A Noncanonical Tryptophan Analogue Reveals an Active Site Hydrogen Bond Controlling Ferryl Reactivity in a Heme Peroxidase

From nature to industry: Harnessing enzymes for biocatalysis

Biocatalysis harnesses enzymes to make valuable products. This green technology is used in countless applications from bench scale to industrial production and allows practitioners to access complex organic molecules, often with fewer synthetic steps and reduced waste. The last decade has seen an explosion in the development of experimental and computational tools to tailor enzymatic properties, equipping enzyme engineers with the ability to create biocatalysts that perform reactions not present in nature. By using (chemo)-enzymatic synthesis routes or orchestrating intricate enzyme cascades, scientists can synthesize elaborate targets ranging from DNA and complex pharmaceuticals to starch made in vitro from CO2-derived methanol. In addition, new chemistries have emerged through the combination of biocatalysis with transition metal catalysis, photocatalysis, and electrocatalysis. This review highlights recent key developments, identifies current limitations, and provides a future prospect for this rapidly developing technology.

Engineering mutually orthogonal PylRS/tRNA pairs for dual encoding of functional histidine analogues

The availability of an expanded genetic code opens exciting new opportunities in enzyme design and engineering. In this regard histidine analogues have proven particularly versatile, serving as ligands to augment metalloenzyme function and as catalytic nucleophiles in designed enzymes. The ability to genetically encode multiple functional residues could greatly expand the range of chemistry accessible within enzyme active sites. Here, we develop mutually orthogonal translation components to selectively encode two structurally similar histidine analogues. Transplanting known mutations from a promiscuous Methanosarcina mazei pyrrolysyl-tRNA synthetase (MmPylRSIFGFF ) into a single domain PylRS from Methanomethylophilus alvus (MaPylRSIFGFF ) provided a variant with improved efficiency and specificity for 3-methyl-L-histidine (MeHis) incorporation. The MaPylRSIFGFF clone was further characterized using in vitro biochemical assays and x-ray crystallography. We subsequently engineered the orthogonal MmPylRS for activity and selectivity for 3-(3-pyridyl)-L-alanine (3-Pyr), which was used in combination with MaPylRSIFGFF to produce proteins containing both 3-Pyr and MeHis. Given the versatile roles played by histidine in enzyme mechanisms, we anticipate that the tools developed within this study will underpin the development of enzymes with new and enhanced functions.

Engineering enzyme activity using an expanded amino acid alphabet

Enzyme design and engineering strategies are typically constrained by the limited size of nature's genetic alphabet, comprised of only 20 canonical amino acids. In recent years, site-selective incorporation of non-canonical amino acids (ncAAs) via an expanded genetic code has emerged as a powerful means of inserting new functional components into proteins, with hundreds of structurally diverse ncAAs now available. Here, we highlight how the emergence of an expanded repertoire of amino acids has opened new avenues in enzyme design and engineering. ncAAs have been used to probe complex biological mechanisms, augment enzyme function and, most ambitiously, embed new catalytic mechanisms into protein active sites that would be challenging to access within the constraints of nature's genetic code. We predict that the studies reviewed in this article, along with further advances in genetic code expansion technology, will establish ncAA incorporation as an increasingly important tool for biocatalysis in the coming years.

The road to fully programmable protein catalysis

The ability to design efficient enzymes from scratch would have a profound effect on chemistry, biotechnology and medicine. Rapid progress in protein engineering over the past decade makes us optimistic that this ambition is within reach. The development of artificial enzymes containing metal cofactors and noncanonical organocatalytic groups shows how protein structure can be optimized to harness the reactivity of nonproteinogenic elements. In parallel, computational methods have been used to design protein catalysts for diverse reactions on the basis of fundamental principles of transition state stabilization. Although the activities of designed catalysts have been quite low, extensive laboratory evolution has been used to generate efficient enzymes. Structural analysis of these systems has revealed the high degree of precision that will be needed to design catalysts with greater activity. To this end, emerging protein design methods, including deep learning, hold particular promise for improving model accuracy. Here we take stock of key developments in the field and highlight new opportunities for innovation that should allow us to transition beyond the current state of the art and enable the robust design of biocatalysts to address societal needs.

Energetic Basis and Design of Enzyme Function Demonstrated Using GFP, an Excited-State Enzyme

The past decades have witnessed an explosion of de novo protein designs with a remarkable range of scaffolds. It remains challenging, however, to design catalytic functions that are competitive with naturally occurring counterparts as well as biomimetic or nonbiological catalysts. Although directed evolution often offers efficient solutions, the fitness landscape remains opaque. Green fluorescent protein (GFP), which has revolutionized biological imaging and assays, is one of the most redesigned proteins. While not an enzyme in the conventional sense, GFPs feature competing excited-state decay pathways with the same steric and electrostatic origins as conventional ground-state catalysts, and they exert exquisite control over multiple reaction outcomes through the same principles. Thus, GFP is an "excited-state enzyme". Herein we show that rationally designed mutants and hybrids that contain environmental mutations and substituted chromophores provide the basis for a quantitative model and prediction that describes the influence of sterics and electrostatics on excited-state catalysis of GFPs. As both perturbations can selectively bias photoisomerization pathways, GFPs with fluorescence quantum yields (FQYs) and photoswitching characteristics tailored for specific applications could be predicted and then demonstrated. The underlying energetic landscape, readily accessible via spectroscopy for GFPs, offers an important missing link in the design of protein function that is generalizable to catalyst design.