RetroBioCat Database: A Platform for Collaborative Curation and Automated Meta-Analysis of Biocatalysis Data

Indigo production identifies hotspots in cytochrome P450 BM3 for diversifying aromatic hydroxylation

Evolution of P450 BM3 is a topic of extensive research, but screening the various substrate/reaction combinations remains a time-consuming process. Indigo production has the potential to serve as a simple high-throughput method for reaction screening, as bacterial colonies expressing indigo (+) variants can be visually identified via their blue phenotype. Indigo (+) single variants, indigo (-) single variants and a combinatorial library, containing mutations that enable the blue phenotype, were screened for their ability to hydroxylate a panel of 12 aromatic compounds using the 4-aminoantipyrine colorimetric assay. Recombination of indigo (+) single variants to create a multiple-variant library is a particularly useful strategy, as all top performing P450 BM3 variants with high hydroxylation activity were either indigo (+) single variants or contained multiple substitutions. Furthermore, active variants, as determined using the 4-AAP assay, were further characterized and several variants were identified that gave more than 90% conversion with 1,3-dichlorobenzene and predominantly formed 2,6-dichlorophenol; other variants showed significant substrate selectivity. This supports the hypothesis that substitution at positions that enable the indigo (+) phenotype, or hotspot residues, is a general mechanism for increasing aromatic hydroxylation activity. Overall, this research demonstrates that indigo (+) single variants, identified via colorimetric colony-based screening, may be recombined to generate a multiply-substituted variant library containing many variants with high aromatic hydroxylation activity. The combination of colony-based screening and other screening assays greatly accelerates enzyme engineering, as readily-identified indigo (+) single variants can be recombined to create a library of active multiple variants without extensive screening of single variants.

Developing deprotectase biocatalysts for synthesis

Organic synthesis often requires multiple steps where a functional group (FG) is concealed from reaction by a protecting group (PG). Common PGs include N-carbobenzyloxy (Cbz or Z) of amines and tert-butyloxycarbonyl (OtBu) of acids. An essential step is the removal of the PG, but this often requires excess reagents, extensive time and can have low % yield. An overarching goal of biocatalysis is to use "green" or "enzymatic" methods to catalyse chemical transformations. One under-utilised approach is the use of "deprotectase" biocatalysts to selectively remove PGs from various organic substrates. The advantage of this methodology is the exquisite selectivity of the biocatalyst to only act on its target, leaving other FGs and PGs untouched. A number of deprotectase biocatalysts have been reported but they are not commonly used in mainstream synthetic routes. This study describes the construction of a cascade to deprotect doubly-protected amino acids. The well known Bacillus BS2 esterase was used to remove the OtBu PG from various amino acid substrates. The more obscure Sphingomonas Cbz-ase (amidohydrolase) was screened with a range of N-Cbz-modified amino acid substrates. We then combined both the BS2 and Cbz-ase together for a 1 pot, 2 step deprotection of the model substrate CBz-L-Phe OtBu to produce the free L-Phe. We also provide some insight into the residues involved in substrate recognition and catalysis using docked ligands in the crystal structure of BS2. Similarly, a structural model of the Cbz-ase identifies a potential di-metal binding site and reveals conserved active site residues. This new biocatalytic cascade should be further explored for its application in chemical synthesis.

Artificial Intelligence Methods and Models for Retro-Biosynthesis: A Scoping Review

Retrosynthesis aims to efficiently plan the synthesis of desirable chemicals by strategically breaking down molecules into readily available building block compounds. Having a long history in chemistry, retro-biosynthesis has also been used in the fields of biocatalysis and synthetic biology. Artificial intelligence (AI) is driving us toward new frontiers in synthesis planning and the exploration of chemical spaces, arriving at an opportune moment for promoting bioproduction that would better align with green chemistry, enhancing environmental practices. In this review, we summarize the recent advancements in the application of AI methods and models for retrosynthetic and retro-biosynthetic pathway design. These techniques can be based either on reaction templates or generative models and require scoring functions and planning strategies to navigate through the retrosynthetic graph of possibilities. We finally discuss limitations and promising research directions in this field.

The Development and Opportunities of Predictive Biotechnology

Recent advances in bioeconomy allow a holistic view of existing and new process chains and enable novel production routines continuously advanced by academia and industry. All this progress benefits from a growing number of prediction tools that have found their way into the field. For example, automated genome annotations, tools for building model structures of proteins, and structural protein prediction methods such as AlphaFold2TM or RoseTTAFold have gained popularity in recent years. Recently, it has become apparent that more and more AI-based tools are being developed and used for biocatalysis and biotechnology. This is an excellent opportunity for academia and industry to accelerate advancements in the field further. Biotechnology, as a rapidly growing interdisciplinary field, stands to benefit greatly from these developments.

Choose Your Own Adventure: A Comprehensive Database of Reactions Catalyzed by Cytochrome P450 BM3 Variants

Cytochrome P450 BM3 monooxygenase is the topic of extensive research as many researchers have evolved this enzyme to generate a variety of products. However, the abundance of information on increasingly diversified variants of P450 BM3 that catalyze a broad array of chemistry is not in a format that enables easy extraction and interpretation. We present a database that categorizes variants by their catalyzed reactions and includes details about substrates to provide reaction context. This database of >1500 P450 BM3 variants is downloadable and machine-readable and includes instructions to maximize ease of gathering information. The database allows rapid identification of commonly reported substitutions, aiding researchers who are unfamiliar with the enzyme in identifying starting points for enzyme engineering. For those actively engaged in engineering P450 BM3, the database, along with this review, provides a powerful and user-friendly platform to understand, predict, and identify the attributes of P450 BM3 variants, encouraging the further engineering of this enzyme.

Genome Mining for New Enzyme Chemistry

A revolution in the field of biocatalysis has enabled scalable access to compounds of high societal values using enzymes. The construction of biocatalytic routes relies on the reservoir of available enzymatic transformations. A review of uncharacterized proteins predicted from genomic sequencing projects shows that a treasure trove of enzyme chemistry awaits to be uncovered. This Review highlights enzymatic transformations discovered through various genome mining methods and showcases their potential future applications in biocatalysis.

Biocatalysis: landmark discoveries and applications in chemical synthesis

Biocatalysis has become an important tool in chemical synthesis, allowing access to complex molecules with high levels of activity and selectivity and with low environmental impact. Key discoveries in protein engineering, bioinformatics, recombinant technology and DNA sequencing have contributed towards the rapid acceleration of the field. This tutorial review explores enzyme engineering strategies and high-throughput screening approaches that have been applied for the discovery and development of enzymes for synthetic application. Landmark developments in the field are discussed and have been carefully selected to highlight the diverse synthetic applications of enzymes within the pharmaceutical, agricultural, food and chemical industries. The design and development of artificial biocatalytic cascades is also examined. This tutorial review will give readers an insight into the landmark discoveries and milestones that have helped shape and grow this branch of catalysis since the discovery of the first enzyme.

Multienzymatic Cascades and Nanomaterial Scaffolding-A Potential Way Forward for the Efficient Biosynthesis of Novel Chemical Products

Synthetic biology is touted as the next industrial revolution as it promises access to greener biocatalytic syntheses to replace many industrial organic chemistries. Here, it is shown to what synthetic biology can offer in the form of multienzyme cascades for the synthesis of the most basic of new materials-chemicals, including especially designer chemical products and their analogs. Since achieving this is predicated on dramatically expanding the chemical space that enzymes access, such chemistry will probably be undertaken in cell-free or minimalist formats to overcome the inherent toxicity of non-natural substrates to living cells. Laying out relevant aspects that need to be considered in the design of multi-enzymatic cascades for these purposes is begun. Representative multienzymatic cascades are critically reviewed, which have been specifically developed for the synthesis of compounds that have either been made only by traditional organic synthesis along with those cascades utilized for novel compound syntheses. Lastly, an overview of strategies that look toward exploiting bio/nanomaterials for accessing channeling and other nanoscale materials phenomena in vitro to direct novel enzymatic biosynthesis and improve catalytic efficiency is provided. Finally, a perspective on what is needed for this field to develop in the short and long term is presented.

Enzyme Databases in the Era of Omics and Artificial Intelligence

Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over the years, various databases that cover different aspects of enzyme biology (e.g., kinetic parameters, enzyme occurrence, and reaction mechanisms) have been developed. Most of the databases are curated manually, which improves reliability of the information; however, such curation cannot keep pace with the exponential growth in published data. Lack of data standardization is another obstacle for data extraction and analysis. Improving machine readability of databases is especially important in the light of recent advances in deep learning algorithms that require big training datasets. This review provides information regarding the current state of enzyme databases, especially in relation to the ever-increasing amount of generated research data and recent advancements in artificial intelligence algorithms. Furthermore, it describes several enzyme databases, providing the reader with necessary information for their use.