Structure Of Enzyme Research Articles

Genomic evidence for the widespread presence of GH45 cellulases among soil invertebrates.

Lignocellulose is a major component of vascular plant biomass. Its decomposition is crucial for the terrestrial carbon cycle. Microorganisms are considered primary decomposers, but evidence increases that some invertebrates may also decompose lignocellulose. We investigated the taxonomic distribution and evolutionary origins of GH45 hydrolases, important enzymes for the decomposition of cellulose and hemicellulose, in a collection of soil invertebrate genomes. We found that these genes are common in springtails and oribatid mites. Phylogenetic analysis revealed that cellulase genes were acquired early in the evolutionary history of these groups. Domain architectures and predicted 3D enzyme structures indicate that these cellulases are functional. Patterns of presence and absence of these genes across different lineages prompt further investigation into their evolutionary and ecological benefits. The ubiquity of cellulase genes suggests that soil invertebrates may play a role in lignocellulose decomposition, independently or in synergy with microorganisms. Understanding the ecological and evolutionary implications might be crucial for understanding soil food webs and the carbon cycle.

Multivariate Silicification-Assisted Single Enzyme Structure Augmentation for Improved Enzymatic Activity-Stability Trade-Off.

The ability to finely tune/balance the structure and rigidity of enzymes to realize both high enzymatic activity and long-term stability is highly desired but highly challenging. In this work, we propose a new concept of silica-enzyme, referred to as "silicazyme", where solid inorganic silica was controlled hybridization with fragile enzyme under moderate condition at single-enzyme level, realizing simultaneous structure augmentation, long-term stability, and high enzymatic activity preservation. A multivariate silicification approach was utilized and occurred around individual enzymes to allow conformal coating. To realize a high activity-stability trade-off the structure flexibility/rigidity of silicazyme was optimized by a component-adjustment-ternary (CAT) plot method. Moreover, the multivariate organosilica frameworks bring great advantages including surface microenvironment adjustability, reversible modification capability, and functional extensibility through the rich chemistry of silica. Overall silicazymes represent a new class of enzymes that promise to broaden their utilization in catalysis, separations, and nanomedicine.

Optical Fiber Surface Plasmon Resonance Sensor for Glyceryl Tributyrate Detection Based on the PAA/CS Composite Hydrogel Embedding Protease Method.

Glycerol tributyrate as a low-density lipoprotein plays a crucial role in drug development and food safety. In this work, a novel high-stability fiber optic sensor for glyceryl tributyrate based on the poly(acrylic acid) (PAA) and chitosan (CS) composite hydrogel embedding method is first proposed. Compared with traditional functionalization, the lipase in a polymer network structure used in this article can not only avoid chemical reactions that cause damage to the enzyme structure but also avoid the instability of ionic bonds and physical adsorption. Therefore, the PAA/CS hydrogel method proposed in this article can effectively retain enzyme structure. First, the impact of different layers (one to five layers) of PAA/CS on pH sensing performance was explored, and it was determined that layers 1-3 could be used for subsequent sensing experiments. Within the linear detection range of 0.5-10 mM, the detection sensitivities of the one to three layers of the biosensor are divided into 0.65, 0.95, and 1.51 nm/mM, respectively, with the three layers having the best effect. When the number of coating layers is three, the detection limit of the sensor is 0.47 mM, meeting the millimole level detection standard for anticancer requirement. Furthermore, the stability and selectivity of the sensor (in the presence of hemoglobin, urea, cholesterol, acetylcholine, and glucose) were analyzed. The three-layer sensor is used for sample detection. At concentrations of 1-10 mM, the absolute value of the recovery percentage (%) is 82-99%, which can accurately detect samples. The sensor proposed in this paper has the advantages of low sample consumption, high sensitivity, simple structure, and label-free measurement. The enzyme-embedding method provides a new route for rapid and reliable glyceryl tributyrate detection, which has potential applications in food safety as well as the development of anticancer drugs.

Role of gamma radiation as an agent modulator of Mucor subtilissimus UCP1262 Fibrinolytic Enzyme (MsFE)

Thrombosis is a dangerous condition that can result in major damage. Fibrinolytic enzymes are significant therapeutic agents for thrombosis. This study focused on MsFE, a fibrinolytic protease from M. subtilissimus UCP1262, exploring its physicochemical traits and the impact of gamma radiation on its activity. Investigations included: fibrinogenolytic activity, effects of solvents and ions, gamma rays, enzyme shelf life, FTIR, CD, clotted times determination, and enzymatic kinetics. Notably, the major results obtained show the protease retained 90 % activity in organic solvents, FTIR indicated carbonyl functional groups and Circular dichroism spectroscopic studies indicated that the secondary structure (β-sheet) of enzyme remains mostly unaffected over pH 2.0–9.0, whereas considerable changes were observed in the tertiary structure. Kinetic analysis revealed altered parameters post-irradiation. Gamma radiation initially enhanced enzyme activity (10 kGy) but progressively decreased beyond 20 kGy. Metallic ions, especially magnesium, augmented irradiated enzyme activity. This study highlights gamma radiation's potential as a modulator for enhanced fibrinolytic activity, suggesting future biomedical applications.

Pulsed Electric Field Treatment of Oat and Barley Flour: Influence on Enzymes, Non-starch Polysaccharides, Dough Rheological Properties, and Application in Flat Bread

AbstractThis study examined the effects of pulsed electric field (PEF) treatment on enzymes, non-starch polysaccharides, and bread-making potential of oat and barley flour. Enzyme activity, microstructure, β-glucan extractability, molecular weight (Mw) and structure of non-starch polysaccharides, dough rheology, and flat bread properties were determined. An exponential decay model explained better the residual activity of oat β-glucanase across electric field intensity than barley β-glucanase. PEF treatment of flour at 12 kV/cm for 162 ms significantly reduced β-glucanase activity (40.2–76.5%) while increasing the concentration of total β-glucans (33.5%) and water-extractable arabinoxylans (36–41%). Mw of linear β-d-glucans decreased (9%) while Mw of branched arabinoxylans increased (6–33%). Scanning electron microscopy showed changes in microstructure of barley proteins. Blending wheat flour (70%) with oat or barley flour (30% weight) after PEF treatment enhanced gluten aggregation energy (29–19%) and breakdown viscosity (18–43%) of dough, as well as increased β-glucan content (21–32%) but reduced specific volume (11–24%). The findings of this study provide a comprehensive insight into the PEF’s potential for retarding enzymatic reactions and preserving integrity of cereal non-starch polysaccharides.

Comparative Analysis of Deep Generative Model for Industrial Enzyme Design

Abstract: Although enzymes have the advantage of efficient catalysis, natural enzymes lack stability in industrial environments and do not even meet the required catalytic reactions. This prompted us to urgently de novo design new enzymes. Computational design is a powerful tool, allowing rapid and efficient exploration of sequence space and facilitating the design of novel enzymes tailored to specific conditions and requirements. It is beneficial to de novo design industrial enzymes using computational methods. Currently, only one tool explicitly designed for the enzyme-only generation performs unsatisfactorily. We have selected several general protein sequence design tools and systematically evaluated their effectiveness when applied to specific industrial enzymes. We investigated the literature related to protein generation. We summarized the computational methods used for sequence generation into three categories: structure-conditional sequence generation, sequence generation without structural constraints, and co-generation of sequence and structure. To effectively evaluate the ability of six computational tools to generate enzyme sequences, we first constructed a luciferase dataset named Luc_64. Then we assessed the quality of enzyme sequences generated by these methods on this dataset, including amino acid distribution, EC number validation, etc. We also assessed sequences generated by structure-based methods on existing public datasets using sequence recovery rates and root-mean-square deviation (RMSD) from a sequence and structure perspective. In the functionality dataset, Luc_64, ABACUS-R, and ProteinMPNN stood out for producing sequences with amino acid distributions and functionalities closely matching those of naturally occurring luciferase enzymes, suggesting their effectiveness in preserving essential enzymatic characteristics. Across both benchmark datasets, ABACUS-R and ProteinMPNN, have also exhibited the highest sequence recovery rates, indicating their superior ability to generate sequences closely resembling the original enzyme structures. Our study provides a crucial reference for researchers selecting appropriate enzyme sequence design tools, highlighting the strengths and limitations of each tool in generating accurate and functional enzyme sequences. ProteinMPNN and ABACUS-R emerged as the most effective tools in our evaluation, offering high accuracy in sequence recovery and RMSD and maintaining the functional integrity of enzymes through accurate amino acid distribution. Meanwhile, the performance of protein general tools for migration to specific industrial enzymes was fairly evaluated on our specific industrial enzyme benchmark.

MODIFICATION OF HYALURONIDASE MICROENVIRONMENT: INNOVATORY APPROACHES FOR DEVELOPMENT OF BIOCATALYTIC MEDICAL PREPARATIONS

The computational study of 3D-model hyaluronidase interaction with shortchain glycosaminoglycan ligands had performed demonstrating the diversity and significance of their reaction on enzyme structure. The purpose of this review was evolution of limiting enzyme functioning interactions (impact on stability, biocatalyst activity) with grounding of recommendations for experimental modification of hyaluronidase for obtaining of its derivative of medicine destination (according the results of theoretical researches). The analysis was performed on databases of PubMed, Web of Science, MedLine, E-library in frames last 15 years. The binding of chondroitin trimers (on centers cn6, cn3, cn1) to hyaluronidase molecular surface increased the enzyme stability, binding of chondroitin sulfate trimers (on centers cs2, cs4, cs7, cs8 or cs1, cs2, cs4, cs7, cs8) decreased the inhibition of enzyme by tetramer heparin. It should be noted the importance of ligand binding for regulation of enzyme functioning and existence of multiform and multicomponent microenvironment of enzyme. The sequence of preferable coupling of ligands with hyaluronidase is elicited in our study and with its help was evaluate reality of experimental selective modification of enzyme (possibly noncovalent or covalently, for instance, with chondroitin sulfate trimers on centers cs7, cs1, cs5) for experimental obtaining of stabilized enzyme forms. The perspective approaches for this aim may be the noncovalent reaction on hyaluronidase by chondroitin or chondroitin sulfate trimers as well covalent modification of biocatalyst by chondroitin sulfate trimers.

Isoliquiritigenin retards starch digestion by increasing resistant starch content and inhibiting the activities of α-amylase and α-glucosidase

The inhibition mechanism of starch digestion by a natural plant active ingredient isoliquiritigenin was studied. The results indicated that isoliquiritigenin effectively decreased the starch hydrolysis through increasing the content of resistant starch, and inhibiting the activities of α-amylase and α-glucosidase. The content of resistant starch increased by 18.85% with the addition of isoliquiritigenin at 8% content. Multispectral analyses showed isoliquiritigenin combined with α-amylase or α-glucosidase to form stable complexes by non-covalent bonds, leading to the enzyme's structure to be loose, which was supported by the results of unstable conformations and an increase in the freedom of amino acid residues of the enzymes in molecular dynamics simulation. Molecular docking demonstrated that isoliquiritigenin bound to the amino acid residues 304–310 nearby the active pocket of α-amylase, and inserted the active site of α-glucosidase competing with the substrate to bind the crucial amino acid residues (Asp215, Asp352 and Glu411), thereby inhibiting α-amylase and α-glucosidase activity. These findings highlight the development potential of isoliquiritigenin as a hypoglycaemic dietary supplement.

Biochemical, structural, and computational analyses of two new clinically identified missense mutations of ALDH7A1

Aldehyde dehydrogenase 7A1 (ALDH7A1) catalyzes a step of lysine catabolism. Certain missense mutations in the ALDH7A1 gene cause pyridoxine dependent epilepsy (PDE), a rare autosomal neurometabolic disorder with recessive inheritance that affects almost 1:65000 live births and is classically characterized by recurrent seizures from the neonatal period. We report a biochemical, structural, and computational study of two novel ALDH7A1 missense mutations that were identified in a child with rare recurrent seizures from the third month of life. The mutations affect two residues in the oligomer interfaces of ALDH7A1, Arg134 and Arg441 (Arg162 and Arg469 in the HGVS nomenclature). The corresponding enzyme variants R134S and R441C (p.Arg162Ser and p.Arg469Cys in the HGVS nomenclature) were expressed in Escherichia coli and purified. R134S and R441C have 10,000- and 50-fold lower catalytic efficiency than wild-type ALDH7A1, respectively. Sedimentation velocity analytical ultracentrifugation shows that R134S is defective in tetramerization, remaining locked in a dimeric state even in the presence of the tetramer-inducing coenzyme NAD+. Because the tetramer is the active form of ALDH7A1, the defect in oligomerization explains the very low catalytic activity of R134S. In contrast, R441C exhibits wild-type oligomerization behavior, and the 2.0 Å resolution crystal structure of R441C complexed with NAD+ revealed no obvious structural perturbations when compared to the wild-type enzyme structure. Molecular dynamics simulations suggest that the mutation of Arg441 to Cys may increase intersubunit ion pairs and alter the dynamics of the active site gate. Our biochemical, structural, and computational data on two novel clinical variants of ALDH7A1 add to the complexity of the molecular determinants underlying pyridoxine dependent epilepsy.

Emergence of catalytic function in prebiotic information-coding polymers

Life as we know it relies on the interplay between catalytic activity and information processing carried out by biological polymers. Here we present a plausible pathway by which a pool of prebiotic information-coding oligomers could acquire an early catalytic function, namely sequence-specific cleavage activity. Starting with a system capable of non-enzymatic templated replication, we demonstrate that even non-catalyzed spontaneous cleavage would promote proliferation by generating short fragments that act as primers. Furthermore, we show that catalytic cleavage function can naturally emerge and proliferate in this system. Specifically, a cooperative catalytic network with four subpopulations of oligomers is selected by the evolution in competition with chains lacking catalytic activity. The cooperative system emerges through the functional differentiation of oligomers into catalysts and their substrates. The model is inspired by the structure of the hammerhead RNA enzyme as well as other DNA- and RNA-based enzymes with cleavage activity that readily emerge through natural or artificial selection. We identify the conditions necessary for the emergence of the cooperative catalytic network. In particular, we show that it requires the catalytic rate enhancement over the spontaneous cleavage rate to be at least 102–103, a factor consistent with the existing experiments. The evolutionary pressure leads to a further increase in catalytic efficiency. The presented mechanism provides an escape route from a relatively simple pairwise replication of oligomers toward a more complex behavior involving catalytic function. This provides a bridge between the information-first origin of life scenarios and the paradigm of autocatalytic sets and hypercycles, albeit based on cleavage rather than synthesis of reactants.

Recent progress of atmospheric and room-temperature plasma as a new and promising mutagenesis technology.

At present, atmospheric and room-temperature plasma (ARTP) is regarded as a new and powerful mutagenesis technology with the advantages of environment-friendliness, operation under mild conditions, and fast mutagenesis speed. Compared with traditional mutagenesis strategies, ARTP is used mainly to change the structure of microbial DNA, enzymes, and proteins through a series of physical, chemical, and electromagnetic effects with the organisms, leading to nucleotide breakage, conversion or inversion, causing various DNA damages, so as to screen out the microbial mutants with better biological characteristics. As a result, in recent years, ARTP mutagenesis and the combination of ARTP with traditional mutagenesis have been widely used in microbiology, showing great potential for application. In this review, the recent progress of ARTP mutagenesis in different application fields and bottlenecks of this technology are systematically summarized, with a view to providing a theoretical basis and technical support for better application. Finally, the outlook of ARTP mutagenesis is presented, and we identify the challenges in the field of microbial mutagenesis by ARTP.

Emergence of catalytic function in prebiotic information-coding polymers.

Life as we know it relies on the interplay between catalytic activity and information processing carried out by biological polymers. Here we present a plausible pathway by which a pool of prebiotic information-coding oligomers could acquire an early catalytic function, namely sequence-specific cleavage activity. Starting with a system capable of non-enzymatic templated replication, we demonstrate that even non-catalyzed spontaneous cleavage would promote proliferation by generating short fragments that act as primers. Furthermore, we show that catalytic cleavage function can naturally emerge and proliferate in this system. Specifically, a cooperative catalytic network with four subpopulations of oligomers is selected by the evolution in competition with chains lacking catalytic activity. The cooperative system emerges through the functional differentiation of oligomers into catalysts and their substrates. The model is inspired by the structure of the hammerhead RNA enzyme as well as other DNA- and RNA-based enzymes with cleavage activity that readily emerge through natural or artificial selection. We identify the conditions necessary for the emergence of the cooperative catalytic network. In particular, we show that it requires the catalytic rate enhancement over the spontaneous cleavage rate to be at least 102-103, a factor consistent with the existing experiments. The evolutionary pressure leads to a further increase in catalytic efficiency. The presented mechanism provides an escape route from a relatively simple pairwise replication of oligomers toward a more complex behavior involving catalytic function. This provides a bridge between the information-first origin of life scenarios and the paradigm of autocatalytic sets and hypercycles, albeit based on cleavage rather than synthesis of reactants.

Predicting the Structure of Enzymes with Metal Cofactors: The Example of [FeFe] Hydrogenases.

The advent of deep learning algorithms for protein folding opened a new era in the ability of predicting and optimizing the function of proteins once the sequence is known. The task is more intricate when cofactors like metal ions or small ligands are essential to functioning. In this case, the combined use of traditional simulation methods based on interatomic force fields and deep learning predictions is mandatory. We use the example of [FeFe] hydrogenases, enzymes of unicellular algae promising for biotechnology applications to illustrate this situation. [FeFe] hydrogenase is an iron-sulfur protein that catalyzes the chemical reduction of protons dissolved in liquid water into molecular hydrogen as a gas. Hydrogen production efficiency and cell sensitivity to dioxygen are important parameters to optimize the industrial applications of biological hydrogen production. Both parameters are related to the organization of iron-sulfur clusters within protein domains. In this work, we propose possible three-dimensional structures of Chlorella vulgaris 211/11P [FeFe] hydrogenase, the sequence of which was extracted from the recently published genome of the given strain. Initial structural models are built using: (i) the deep learning algorithm AlphaFold; (ii) the homology modeling server SwissModel; (iii) a manual construction based on the best known bacterial crystal structure. Missing iron-sulfur clusters are included and microsecond-long molecular dynamics of initial structures embedded into the water solution environment were performed. Multiple-walkers metadynamics was also used to enhance the sampling of structures encompassing both functional and non-functional organizations of iron-sulfur clusters. The resulting structural model provided by deep learning is consistent with functional [FeFe] hydrogenase characterized by peculiar interactions between cofactors and the protein matrix.

An Artificial Enzyme: How Nanoconfinement Allows the Selective Electrochemical Detection of Glucose Directly in Whole Blood

AbstractNanoparticles that catalyze biochemically relevant reactions are promoted as alternative enzymes. The application of such artificial enzymes is severely restricted by poor selectivity in biological fluids; mainly because the reactions occur at active sites on the exterior surface of the nanoparticle. Enzymes in contrast typically have their active sites down a nanoconfined substrate channel where the reaction occurs in different solution conditions to bulk solution which aids in achieving selectivity for the substrate. Herein the same 3D structure of enzymes is mimicked in nanoparticles to allow selective reactions in biological fluids. This is achieved using a gold nanoparticle coated in a conducting mesoporous carbon shell where isolated nanochannels lead to the gold surface. It can detect glucose in whole blood with no interference from other species. This is achieved by electrochemically pulsing the artificial enzymes to generate the locally required alkalinity for an effective electrocatalytic reaction in the nanochannels, as well as expelling fouling agents that will otherwise passivate the electrocatalytic reaction. The artificial enzymes are shown to be capable of detecting glucose in biological fluids, without loss of signal, for several months. This study shows how nanoconfinement in nanoparticles can be exploited to potentially allow a broad range of species to be selectively detected in biological fluids with stability that can exceed that of enzymes.

Investigation of the potential mechanisms of α-amylase and glucoamylase through ultrasound intensification

The aim of this study is to enhance the efficiency of enzymes, reduce operational costs, and increase production output. Experimental research shows that ultrasound positively impacted the activity of α-amylase and glucoamylase, with the peak α-amylase activity observed at 30 W for 5 min and the highest glucoamylase activity at 60 W for 3 min. Ultrasonication extended the optimal temperature of both enzymes, but had no effect on the optimal pH. According to the kinetic experiments, ultrasonic treatment could improve the catalytic efficiency of α-amylase and glucoamylase. Furthermore, the SDS-PAGE results revealed that ultrasound treatment did not alter the molecular weights of the enzymes and their primary structures; The circular dichroism and fluorescence spectroscopy analysis indicated the secondary structural components, especially the α-sheet and the tryptophan fluorescence intensity, were notably affected by ultrasound. The changes in the secondary and tertiary structure of α-amylase and glucoamylase suggest that ultrasonic treatment may enhance their activities. Our findings provide a theoretical basis for the efficient utilization of α-amylase and glucoamylase through understanding the enzyme structure changes after ultrasound.

Exploring the Antarctic aminopeptidase P from Pseudomonas sp. strain AMS3 through structural analysis and molecular dynamics simulation

Aminopeptidase P (APPro) is a crucial metalloaminopeptidase involved in amino acid cleavage from peptide N-termini, playing essential roles as versatile biocatalysts with applications ranging from pharmaceuticals to industrial processes. Despite acknowledging its potential for catalysis in lower temperatures, detailed molecular basis and biotechnological implications in cold environments are yet to be explored. Therefore, this research aims to investigate the molecular mechanisms underlying the cold-adapted characteristics of APPro from Pseudomonas sp. strain AMS3 (AMS3-APPro) through a detailed analysis of its structure and dynamics. In this study, structure analysis and molecular dynamics (MD) simulation of a predicted model of AMS3-APPro has been performed at different temperatures to assess structural flexibility and thermostability across a temperature range of 0–60 °C over 100 ns. The MD simulation results revealed that the structure were able to remain stable at low temperatures. Increased temperatures present a potential threat to the overall stability of AMS3-APPro by disrupting the intricate hydrogen bond networks crucial for maintaining structural integrity, thereby increasing the likelihood of protein unfolding. While the metal binding site at the catalytic core exhibits resilience at higher temperatures, highlighting its local structural integrity, the overall enzyme structure undergoes fluctuations and potential denaturation. This extensive structural instability surpasses the localized stability observed at the metal binding site. Consequently, these assessments offer in-depth understanding of the cold-adapted characteristics of AMS3-APPro, highlighting its capability to uphold its native conformation and stability in low-temperature environments. In summary, this research provides valuable insights into the cold-adapted features of AMS3-APPro, suggesting its efficient operation in low thermal conditions, particularly relevant for potential biotechnological applications in cold environments. Communicated by Ramaswamy H. Sarma

The effect of buffer pH on enzyme activity

This study investigates the effect of pH on enzyme-catalyzed activity, with an emphasis on the involvement of wheat germ acid phosphatase in dephosphorylation processes. Temperature, pH, and enzyme concentration all have a substantial impact on enzyme activity and substrate interaction. Wheat germ acid phosphatase was chosen for this work. The activity of the enzyme in dephosphorylating p-nitrophenyl phosphate (p-NPP) into p-nitrophenol (p-NP) was evaluated using a stopped assay approach. The reaction was stopped by introducing sodium hydroxide, which ionises p-NP and produces a yellow anion visible at 405 nm. The experiment measured product production in nmol per minute and included three sections: Created a standard for the amount of p-NP with its absorbance at 405 nm; Found the ideal incubation period for maximal product generation by wheat germ acid phosphatase; Evaluated the effect of pH on enzyme activity measuring the first reaction velocity in various pH settings. The results showed that when the buffer pH diverged from the ideal value of 5.5, catalysis rates reduced dramatically, implying that high pH levels may modify the protein structure of the enzyme and reduce its catalytic effectiveness. This work emphasises the importance of pH in enzymatic activity and its potential impacts on enzyme structural integrity.

Overview of Synthesis and Applications of Unnatural Lipophilic α-Amino Acids

Abstract: Naturally and synthetically obtained lipophilic α-amino acids exhibit diverse properties and applications in academia and industry. Unnatural hydrophobic/lipophilic amino acids lacking polarity in their side chains manifest the biologically significant structure of peptides and proteins. The hydrophobic effect of lipophilic amino acids stabilizes the structure of proteins, peptides, and enzymes during their indigenous folding-unfolding phenomena. The presence of these amino acids in the backbone of protein and peptide-derived drug delivery systems such as lysine-derived surfactants and glycodendrimers can also enhance the cell penetration of drugs of interest. Cationic poly-l-lysine dendrimers, α-amino oleic acid, and a naturally occurring cyclic heptadepsipeptide HUN7293 are recognized as promising biomaterials for developing prodrugs and also serve as biocompatible surfactants in the food and pharmaceutical industries. The synthesis of unnatural lipophilic amino acids, N-lauroyl sarcosine, N-lauroyl glutamic acid, N-octylglycine, N-myristoyl glycine etc. has gained attention for preparing novel compounds for advanced academic, industrial, and societal applications. This review article discusses the applications and synthesis of hydrophobic/lipophilic α-amino acids using ester enolate Claisen rearrangement, chiral auxiliary, chiral pool, chiral catalysts, and many more relevant methodologies.

Crystal structures of the fatty acid biosynthesis initiation enzymes in Bacillus subtilis

Bacteria use the fatty acid composition of membrane lipids to maintain homeostasis of the bilayer. β-Ketoacyl-ACP synthase III (FabH) initiates fatty acid biosynthesis and is the primary determinant of the fatty acid composition. FabH condenses malonyl-acyl carrier protein with an acyl-Coenzyme A primer to form β -ketoacyl-acyl carrier protein which is used to make substrates for lipid synthesis. The acyl-Coenzyme A primer determines whether an acyl chain in the membrane has iso, anteiso, or no branching (straight chain) and biophysical properties of the membrane. The soil bacterium Bacillus subtilis encodes two copies of FabH (BsFabHA and BsFabHB), and here we solve their crystal structures. The substrate-free 1.85 Å and 2.40 Å structures of BsFabHA and BsFabHB show both enzymes have similar residues that line the active site but differ in the architecture surrounding the catalytic residues and oxyanion hole. Branching in the BsFabHB active site may better accommodate the structure of an anteiso branched acyl-Coenzyme A molecule and thus confer superior utilization to BsFabHA for this primer type. The 2.02 Å structure of BsFabHA•Coenzyme A shows how the active site architecture changes after binding the first substrate. The other notable difference is an amino acid insertion in BsFabHB that extends a cap that covers the dimer interface. The cap topology is diverse across FabH structures and appears to be a distinguishing feature. FabH enzymes have variable sensitivity to natural product inhibitors and the availability of crystal structures help clarify how nature designs antimicrobials that differentially target FabH homologs.

Abstract 1268 The influence of surface residues on the structure and activity of a salt-dependent halophile enzyme

Abstract 1268 The influence of surface residues on the structure and activity of a salt-dependent halophile enzyme