Enzymatic Δ1-Dehydrogenation of 3-Ketosteroids—Reconciliation of Kinetic Isotope Effects with the Reaction Mechanism

Enzymatic synthesis of a skin active ingredient - glochidone by 3-ketosteroid dehydrogenase from Sterolibacterium denitrificans

In this study, we applied AcmB2, sourced from Sterolibacterium denitrificans, to catalyze the oxidative dehydrogenation of 3-ketolupeol (lupenone), a derivative of lupeol, triterpene obtained from birch bark. This enzymatic Δ1-dehydrogenation catalyzed by AcmB2 yielded glochidone, a bioactive compound frequently obtained from medicinal plants like Salvia trichoclada and Maytenus boria. Glochidone is known for its broad biological activities, including antibacterial, antifungal, anti-inflammatory, anticancer, antidiabetic as well as acetylcholinesterase inhibition. Our research demonstrates >99% conversion efficiency with 100% regioselectivity of the reaction. The effective conversion to glochidone employed an electron acceptor e.g., potassium hexacyanoferrate III, in mild, environmentally friendly conditions: 8-16% 2-hydroxypropyl-β-cyclodextrin, and 2-3% 2-methoxyethanol. AcmB2 reaction optimum was determined at pH 8.0 and 30 °C. Enzyme's biochemical attributes such as electron acceptor type, concentration and steroid substrate specificity were investigated. Among 4-, 5- and 6-ring steroid derivatives androst-4-en-3,17-dione and testosterone propionate were determined as the best substrates of AcmB2. Δ1-Dehydrogenation of substrates such as lupenone, diosgenone and 3-ketopetromyzonol was confirmed. We have assessed the antioxidant and rejuvenating characteristics of glochidone as an active component in formulations, considering its precursors, lupeol, and lupenone as well. Glochidone exhibited limited antioxidant and chelating capabilities compared to lupeol and reference compounds. However, it demonstrated robust rejuvenating properties, with a sirtuin induction level of 61.5 ± 1.87%, notably surpassing that of the reference substance, E-resveratrol (45.15 ± 0.09%). Additionally, glochidone displayed 26.5±0.67 and 19.41±0.76% inhibition of elastase and collagenase, respectively. The safety of all studied triterpenes was confirmed on skin reconstructed human Epidermis model. These findings provide valuable insights into the potential applications of glochidone in formulations aimed at addressing skin health concerns. This research presents the first example of an enzyme in the 3-ketosteroid dehydrogenase (KstD) family catalyzing the Δ1-dehydrogenation of a pentacyclic triterpene. We also explored structural differences between AcmB, AcmB2, and related KstDs pointing to G52 and P532 as potentially responsible for the unique substrate specificity of AcmB2. Our findings not only highlight the enzyme's capabilities but also present novel enzymatic pathways for bioactive compound synthesis.

Single-cell enzymatic cascade synthesis of testolactone enabled by engineering of polycyclic ketone monooxygenase and multi-gene expression fine-tuning

The synthesis of steroids is challenging through multistep steroidal core modifications with high site-selectivity and productivity. In this work, a novel enzymatic cascade system was constructed for synthesis of testolactone by specific C17 lactonization/Δ1-dehydrogenation from inexpensive androstenedione using an engineered polycyclic ketone monooxygenase (PockeMO) and an appropriate 3-ketosteroid-Δ1-dehydrogenase (ReKstD). The focused saturation mutagenesis in the substrate binding pocket was implemented for evolution of PockeMO to eliminate the bottleneck effect. A best mutant MU3 (I225L/L226V/L532Y) was obtained with 20-fold higher specific activity compared to PockeMO. The catalytic efficiency (kcat/Km) of MU3 was 171-fold higher and the substrate scope shifted to polycyclic ketones. Molecular dynamic simulations suggested that the activity was improved by stabilization of the pre-lactonization state and generation of productive orientation of 4-AD mediated by distal L532Y mutation. Based on that, the three genes, MU3, ReKstD and a ketoreductase for NADPH regeneration, were rationally integrated in one cell via expression fine-tuning to form the efficient single cell catalyst E. coli S9. The single whole-cell biocatalytic process was scaled up and could generate 9.0 g/L testolactone with the high space time yield of 1 g/L/h without steroidal by-product, indicating the potential for site-specific and one-pot synthesis of steroid.

Structure, Mutagenesis, and QM:MM Modeling of 3-Ketosteroid Δ1-Dehydrogenase from Sterolibacterium denitrificans─The Role of a New Putative Membrane-Associated Domain and Proton-Relay System in Catalysis

3-Ketosteroid Δ¹-dehydrogenases (KstD) are important microbial flavin enzymes that initiate the metabolism of steroid ring A and find application in the synthesis of steroid drugs. We present a structure of the KstD from Sterolibacterium denitrificans (AcmB), which contains a previously uncharacterized putative membrane-associated domain and extended proton-relay system. The experimental and theoretical studies show that the steroid Δ¹-dehydrogenation proceeds according to the Ping-Pong bi-bi kinetics and a two-step base-assisted elimination (E2cB) mechanism. The mechanism is validated by evaluating the experimental and theoretical kinetic isotope effect for deuterium-substituted substrates. The role of the active-site residues is quantitatively assessed by point mutations, experimental activity assays, and QM/MM MD modeling of the reductive half-reaction (RHR). The pre-steady-state kinetics also reveals that the low pH (6.5) optimum of AcmB is dictated by the oxidative half-reaction (OHR), while the RHR exhibits a slight optimum at the pH usual for the KstD family of 8.5. The modeling confirms the origin of the enantioselectivity of C2-H activation and substrate specificity for Δ⁴-3-ketosteroids. Finally, the cholest-4-en-3-one turns out to be the best substrate of AcmB in terms of ΔG of binding and predicted rate of dehydrogenation.

1,2-Hydrogenation and Transhydrogenation Catalyzed by 3-Ketosteroid Δ1-Dehydrogenase from Sterolibacterium denitrificans-Kinetics, Isotope Labelling and QM:MM Modelling Studies

Bacteria and fungi that are able to metabolize steroids express 3-ketosteroid-Δ¹-dehydrogenases (KstDs). KstDs such as AcmB form Sterolibacterium denitrificans Chol-1 catalyze the enantioselective 1α,2β-dehydrogenation of steroids to their desaturated analogues, e.g., the formation of 1,4-androstadiene-3,17-dione (ADD) from 4-androsten-3,17-dione (AD). The reaction catalyzed by KstD can be reversed if the appropriate electron donor, such as benzyl viologen radical cation, is present. Furthermore, KstDs can also catalyze transhydrogenation, which is the transfer of H atoms between 3-ketosteroids and 1-dehydrosteroids. In this paper, we showed that AcmB exhibits lower pH optima for hydrogenation and dehydrogenation by 3.5-4 pH units than those observed for KstD from Nocardia corallina. We confirmed the enantiospecificity of 1α,2β-hydrogenation and 1α,2β-transhydrogenation catalyzed by AcmB and showed that, under acidic pH conditions, deuterons are introduced not only at 2β but also at the 1α position. We observed a higher degree of H/D exchange at Y363, which activates the C2-H bond, compared to that at FAD, which is responsible for redox at the C1 position. Furthermore, for the first time, we observed the introduction of the third deuteron into the steroid core. This effect was explained through a combination of LC-MS experiments and QM:MM modelling, and we attribute it to a decrease in the enantioselectivity of C2-H activation upon the deuteration of the 2β position. The increase in the activation barrier resulting from isotopic substitution increases the chance of the formation of d³-substituted 3-ketosteroids. Finally, we demonstrate a method for the synthesis of 3-ketosteroids chirally deuterated at 1α,2β positions, obtaining 1α,2β-d²-4-androsten-3,17-dione with a 51% yield (8.61 mg).

Nonmetal Graphdiyne Nanozyme-Based Ferroptosis-Apoptosis Strategy for Colon Cancer Therapy

Ferroptosis-apoptosis, a new modality of induced cell death dependent on reactive oxygen species, has drawn tremendous attention in the field of nanomedicine. A metal-free ferroptosis-apoptosis inducer was reported based on boron and nitrogen codoped graphdiyne (BN-GDY) that possesses efficient glutathione (GSH) depletion capability and concurrently induces ferroptosis by deactivation of GSH-dependent peroxidases 4 (GPX4) and apoptosis by downregulation of Bcl2. The high catalytic activity of BN-GDY is explicated by both kinetic experiments and density functional theory (DFT) calculations of Gibbs free energy change during hydrogen peroxide (H₂O₂) decomposition. In addition, a unique sequence Bi-Bi mechanism is discovered, which is distinct from the commonly reported ping-pong Bi-Bi mechanism of most peroxidase mimics and natural enzymes. We anticipate that this nonmetal ferroptosis-apoptosis therapeutic concept by carbon-based nanomaterials would provide proof-of-concept evidence for nanocatalytic medicines in cancer therapy.

Model Setup and Procedures for Prediction of Enzyme Reaction Kinetics with QM-Only and QM:MM Approaches

The enzyme-catalyzed reactions are traditionally studied with experimental kinetic assays. The modern theoretical modeling techniques provide a complementary way to investigate these catalytic reactions. Experimental assay frequently does not allow an unequivocal answer to the factors controlling the reaction mechanism. On the other hand, the theoretical experiments provide a precise understanding of the molecular-level steps involved in catalytic reactions. However, modeling requires at least structural data on the enzyme and reactant, and the complexity of the enzyme systems can still be a challenge.In this chapter, we are going to describe how to apply theoretical modeling methods, such as MD simulation, QM-only cluster models of enzyme active site, or QM:MM multiscale modeling to study enzyme kinetics and even to predict kinetic isotope effect (KIE). We present a full protocol that starts from the PDB structure of the enzyme, through MD simulation of enzyme: substrate complex and statistical analysis of MD trajectory, selection of a model of the active site, and study of reaction pathways. We show how theoretical predictions basing on QM-only cluster models, QM:MM model, or multiple QM:MM models derived from QM:MM:MD simulations can be correlated with experimental kinetic results. Finally, we show how one can calculate intrinsic KIE associated with an individual molecular step.