Rational Design of Photocatalysts for Controlled Polymerization: Effect of Structures on Photocatalytic Activities

Over the past decade, the use of photocatalysts (PCs) in controlled polymerization has brought new opportunities in sophisticated macromolecular synthesis. However, the selection of PCs in these systems has been typically based on laborious trial-and-error strategies. To tackle this limitation, computer-guided rational design of PCs based on knowledge of structure-property-performance relationships has emerged. These rational strategies provide rapid and economic methodologies for tuning the performance and functionality of a polymerization system, thus providing further opportunities for polymer science. This review provides an overview of PCs employed in photocontrolled polymerization systems and summarizes their progression from early systems to the current state-of-the-art. Background theories on electronic transitions are also introduced to establish the structure-property-performance relationships from a perspective of quantum chemistry. Typical examples for each type of structure-property relationships are then presented to enlighten future design of PCs for photocontrolled polymerization.

Structure-based reconstruction of a Mycobacterium hypothetical protein into an active Δ5-3-ketosteroid isomerase

Protein engineering based on structure homology holds the potential to engineer steroid-transforming enzymes on demand. Based on the genome sequencing analysis of industrial Mycobacterium strain HGMS2 to produce 4-androstene-3,17-dione (4-AD), three hypothetical proteins were predicted as putative Δ⁵-3-ketosteroid isomerases (KSIs) to catalyze an intramolecular proton transfer involving the transformation of 5-androstene-3,17-dione (5-AD) into 4-AD, which were defined as mKSI228, mKSI291 and mKSI753. Activity assays indicated that mKSI228 and mKSI291 exhibited weak activity, as low as 0.7% and 1.5%, respectively, of a well-studied and highly active KSI from Pseudomonas putida KSI (pKSI), while mKSI753 had no activity similar to Mycobacterium tuberculosis KSI (mtKSI). Although the 3D structures of the putative mKSIs were homologous to pKSI, their amino acid sequences were significantly different from those of pKSI and tKSI. Thus, by use of these two KSIs as homology models, we were able to convert the low-active mKSI291 into a high-active active KSI by site-directed mutagenesis. On the other hand, an X-ray crystallographic structure of mKSI291 identified a water molecule in its active site. This unique water molecule might function as a bridge to connect Ser-OH, Tyr57-OH and C3O of the intermediate form a hydrogen-bonding network that was responsible for its weak activity, compared with that of mtKSI. Our results not only demonstrated the use of a protein engineering approach to understanding KSI catalytic mechanism, but also provided an example for engineering the catalytic active sites and gaining a functional enzyme based on homologous structures.

Alkene hydrogenation activity of enoate reductases for an environmentally benign biosynthesis of adipic acid

Adipic acid, a precursor for Nylon-6,6 polymer, is one of the most important commodity chemicals, which is currently produced from petroleum. The biosynthesis of adipic acid from glucose still remains challenging due to the absence of biocatalysts required for the hydrogenation of unsaturated six-carbon dicarboxylic acids to adipic acid. Here, we demonstrate the first enzymatic hydrogenation of 2-hexenedioic acid and muconic acid to adipic acid using enoate reductases (ERs). ERs can hydrogenate 2-hexenedioic acid and muconic acid producing adipic acid with a high conversion rate and yield in vivo and in vitro. Purified ERs exhibit a broad substrate spectrum including aromatic and aliphatic 2-enoates and a significant oxygen tolerance. The discovery of the hydrogenation activity of ERs contributes to an understanding of the catalytic mechanism of these poorly characterized enzymes and enables the environmentally benign biosynthesis of adipic acid and other chemicals from renewable resources.

Speeding up enzyme engineering computationally

Can in silico engineering speed up the delivery of biocatalysts for the burgeoning bioeconomy? In this issue, Kamerlin and coworkers introduce CADEE [Amrein et al. (2017), IUCrJ, 4, 50-64] - a framework for Computer-Aided Directed Evolution of Enzymes - that promises to lessen the burden on 'wet lab' enzymologists when optimizing biocatalysts using laboratory-based directed evolution methods.

A Single-Site Mutation at Ser146 Expands the Reactivity of the Oxygenase Component of p-Hydroxyphenylacetate 3-Hydroxylase

The oxygenase component (C₂) of p-hydroxyphenylacetate (4-HPA) 3-hydroxylase (HPAH) from Acinetobacter baumannii catalyzes the hydroxylation of various phenolic acids. In this report, we found that substitution of a residue close to the phenolic group binding site to yield the S146A variant resulted in an enzyme that is more effective than the wild-type in catalyzing the hydroxylation of 4-aminophenylacetate (4-APA). Product yields for both wild-type and S146A enzymes are better at lower pH values. Multiple turnover reactions of the wild-type and S146A enzymes indicate that both enzymes first hydroxylate 3-APA to give 3-hydroxy-4-aminophenylacetate (3-OH-4-APA), which is further hydroxylated to give 3,5-dihydroxy-4-aminophenylacetate, similar to the reaction of C₂ with 4-HPA. Stopped-flow experiments showed that 4-APA can only bind to the wild-type enzyme at pH 6.0 and not at pH 9.0, while it can bind to S146A under both pH conditions. Rapid-quench flow results indicate that the wild-type enzyme has low reactivity toward 4-APA hydroxylation, with a hydroxylation rate constant (k_OH) for 4-APA of 0.028 s^-1 compared to 17 s^-1 for 4-HPA, the native substrate. In contrast, for S146A, the hydroxylation rate constants for both substrates are very similar (2.6 s^-1 for 4-HPA versus 2.5 s^-1 for 4-APA). These data indicate that Ser146 is a key catalytic residue involved in optimizing C₂ reactivity toward a phenolic compound. Removing this hydroxyl group expands C₂ activity toward a non-natural aniline substrate. This understanding should be helpful for future rational engineering of other two-component flavin-dependent monooxygenases that have this conserved Ser residue.

Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

The amino acid sequence of a protein affects both its structure and its function. Thus, the ability to modify the sequence, and hence the structure and activity, of individual proteins in a systematic way, opens up many opportunities, both scientifically and (as we focus on here) for exploitation in biocatalysis. Modern methods of synthetic biology, whereby increasingly large sequences of DNA can be synthesised de novo, allow an unprecedented ability to engineer proteins with novel functions. However, the number of possible proteins is far too large to test individually, so we need means for navigating the 'search space' of possible protein sequences efficiently and reliably in order to find desirable activities and other properties. Enzymologists distinguish binding (Kd) and catalytic (kcat) steps. In a similar way, judicious strategies have blended design (for binding, specificity and active site modelling) with the more empirical methods of classical directed evolution (DE) for improving kcat (where natural evolution rarely seeks the highest values), especially with regard to residues distant from the active site and where the functional linkages underpinning enzyme dynamics are both unknown and hard to predict. Epistasis (where the 'best' amino acid at one site depends on that or those at others) is a notable feature of directed evolution. The aim of this review is to highlight some of the approaches that are being developed to allow us to use directed evolution to improve enzyme properties, often dramatically. We note that directed evolution differs in a number of ways from natural evolution, including in particular the available mechanisms and the likely selection pressures. Thus, we stress the opportunities afforded by techniques that enable one to map sequence to (structure and) activity in silico, as an effective means of modelling and exploring protein landscapes. Because known landscapes may be assessed and reasoned about as a whole, simultaneously, this offers opportunities for protein improvement not readily available to natural evolution on rapid timescales. Intelligent landscape navigation, informed by sequence-activity relationships and coupled to the emerging methods of synthetic biology, offers scope for the development of novel biocatalysts that are both highly active and robust.

A water-dependent kinetics guide for complex lipase-mediated synthesis of biolubricants in a water activity control reactor

A water-dependent kinetic model for a lipase-mediated reaction with multiple substrates and products in a water activity control reactor was developed.