Shifting redox reaction equilibria on demand using an orthogonal redox cofactor.

Nature's two redox cofactors, nicotinamide adenine dinucleotide (NAD+) and nicotinamide adenine dinucleotide phosphate (NADP+), are held at different reduction potentials, driving catabolism and anabolism in opposite directions. In biomanufacturing, there is a need to flexibly control redox reaction direction decoupled from catabolism and anabolism. We established nicotinamide mononucleotide (NMN+) as a noncanonical cofactor orthogonal to NAD(P)+. Here we present the development of Nox Ortho, a reduced NMN+ (NMNH)-specific oxidase, that completes the toolkit to modulate NMNH:NMN+ ratio together with an NMN+-specific glucose dehydrogenase (GDH Ortho). The design principle discovered from Nox Ortho engineering and modeling is facilely translated onto six different enzymes to create NMN(H)-orthogonal biocatalysts with a consistent ~103-106-fold cofactor specificity switch from NAD(P)+ to NMN+. We assemble these enzymes to produce stereo-pure 2,3-butanediol in cell-free systems and in Escherichia coli, enabled by NMN(H)'s distinct redox ratio firmly set by its designated driving forces, decoupled from both NAD(H) and NADP(H).

Protein stability prediction by fine-tuning a protein language model on a mega-scale dataset.

Protein stability plays a crucial role in a variety of applications, such as food processing, therapeutics, and the identification of pathogenic mutations. Engineering campaigns commonly seek to improve protein stability, and there is a strong interest in streamlining these processes to enable rapid optimization of highly stabilized proteins with fewer iterations. In this work, we explore utilizing a mega-scale dataset to develop a protein language model optimized for stability prediction. ESMtherm is trained on the folding stability of 528k natural and de novo sequences derived from 461 protein domains and can accommodate deletions, insertions, and multiple-point mutations. We show that a protein language model can be fine-tuned to predict folding stability. ESMtherm performs reasonably on small protein domains and generalizes to sequences distal from the training set. Lastly, we discuss our model's limitations compared to other state-of-the-art methods in generalizing to larger protein scaffolds. Our results highlight the need for large-scale stability measurements on a diverse dataset that mirrors the distribution of sequence lengths commonly observed in nature.

Engineering a nicotinamide mononucleotide redox cofactor system for biocatalysis.

Biological production of chemicals often requires the use of cellular cofactors, such as nicotinamide adenine dinucleotide phosphate (NADP+). These cofactors are expensive to use in vitro and difficult to control in vivo. We demonstrate the development of a noncanonical redox cofactor system based on nicotinamide mononucleotide (NMN+). The key enzyme in the system is a computationally designed glucose dehydrogenase with a 107-fold cofactor specificity switch toward NMN+ over NADP+ based on apparent enzymatic activity. We demonstrate that this system can be used to support diverse redox chemistries in vitro with high total turnover number (~39,000), to channel reducing power in Escherichia coli whole cells specifically from glucose to a pharmaceutical intermediate, levodione, and to sustain the high metabolic flux required for the central carbon metabolism to support growth. Overall, this work demonstrates efficient use of a noncanonical cofactor in biocatalysis and metabolic pathway design.

Assessing Alkene Reactivity toward Cytochrome P450-Mediated Epoxidation through Localized Descriptors and Regression Modeling.

The prediction of sites of epoxidation by cytochrome P450s during metabolism is particularly important in drug design, as epoxides are capable of alkylating biological macromolecules. Reliable methods are needed to quantitatively predict P450-mediated epoxidation barriers for inclusion in high-throughput screening campaigns alongside protein-ligand docking. Utilizing the fractional occupation number weighted density (FOD) and orbital-weighted Fukui index (fw+) as descriptors of local reactivity and a data set of 36 alkene epoxidation barriers computed with density functional theory (DFT), we developed and validated a multiple linear regression model for the reliable estimation of epoxidation barriers using only substrate structures as input. Using our recommended level of theory (GFN2-xTB//GFN-FF), mean absolute errors in the training and test sets were found to be 0.66 and 0.70 kcal/mol, respectively, with coefficients of determination of ca. 0.80. We demonstrate the utility of this approach on three known substrates of CYP101A1 and further show that this approach is inappropriate for particularly electron-rich alkenes. By employing a modern semiempirical method on force-field-generated geometries, the required descriptors can be calculated on the millisecond timescale per structure, making the approach well suited for incorporation into high-throughput methodologies alongside docking.

Discovery, Design, and Structural Characterization of Alkane-Producing Enzymes across the Ferritin-like Superfamily.

To complement established rational and evolutionary protein design approaches, significant efforts are being made to utilize computational modeling and the diversity of naturally occurring protein sequences. Here, we combine structural biology, genomic mining, and computational modeling to identify structural features critical to aldehyde deformylating oxygenases (ADOs), an enzyme family that has significant implications in synthetic biology and chemoenzymatic synthesis. Through these efforts, we discovered latent ADO-like function across the ferritin-like superfamily in various species of Bacteria and Archaea. We created a machine learning model that uses protein structural features to discriminate ADO-like activity. Computational enzyme design tools were then utilized to introduce ADO-like activity into the small subunit of Escherichia coli class I ribonucleotide reductase. The integrated approach of genomic mining, structural biology, molecular modeling, and machine learning has the potential to be utilized for rapid discovery and modulation of functions across enzyme families.

Crystal Structure and Mechanistic Molecular Modeling Studies of Mycobacterium tuberculosis Diterpene Cyclase Rv3377c.

Terpenes make up the largest class of natural products, with extensive chemical and structural diversity. Diterpenes, mostly isolated from plants and rarely prokaryotes, exhibit a variety of important biological activities and valuable applications, including providing antitumor and antibiotic pharmaceuticals. These natural products are constructed by terpene synthases, a class of enzymes that catalyze one of the most complex chemical reactions in biology: converting simple acyclic oligo-isoprenyl diphosphate substrates to complex polycyclic products via carbocation intermediates. Here we obtained the second ever crystal structure of a class II diterpene synthase from bacteria, tuberculosinol pyrophosphate synthase (i.e., Halimadienyl diphosphate synthase, MtHPS, or Rv3377c) from Mycobacterium tuberculosis (Mtb). This enzyme transforms (E,E,E)-geranylgeranyl diphosphate into tuberculosinol pyrophosphate (Halimadienyl diphosphate). Rv3377c is part of the Mtb diterpene pathway along with Rv3378c, which converts tuberculosinol pyrophosphate to 1-tuberculosinyl adenosine (1-TbAd). This pathway was shown to exist only in virulent Mycobacterium species, but not in closely related avirulent species, and was proposed to be involved in phagolysosome maturation arrest. To gain further insight into the reaction pathway and the mechanistically relevant enzyme substrate binding orientation, electronic structure calculation and docking studies of reaction intermediates were carried out. Results reveal a plausible binding mode of the substrate that can provide the information to guide future drug design and anti-infective therapies of this biosynthetic pathway.

Functional characterization and reclassification of an enzyme previously proposed to be a limonoid UDP-glucosyltransferase.

BACKGROUND: A major problem in the orange industry is 'delayed' bitterness, which is caused by limonin, a bitter compound developing from its non-bitter precursor limonoate A-ring lactone (LARL) during and after extraction of orange juice. The glucosidation of LARL by limonoid UDP-glucosyltransferase (LGT) to form non-bitter glycosyl-limonin during orange maturation has been demonstrated as a natural way to debitter by preventing the formation of limonin. RESULT: Here, the debittering potential of heterogeneously expressed glucosyltransferase, maltose-binding protein (MBP) fused to cuGT from Citrus unishiu Marc (MBP-cuGT), which was previously regarded as LGT, was evaluated. A liquid chromatography - mass spectrometry (LC-MS) method was established to determine the concentration of limonin and its derivatives. The protocols to obtain its potential substrates, LARL and limonoate (limonin with both A and D ring open), were also developed. Surprisingly, MBP-cuGT did not exhibit any detectable effect on limonin degradation when Navel orange juice was used as the substrate; MBP-cuGT was unable to biotransform either LARL or limonoate as purified substrates. However, it was found that MBP-cuGT displayed a broad activity spectrum towards flavonoids, confirming that the enzyme produced was active under the conditions evaluated in vitro. CONCLUSION: Our results based on LC-MS demonstrated that cuGT functionality was incorrectly identified. Its active substrates, including various flavonoids but not limonoids, highlight the need for further efforts to identify the enzyme responsible for LGT activity to develop biotechnology-based approaches for producing orange juice from varietals that traditionally have a delayed bitterness. © 2020 Society of Chemical Industry.

Toward Development of Fluorescence-Quenching-Based Biosensors for Drought Stress in Plants.

Abscisic acid (ABA) is a drought stress signaling molecule, and simple methods for detecting its levels could benefit agriculture. Here, we present proof-of-concept detection for ABA in aqueous solutions by the use of a mixture of Cyanine 5.5 (Cy5.5) fluorophore- and BHQ3 quencher-conjugated endogenous ABA receptor pyrabactin resistance 1 like proteins (PYL3). These dye-conjugated PYL3 protein form dimers in solutions without ABA and monomerize upon ABA binding. When they are in dimers, fluorescence of Cy5.5 is either nearly completely quenched by the BHQ3 or 20% quenched by another Cy5.5. Consequently, mixtures of equal amounts of the two protein conjugates were used to detect ABA in aqueous solution. As the ABA concentration increased from <1 µM to 1 mM, the intensity of fluorescence detected at around 680 nm from the mixture was more than doubled as a result of ABA-induced monomerization, which leads to halt of quenching and recovery of fluorescence of Cy5.5 in monomers. Kinetic modeling was used to simulate the fluorescence response from the mixture and the results generally agree with the experimentally observed trend. This work demonstrates that fluorescence measurements of a single dissociation reaction in one spectral region are adequate to assess the ABA concentration of a solution.

Molecular annotation of food - towards personalized diet and precision health.

BACKGROUND: Personalized diet requires matching human genotypic and phenotypic features to foods that increase the chance of achieving a desired physiological health outcome. New insights and technologies will help to decipher the intricacies of diet-health relationships and create opportunities for breakthroughs in dietary interventions for personal health management. SCOPE AND APPROACH: This article describes the scientific progress towards personalized diet and points out the need for integrating high-quality data on food. A framework for molecular annotation of food is presented, focusing on what aspects should be measured and how these measures relate to health. Strategies of applying trending technologies to improve personalized diet and health are discussed, highlighting challenges and opportunities for transforming data into insights and actions. KEY FINDINGS AND CONCLUSIONS: The goal of personalized diet is to enable individuals and caregivers to make informed dietary decisions for targeted health management. Achieving this goal requires a better understanding of how molecular properties of food influence individual eating behavior and health outcomes. Annotating food at a molecular level encompasses characterizing its chemical composition and modifications, physicochemical structure, and biological properties. Features of molecular properties in the food annotation framework are applicable to varied conditions and processes from raw materials to meals. Applications of trending technologies, such as omics techniques, wearable biosensors, and artificial intelligence, will support data collection, data analytics, and personalized dietary actions for targeted health management.

The Zinc Linchpin Motif in the DNA Repair Glycosylase MUTYH: Identifying the Zn2+ Ligands and Roles in Damage Recognition and Repair.

The DNA base excision repair (BER) glycosylase MUTYH prevents DNA mutations by catalyzing adenine (A) excision from inappropriately formed 8-oxoguanine (8-oxoG):A mismatches. The importance of this mutation suppression activity in tumor suppressor genes is underscored by the association of inherited variants of MUTYH with colorectal polyposis in a hereditary colorectal cancer syndrome known as MUTYH-associated polyposis, or MAP. Many of the MAP variants encompass amino acid changes that occur at positions surrounding the two-metal cofactor-binding sites of MUTYH. One of these cofactors, found in nearly all MUTYH orthologs, is a [4Fe-4S]2+ cluster coordinated by four Cys residues located in the N-terminal catalytic domain. We recently uncovered a second functionally relevant metal cofactor site present only in higher eukaryotic MUTYH orthologs: a Zn2+ ion coordinated by three Cys residues located within the extended interdomain connector (IDC) region of MUTYH that connects the N-terminal adenine excision and C-terminal 8-oxoG recognition domains. In this work, we identified a candidate for the fourth Zn2+ coordinating ligand using a combination of bioinformatics and computational modeling. In addition, using in vitro enzyme activity assays, fluorescence polarization DNA binding assays, circular dichroism spectroscopy, and cell-based rifampicin resistance assays, the functional impact of reduced Zn2+ chelation was evaluated. Taken together, these results illustrate the critical role that the "Zn2+ linchpin motif" plays in MUTYH repair activity by providing for proper engagement of the functional domains on the 8-oxoG:A mismatch required for base excision catalysis. The functional importance of the Zn2+ linchpin also suggests that adjacent MAP variants or exposure to environmental chemicals may compromise Zn2+ coordination, and ability of MUTYH to prevent disease.

Foldit Standalone: a video game-derived protein structure manipulation interface using Rosetta.

SUMMARY: Foldit Standalone is an interactive graphical interface to the Rosetta molecular modeling package. In contrast to most command-line or batch interactions with Rosetta, Foldit Standalone is designed to allow easy, real-time, direct manipulation of protein structures, while also giving access to the extensive power of Rosetta computations. Derived from the user interface of the scientific discovery game Foldit (itself based on Rosetta), Foldit Standalone has added more advanced features and removed the competitive game elements. Foldit Standalone was built from the ground up with a custom rendering and event engine, configurable visualizations and interactions driven by Rosetta. Foldit Standalone contains, among other features: electron density and contact map visualizations, multiple sequence alignment tools for template-based modeling, rigid body transformation controls, RosettaScripts support and an embedded Lua interpreter. AVAILABILITY AND IMPLEMENTATION: Foldit Standalone is available for download at https://fold.it/standalone , under the Rosetta license, which is free for academic and non-profit users. It is implemented in cross-platform C ++ and binary executables are available for Windows, macOS and Linux. CONTACT: scooper@ccs.neu.edu.

Combination of type II fatty acid biosynthesis enzymes and thiolases supports a functional ß-oxidation reversal.

An engineered reversal of the ß-oxidation cycle (r-BOX) and the fatty acid biosynthesis (FAB) pathway are promising biological platforms for advanced fuel and chemical production in part due to their iterative nature supporting the synthesis of various chain length products. While diverging in their carbon-carbon elongation reaction mechanism, iterative operation of each pathway relies on common chemical conversions (reduction, dehydration, and reduction) differing only in the attached moiety (acyl carrier protein (ACP) in FAB vs Coenzyme A in r-BOX). Given this similarity, we sought to determine whether FAB enzymes can be used in the context of r-BOX as a means of expanding available r-BOX components with a ubiquitous set of well characterized enzymes. Using enzymes from the type II FAB pathway (FabG, FabZ, and FabI) in conjunction with a thiolase catalyzing a non-decarboxylative condensation, we demonstrate that FAB enzymes support a functional r-BOX. Pathway operation with FAB enzymes was improved through computationally directed protein design to develop FabZ variants with amino acid substitutions designed to disrupt hydrogen bonding at the FabZ-ACP interface and introduce steric and electrostatic repulsion between the FabZ and ACP. FabZ with R126W and R121E substitutions resulted in improved carboxylic acid and alcohol production from one- and multiple-turn r-BOX compared to the wild-type enzyme. Furthermore, the ability for FAB enzymes to operate on functionalized intermediates was exploited to produce branched chain carboxylic acids through an r-BOX with functionalized priming. These results not only provide an expanded set of enzymes within the modular r-BOX pathway, but can also potentially expand the scope of products targeted through this pathway by operating with CoA intermediates containing various functional groups.

Computational protein design enables a novel one-carbon assimilation pathway.

We describe a computationally designed enzyme, formolase (FLS), which catalyzes the carboligation of three one-carbon formaldehyde molecules into one three-carbon dihydroxyacetone molecule. The existence of FLS enables the design of a new carbon fixation pathway, the formolase pathway, consisting of a small number of thermodynamically favorable chemical transformations that convert formate into a three-carbon sugar in central metabolism. The formolase pathway is predicted to use carbon more efficiently and with less backward flux than any naturally occurring one-carbon assimilation pathway. When supplemented with enzymes carrying out the other steps in the pathway, FLS converts formate into dihydroxyacetone phosphate and other central metabolites in vitro. These results demonstrate how modern protein engineering and design tools can facilitate the construction of a completely new biosynthetic pathway.

Impact of scaffold rigidity on the design and evolution of an artificial Diels-Alderase.

By combining targeted mutagenesis, computational refinement, and directed evolution, a modestly active, computationally designed Diels-Alderase was converted into the most proficient biocatalyst for [4+2] cycloadditions known. The high stereoselectivity and minimal product inhibition of the evolved enzyme enabled preparative scale synthesis of a single product diastereomer. X-ray crystallography of the enzyme-product complex shows that the molecular changes introduced over the course of optimization, including addition of a lid structure, gradually reshaped the pocket for more effective substrate preorganization and transition state stabilization. The good overall agreement between the experimental structure and the original design model with respect to the orientations of both the bound product and the catalytic side chains contrasts with other computationally designed enzymes. Because design accuracy appears to correlate with scaffold rigidity, improved control over backbone conformation will likely be the key to future efforts to design more efficient enzymes for diverse chemical reactions.

Engineering of Kuma030: A Gliadin Peptidase That Rapidly Degrades Immunogenic Gliadin Peptides in Gastric Conditions.

Celiac disease is characterized by intestinal inflammation triggered by gliadin, a component of dietary gluten. Oral administration of proteases that can rapidly degrade gliadin in the gastric compartment has been proposed as a treatment for celiac disease; however, no protease has been shown to specifically reduce the immunogenic gliadin content, in gastric conditions, to below the threshold shown to be toxic for celiac patients. Here, we used the Rosetta Molecular Modeling Suite to redesign the active site of the acid-active gliadin endopeptidase KumaMax. The resulting protease, Kuma030, specifically recognizes tripeptide sequences that are found throughout the immunogenic regions of gliadin, as well as in homologous proteins in barley and rye. Indeed, treatment of gliadin with Kuma030 eliminates the ability of gliadin to stimulate a T cell response. Kuma030 is capable of degrading >99% of the immunogenic gliadin fraction in laboratory-simulated gastric digestions within physiologically relevant time frames, to a level below the toxic threshold for celiac patients, suggesting great potential for this enzyme as an oral therapeutic for celiac disease.

Mechanistic Analysis of an Engineered Enzyme that Catalyzes the Formose Reaction.

An enzyme that catalyzes the formose reaction, termed "formolase", was recently engineered through a combination of computational protein design and directed evolution. We have investigated the kinetic role of the computationally designed residues and further characterized the enzyme's product profile. Kinetic studies illustrated that the computationally designed mutations were synergistic in their contributions towards enhancing activity. Mass spectrometry revealed that the engineered enzyme produces two products of the formose reaction-dihydroxyacetone and glycolaldehyde-with the product profile dependent on the formaldehyde concentration. We further explored the effects of this product profile on the thermodynamics and yield of the overall carbon assimilation from the formolase pathway to help guide future efforts to engineer this pathway.

Docking carbocations into terpene synthase active sites using chemically meaningful constraints-The TerDockin approach.

Terpenes are a diverse class of natural products which have long been sought after for their chemical properties as medicine, perfumes, and for food flavoring. Computational docking studies of terpene mechanisms have been a challenge due to the lack of strong directing groups which many docking programs rely on. In this chapter, we dive into our computational method Terdockin (Terpene-Docking) as a successful methodology in modeling terpene synthase mechanisms. This method could also be used as inspiration for any multi-ligand docking project.

Acid-active proteases to optimize dietary protein digestibility: a step towards sustainable nutrition.

Introduction: Historically, prioritizing abundant food production often resulted in overlooking nutrient quality and bioavailability, however, environmental concerns have now propelled sustainable nutrition and health efficacy to the forefront of global attention. In fact, increasing demand for protein is the major challenge facing the food system in the 21st century with an estimation that 70% more food is needed by 2050. This shift has spurred interest in plant-based proteins for their sustainability and health benefits, but most alternative sources of protein are poorly digestible. There are two approaches to solve digestibility: improve the digestibility of food proteins or improve the digestive capacity of consumers. Enhancing nutrient digestibility and bioavailability across diverse protein sources is crucial, with proteases presenting a promising avenue. Research, inspired by the proteases of human breast milk, has demonstrated that exogenous microbial proteases can activate within the human digestive tract and substantially increase the digestion of targeted proteins that are otherwise difficult to fully digest. Methods: Here, we introduce the use of an acid-active family of bacterial proteases (S53) to improve the digestibility and nutritional quality of a variety of protein sources, evaluated using the INFOGEST 2.0 protocol. Results: Results from in vitro digestibility indicate that the most effective protease in the S53 family substantially improves the digestibility of an array of animal and plant-derived proteins-soy, pea, chickpea, rice, casein, and whey. On average, this protease elevated protein digestibility by 115% during the gastric phase and by 15% in the intestinal phase, based on the degree of hydrolysis. Discussion: The widespread adoption of these proteases has the potential to enhance nutritional value and contribute to food security and sustainability. This approach would complement ongoing efforts to improve proteins in the food supply, increase the quality of more sustainable protein sources and aid in the nourishment of patients with clinically compromised, fragile intestines and individuals like older adults and high-performance athletes who have elevated protein needs.

Discovery of Potent Glycosidases Enables Quantification of Smoke-Derived Phenolic Glycosides through Enzymatic Hydrolysis.

When grapes are exposed to wildfire smoke, certain smoke-related volatile phenols (VPs) can be absorbed into the fruit, where they can be then converted into volatile-phenol (VP) glycosides through glycosylation. These volatile-phenol glycosides can be particularly problematic from a winemaking standpoint as they can be hydrolyzed, releasing volatile phenols, which can contribute to smoke-related off-flavors. Current methods for quantitating these volatile-phenol glycosides present several challenges, including the requirement of expensive capital equipment, limited accuracy due to the molecular complexity of the glycosides, and the utilization of harsh reagents. To address these challenges, we proposed an enzymatic hydrolysis method enabled by a tailored enzyme cocktail of novel glycosidases discovered through genome mining, and the generated VPs from VP glycosides can be quantitated by gas chromatography-mass spectrometry (GC-MS). The enzyme cocktails displayed high activities and a broad substrate scope when using commercially available VP glycosides as the substrates for testing. When evaluated in an industrially relevant matrix of Cabernet Sauvignon wine and grapes, this enzymatic cocktail consistently achieved a comparable efficacy of acid hydrolysis. The proposed method offers a simple, safe, and affordable option for smoke taint analysis.

Design to Data for mutants of B-glucosidase B from Paenibacillus polymyxa : V311D, F248N, Y166H, Y166K, M221K.

Engaging computational tools for protein design is gaining traction in the enzyme engineering community. However, current design and modeling algorithms have limited functionality predictive capacities for enzymes due to limitations of the dataset in terms of size and data quality. This study aims to expand training datasets for improved algorithm development with the addition of five rationally designed single-point enzyme variants. ß-glucosidase B variants were modeled in Foldit Standalone and then produced and assayed for thermal stability and kinetic parameters. Functional parameters: thermal stability (T M ) and Michaelis-Menten constants ( k cat , K M , and k cat /K M ) of five variants, V311D, Y166H, M221K, F248N, and Y166K, were added into the Design2Data database. As a case study, evaluation of this small mutant set finds mutational effect trends that both corroborate and contradict findings from larger studies examining the entire dataset.