([HyEtPy]Cl) was synthesized and explored as a novel promoter for 1,4-diazabicyclo [2.2.2] octane (DABCO)-catalyzed Knoevenagel condensation reactions, which showed better catalytic activity compared to other ionic liquid (IL) that had no hydroxyl group attached to the IL scaffold. The effect of hydrogen bond formation between the hydroxyl group of [HyEtPy]Cl and the carbonyl group of aldehyde played an important role in the Knoevenagel condensation reaction. In the [HyEtPy]Cl–H₂O–DABCO composite system, Knoevenagel condensation reactions proceeded smoothly and cleanly, and the corresponding Knoevenagel condensation products were obtained in good to excellent yields in all cases examined. This protocol provides a versatile solvent–catalyst system, which has notable advantages such as being eco-friendly, ease of work-up and convenient reuse of the ionic liquid.

N-(2-Hydroxy-ethyl)-pyridinium chloride ([HyEtPy]Cl) was synthesized and explored as a novel promoter for 1,4-diazabicyclo [2.2.2] octane (DABCO)-catalyzed Knoevenagel condensation reactions, excellent catalytic activity was obtained.

Role of Conformational Dynamics in the Evolution of Retro-Aldolase Activity

Enzymes exist as ensembles of conformations that are important for function. Tuning these populations of conformational states through mutation enables evolution toward additional activities. Here we computationally evaluate the population shifts induced by distal and active site mutations in a family of computationally designed and experimentally optimized retro-aldolases. The conformational landscape of these enzymes was significantly altered during evolution, as pre-existing catalytically active conformational substates became major states in the most evolved variants. We further demonstrate that key residues responsible for these substate conversions can be predicted computationally. Significantly, the identified residues coincide with those positions mutated in the laboratory evolution experiments. This study establishes that distal mutations that affect enzyme catalytic activity can be predicted computationally and thus provides the enzyme (re)design field with a rational strategy to determine promising sites for enhancing activity through mutation.

Enzyme engineering: reaching the maximal catalytic efficiency peak

The practical need for highly efficient enzymes presents new challenges in enzyme engineering, in particular, the need to improve catalytic turnover (k_cat) or efficiency (k_cat/K_M) by several orders of magnitude. However, optimizing catalysis demands navigation through complex and rugged fitness landscapes, with optimization trajectories often leading to strong diminishing returns and dead-ends. When no further improvements are observed in library screens or selections, it remains unclear whether the maximal catalytic efficiency of the enzyme (the catalytic 'fitness peak') has been reached; or perhaps, an alternative combination of mutations exists that could yield additional improvements. Here, we discuss fundamental aspects of the process of catalytic optimization, and offer practical solutions with respect to overcoming optimization plateaus.

Computational Redesign of Acyl-ACP Thioesterase with Improved Selectivity toward Medium-Chain-Length Fatty Acids

Enzyme and metabolic engineering offer the potential to develop biocatalysts for converting natural resources into a wide range of chemicals. To broaden the scope of potential products beyond natural metabolites, methods of engineering enzymes to accept alternative substrates and/or perform novel chemistries must be developed. DNA synthesis can create large libraries of enzyme-coding sequences, but most biochemistries lack a simple assay to screen for promising enzyme variants. Our solution to this challenge is structure-guided mutagenesis in which optimization algorithms select the best sequences from libraries based on specified criteria (i.e. binding selectivity). Here, we demonstrate this approach by identifying medium-chain (C₆-C₁₂) acyl-ACP thioesterases through structure-guided mutagenesis. Medium-chain fatty acids, products of thioesterase-catalyzed hydrolysis, are limited in natural abundance compared to long-chain fatty acids; the limited supply leads to high costs of C₆-C₁₀ oleochemicals such as fatty alcohols, amines, and esters. Here, we applied computational tools to tune substrate binding to the highly-active 'TesA thioesterase in Escherichia coli. We used the IPRO algorithm to design thioesterase variants with enhanced C₁₂- or C₈-specificity while maintaining high activity. After four rounds of structure-guided mutagenesis, we identified three thioesterases with enhanced production of dodecanoic acid (C₁₂) and twenty-seven thioesterases with enhanced production of octanoic acid (C₈). The top variants reached up to 49% C₁₂ and 50% C₈ while exceeding native levels of total free fatty acids. A comparably sized library created by random mutagenesis failed to identify promising mutants. The chain length-preference of 'TesA and the best mutant were confirmed in vitro using acyl-CoA substrates. Molecular dynamics simulations, confirmed by resolved crystal structures, of 'TesA variants suggest that hydrophobic forces govern 'TesA substrate specificity. We expect that the design rules we uncovered and the thioesterase variants identified will be useful to metabolic engineering projects aimed at sustainable production of medium-chain oleochemicals.

Novel Hydrogen-Bonding Cross-Linking Aggregation-Induced Emission: Water as a Fluorescent "Ribbon" Detected in a Wide Range

The development of efficient sensors for detection of the water content in a wide detection range is highly desirable for balance in many industrial processes and products. Presented herein are six novel different substituted Schiff base Zn(II) complexes, which exhibit the remarkable capability to detect traces of water in a wide linear range (most can reach 0-94%, v/v), low detection limit of 0.2% (v/v), and rapid response time of 8 s in various organic solvents by virtue of an unusual water-activated hydrogen-bonding cross-linking AIE (WHCAIE) mechanism. As a proof-of-concept, the WHCAIE mechanism is explained well by single X-ray diffraction, absorption spectra, fluorescence spectra, dynamic light scattering, ¹H NMR spectra, and theoretical calculations. In addition, the molecules demonstrated their application for the detection of humidity (42-80%). These Schiff base Zn(II) complexes become one of the most powerful water sensors known due to their extraordinary sensitivity, fast response, and wide detection range for water.

Chemoselective Henry Condensations Catalyzed by Artificial Carboligases

The promiscuity of de novo designed enzymes provides a privileged platform for diverse abiological reactions. In this work, we report the first example of a nitroolefin synthase that catalyzes the Henry condensation between aromatic aldehydes and nitromethane. Significant catalytic activity was discovered in the computationally designed and evolved carboligase RA95.5-8, and mutations around the active site were shown to improve the reaction rate, demonstrating the potential to optimize the enzyme by directed evolution. This novel nitroolefin synthase could participate in complex biological cascades, whereby the highly tunable chemoselectivity could afford useful synthetic building blocks.

Hacking nature: genetic tools for reprograming enzymes

Enzymes have many modern industrial applications, from biomass decomposition in the production of biofuels to highly stereospecific biotransformations in pharmaceutical manufacture. The capacity to find or engineer enzymes with activities pertinent to specific applications has been essential for the growth of a multibillion dollar enzyme industry. Over the course of the past 50–60 years our capacity to address this issue has become increasingly sophisticated, supported by innumerable advances, from early discoveries such as the co-linearity of DNA and protein sequence1 to modern computational technologies for enzyme design. The design of enzyme function is an exciting nexus of fundamental biochemical understanding and applied engineering. Herein, we will cover some of the methods used in discovery and design, including some ‘next generation’ tools.

Enantiocomplementary Synthesis of γ-Nitroketones Using Designed and Evolved Carboligases

Artificial enzymes created by computational design and directed evolution are versatile biocatalysts whose promiscuous activities represent potentially attractive starting points for divergent evolution in the laboratory. The artificial aldolase RA95.5-8, for example, exploits amine catalysis to promote mechanistically diverse carboligations. Here we report that RA95.5-8 variants catalyze the asymmetric synthesis of γ-nitroketones via two alternative enantiocomplementary Michael-type reactions: enamine-mediated addition of acetone to nitrostyrenes, and nitroalkane addition to conjugated ketones activated as iminium ions. In addition, a cascade of three aldolase-catalyzed reactions enables one-pot assembly of γ-nitroketones from three simpler building blocks. Together, our results highlight the chemical versatility of artificial aldolases for the practical synthesis of important chiral synthons.

Computational tools for the evaluation of laboratory-engineered biocatalysts

Biocatalysis is based on the application of natural catalysts for new purposes, for which enzymes were not designed. Although the first examples of biocatalysis were reported more than a century ago, biocatalysis was revolutionized after the discovery of an in vitro version of Darwinian evolution called Directed Evolution (DE). Despite the recent advances in the field, major challenges remain to be addressed. Currently, the best experimental approach consists of creating multiple mutations simultaneously while limiting the choices using statistical methods. Still, tens of thousands of variants need to be tested experimentally, and little information is available on how these mutations lead to enhanced enzyme proficiency. This review aims to provide a brief description of the available computational techniques to unveil the molecular basis of improved catalysis achieved by DE. An overview of the strengths and weaknesses of current computational strategies is explored with some recent representative examples. The understanding of how this powerful technique is able to obtain highly active variants is important for the future development of more robust computational methods to predict amino-acid changes needed for activity.

Applied evolutionary theories for engineering of secondary metabolic pathways

An expanded definition of 'secondary metabolism' is emerging. Once the exclusive provenance of naturally occurring organisms, evolved over geological time scales, secondary metabolism increasingly encompasses molecules generated via human engineered biocatalysts and biosynthetic pathways. Many of the tools and strategies for enzyme and pathway engineering can find origins in evolutionary theories. This perspective presents an overview of selected proposed evolutionary strategies in the context of engineering secondary metabolism. In addition to the wealth of biocatalysts provided via secondary metabolic pathways, improving the understanding of biosynthetic pathway evolution will provide rich resources for methods to adapt to applied laboratory evolution.