Deorphanizing Human Cytochrome P450 Enzymes CYP4A22 and CYP4Z1 through Mechanistic in silico Modeling

Cytochrome P450 (CYP) enzymes are monooxygenases that catalyze the oxidation of structurally diverse substrates and are present in various lifeforms, including humans. Human CYPs catalyze the metabolism of xenobiotics including drugs and are involved in the essential biosynthesis of steroids, vitamins, and lipids. CYP-catalyzed metabolism and biosynthesis has been extensively studied recently, but several CYPs remain understudied despite their potential role in key biotransformation pathways. For these so-called ‘orphaned CYPs’, physiological function and structure are yet unknown, such as for CYP4A22 and 4Z1. CYP4A22 catalyzes the ω-hydroxylation of arachidonic acid to the angiogenic 20-hydroxyeicosatetraenoic acid. CYP4Z1 is overexpressed in breast cancer and other malignancies, which is correlated with tumor progression. Hence, CYP4Z1 is considered a promising breast cancer target that was not previously addressed by small molecule inhibitors. Here, we report our efforts to deorphanize CYP4A22 and 4Z1 together with our experimental partner Prof. Bureik. We were the first to predict the structure of CYP4A22 and 4Z1 by homology modeling and overcame the challenge of low-sequence similarity templates by incorporating substrate activities. We applied substrate docking and 3D pharmacophore modeling to rationalize how the binding site structure determines structure-activity relationships (SAR) trends. The well-known structural flexibility of CYPs was partially accounted for by molecular dynamics simulations. For the first time, enzyme-substrate interactions dynamics were analyzed with our novel dynamic pharmacophore approach, which led to the prediction of key residues. For CYP4A22, a residue influencing ω-hydroxylation (Phe320) and two binding residues (Arg96 and Arg233) were predicted. For CYP4Z1, the key role of Arg487 and assisting role of Asn381 for substrate binding were predicted, which was validated by in vitro mutational studies. The thereby validated CYP4Z1 model and substrate SAR were used in a virtual screening campaign resulting in a new potent and selective CYP4Z1 inhibitor (IC50: 63 ± 19 nM). Taken together, we established an in vitro/in silico deorphanization protocol that shed light on the structure-function relationships of CYP4A22 and 4Z1. This enabled us to discover a potent inhibitor of CYP4Z1 that will allow further studies on the physiological and pathophysiological role of the enzyme and might be further improved to target CYP4Z1 in a new therapeutical approach. Similar workflows could easily be applied to study other neglected enzymes in metabolism and other biotransformation pathways.Cytochrom P450 (CYP)-Enzyme sind Monooxygenasen, die die Oxidation strukturell diverser Substrate katalysieren und in verschiedenen Lebensformen, einschließlich des Menschen, vorkommen. Menschliche CYPs katalysieren den Metabolismus von Xenobiotika einschließlich Arzneistoffen und sind an der essenziellen Biosynthese von Steroiden, Vitaminen und Lipiden beteiligt. CYP-katalysierter Metabolismus und Biosynthese wurden in der Vergangenheit intensiv untersucht, aber einige CYPs sind trotz ihrer potenziellen Rolle in wichtigen Biotransformationswegen noch wenig erforscht. Für diese so genannten „orphaned“ oder „verwaisten“ CYPs, sind physiologische Funktion und Struktur noch unbekannt, wie z.B. CYP4A22 und 4Z1. CYP4A22 katalysiert die ω-Hydroxylierung von Arachidonsäure zu der angiogenen 20-Hydroxyeicosatetraensäure. CYP4Z1 wird bei Brustkrebs und anderen malignen Erkrankungen überexprimiert, was mit der Tumorprogression korreliert ist. Daher wird CYP4Z1 als ein vielversprechendes Brustkrebs-Target angesehen, das bisher nicht durch niedermolekulare Inhibitoren adressiert wurde. Hier berichten wir über unsere Bemühungen, CYP4A22 und 4Z1 zusammen mit unserem experimentellen Partner Prof. Bureik zu deorphanisieren. Wir waren die Ersten, die die Struktur von CYP4A22 und 4Z1 durch Homologiemodellierung vorhersagten und überwanden die Herausforderung der Templates mit geringer Sequenzähnlichkeit, indem wir Substrataktivitäten mit einbezogen. Wir wendeten Substrat-Docking und 3D-Pharmakophor-Modellierung an, um zu rationalisieren, wie die Struktur der Bindungstasche die Trends der Struktur-Aktivitäts-Beziehungen (SAR) bestimmt. Die bekannte strukturelle Flexibilität von CYPs wurde partiell durch Molekulardynamik-Simulationen berücksichtigt. Zum ersten Mal wurde die Dynamik der Enzym-Substrat-Interaktionen mit unserem neuartigen dynamischen Pharmakophor-Ansatz analysiert, was zur Vorhersage von wichtigen Aminosäuren führte. Für CYP4A22 wurde eine Aminosäure, die die ω-Hydroxylierung beeinflusst (Phe320) und zwei Bindungsaminosäuren (Arg96 und Arg233) vorhergesagt. Für CYP4Z1 wurde die Schlüsselrolle von Arg487 und die unterstützende Rolle von Asn381 für die Substratbindung vorhergesagt, welche durch in vitro Mutationsstudien validiert wurde. Das dadurch validierte CYP4Z1-Modell und die Substrat-SAR wurden in einer virtuellen Screening-Kampagne verwendet, die zu einen neuen potenten und selektiven CYP4Z1-Inhibitor führte (IC50: 63 ± 19 nM). Zusammengenommen haben wir ein in vitro/in silico Deorphanisierungsprotokoll etabliert, welches die Struktur-Funktionsbeziehungen von CYP4A22 und 4Z1 beleuchtet. Dies versetzte uns in die Lage einen potenten Inhibitor von CYP4Z1 zu entdecken, der weitere Studien über die physiologische und pathophysiologische Rolle des Enzyms ermöglichen wird und möglicherweise weiter verbessert werden kann, um CYP4Z1 in einem neuen therapeutischen Ansatz zu adressieren. Ähnliche Arbeitsabläufe könnte leicht angewendet werden, um andere vernachlässigte Enzyme im Metabolismus und anderen Biotransformationswegen zu untersuchen

Structural Dynamics of L1 and L2 β-lactamase

Stenotrophomonas maltophilia is a Gram-negative bacterium, found in several different environments, such as soil, water and hospital. It can cause multiple infections but also has strong resistance to many antibiotics such as cephalosporins, carbapenems, and aminoglycosides. S. maltophilia confers antibiotic resistance through expression of two different β-lactamases: L1-metallo-β-lactamase (L1 MBL) and L2 β-lactamase. L1 MBL is a class B3 β-lactamase and is the only known tetrameric β-lactamase known to humans. L2 is a class A β-lactamase which has been recently identified. In L1 MBL, there are, two loops (α3-β7 and β12-α5) known as the gating loops, that enclose the active site. The “open” and “close” conformations of these two loops were observed in the molecular dynamic simulation. These two conformations allow the gate loops have the ability of controlling the volume of the zinc binding pocket. The pocket size affects the substrate binding and further influence the catalytic activity of the whole protein. Therefore, gating loops are thought to have an important role in substrate binding and catalysis. In this thesis, the dynamics of the gating loops is explored through Markov state models. The “open” and “closed” confirmations are defined and three key interactions (salt bridge between R236 and D150c, the π–π stacking between H151 and Y227 and the orientation of P225) were identified that play an important role in controlling the conformation of the gating loops. Furthermore, as a tetramer, the correlation between the four subunits was also explored through CVAE-based deep learning and network analysis. The results revealed a ‘dimer of dimer’ dynamics in L1 MBL. The second part of the thesis focuses on exploring the dynamics of L2 β-lactamase family consisting of L2a, L2b, L2c and L2d enzymes. Homology modelling, MDLovofit, Markov state models, dynamic cross-correlation analysis and CVAE-based deep learning were employed for identifying potential key interactions and dynamic correlations between each subtype. Two dynamic combinations regions were revealed (α1 helix/N-terminal, β9-α15 loop, β7-β8 loop, hinge region, and C terminal, β1-β2 loop, β8-β9 loop) which exist in all four L2 β-lactamases. Stabilising these two combinations could possibly help inhibit the function of L2 β-lactamases. Besides, several potential key residues which result in high dynamic regions were also identified. Since very few research targeted on L2 β-lactamases, this work could be a starting point for the following-up work. The improved understanding of the dynamics of L1 and L2 β-lactamases will help in the design of their inhibitors and discovery of novel resistance breakers