Molecular modeling on inhibitor complexes and active-site dynamics of cytochrome P450 C17, a target for prostate cancer therapy

Non-steroidal CYP17A1 Inhibitors: Discovery and Assessment

CYP17A1 is an enzyme that plays a major role in steroidogenesis and is critically involved in the biosynthesis of steroid hormones. Therefore, it remains an attractive target in several serious hormone-dependent cancer diseases, such as prostate cancer and breast cancer. The medicinal chemistry community has been committed to the discovery and development of CYP17A1 inhibitors for many years, particularly for the treatment of castration-resistant prostate cancer. The current Perspective reflects upon the discovery and evaluation of non-steroidal CYP17A1 inhibitors from a medicinal chemistry angle. Emphasis is placed on the structural aspects of the target, key learnings from the presented chemotypes, and design guidelines for future inhibitors.

Key regulators in the architecture of substrate access/egress channels in mammalian cytochromes P450 governing flexibility in substrate oxyfunctionalization

Cytochrome P450s (CYP) represent a superfamily of b-type hemoproteins catalyzing oxifunctionalization of a vast array of endogenous and exogenous compounds. The present review focuses on assessment of the topology of prospective determinants in substrate entry and product release channels of mammalian P450s, steering the conformational dynamics of substrate accessibility and productive ligand orientation toward the iron-oxene core. Based on a generalized, CYP3A4-related construct, the sum of critical elements from diverse target enzymes was found to cluster within the known substrate recognition sites. The majority of prevalent substrate access/egress tunnels revealed to be of fairly balanced functional importance. The hydrophobicity profile of the candidates revealed to be the most salient feature in functional interaction throughout the conduits, while bulkiness of the residues imposes steric restrictions on substrate traveling. Thus, small amino acids such as prolines and glycines serve as hinges, driving conformational flexibility in ligand passage. Similarly, bottlenecks in the tunnel architecture, being narrowest encounter points within the CYP3A4 model, have a vital function in substrate selectivity along with clusters of aromatic amino acids acting as gatekeepers. In addition, peripheral patches in conduits may house determinants modulating allosteric cooperativity between remote and central domains in the P450 structure. Remarkably, the bulk critical residues lining tunnels in the various isozymes reside in helices B'/C and F/G inclusive of their interhelical turns as well as in helix I. This suggests these regions to represent hotspots for targeted genetic engineering to tailor more sophisticated mammalian P450s exploitable in industrial, biotechnological and medicinal areas.

Steroidogenic cytochrome P450 17A1 structure and function

Cytochrome P450 17A1 (CYP17A1) is a critical steroidogenic enzyme, essential for producing glucocorticoids and sex hormones. This review discusses the complex activity of CYP17A1, looking at its role in both the classical and backdoor steroidogenic pathways and the complex chemistry it carries out to perform both a hydroxylation reaction and a carbon-carbon cleavage, or lyase reaction. Functional and structural investigations have informed our knowledge of these two reactions. This review focuses on a few specific aspects of this discussion: the identities of reaction intermediates, the coordination of hydroxylation and lyase reactions, the effects of cytochrome b5, and conformational selection. These discussions improve understanding of CYP17A1 in a physiological setting, where CYP17A1 is implicated in a variety of steroidogenic diseases. This information can be used to improve ways in which CYP17A1 can be effectively modulated to treat diseases such as prostate and breast cancer, Cushing's syndrome, and glioblastoma.

The effect of drug loading on the properties of abiraterone-hydroxypropyl beta cyclodextrin solid dispersions processed by solvent free KinetiSol® technology

Abiraterone is a poorly water-soluble drug used in the treatment of prostate cancer. In our previous study, we reported that KinetiSol® processed solid dispersions (KSDs) based on hydroxypropyl β-cyclodextrin (HPBCD) showed improved dissolution and pharmacokinetics of abiraterone. However, the nature of abiraterone-HPBCD interaction within the KSDs or the effect of drug loading on the physicochemical properties and in vivo performance of HPBCD-based KSDs remain largely unknown. We hypothesize that KinetiSol technology can prepare abiraterone-HPBCD complexes within KSDs and that increasing the drug loading beyond an optimal point reduces the in vitro and in vivo performance of these KSDs. To confirm our hypothesis, we developed KSDs with 10-50% w/w drug loading and analyzed them using X-ray diffractometry and modulated differential scanning calorimetry. We found that KSDs containing 10-30% drug were amorphous. Interestingly, two-dimensional solid-state nuclear magnetic resonance and Raman spectroscopy indicated that the abiraterone-HPBCD complexes were formed. At elevated temperatures, the 10% and 20% drug-loaded KSDs were physically stable, while the 30% drug-loaded KSD showed recrystallization of abiraterone. In vitro dissolution and in vivo pharmacokinetic performances improved as the drug loading decreased; we attribute this to increased noncovalent interactions between abiraterone and HPBCD at lower drug loadings. Overall, the 10% drug loaded KSD showed a dissolution enhancement of 15.7-fold compared to crystalline abiraterone, and bioavailability enhancement of 3.9-fold compared to the commercial abiraterone acetate tablet Zytiga®. This study is first to confirm that KinetiSol, a high-energy, solvent-free technology, is capable of forming abiraterone-HPBCD complexes. Furthermore, in terms of in vitro and in vivo performance, a 10% drug load is optimal.

Comparative Dynamics and Functional Mechanisms of the CYP17A1 Tunnels Regulated by Ligand Binding

As an important member of cytochrome P450 (CYP) enzymes, CYP17A1 is a dual-function monooxygenase with a critical role in the synthesis of many human steroid hormones, making it an attractive therapeutic target. The emerging structural information about CYP17A1 and the growing number of inhibitors for these enzymes call for a systematic strategy to delineate and classify mechanisms of ligand transport through tunnels that control catalytic activity. In this work, we applied an integrated computational strategy to different CYP17A1 systems with a panel of ligands to systematically study at the atomic level the mechanism of ligand-binding and tunneling dynamics. Atomistic simulations and binding free energy computations identify the dynamics of dominant tunnels and characterize energetic properties of critical residues responsible for ligand binding. The common transporting pathways including S, 3, and 2c tunnels were identified in CYP17A1 binding systems, while the 2c tunnel is a newly formed pathway upon ligand binding. We employed and integrated several computational approaches including the analysis of functional motions and sequence conservation, atomistic modeling of dynamic residue interaction networks, and perturbation response scanning analysis to dissect ligand tunneling mechanisms. The results revealed the hinge-binding and sliding motions as main functional modes of the tunnel dynamic, and a group of mediating residues as key regulators of tunnel conformational dynamics and allosteric communications. We have also examined and quantified the mutational effects on the tunnel composition, conformational dynamics, and long-range allosteric behavior. The results of this investigation are fully consistent with the experimental data, providing novel rationale to the experiments and offering valuable insights into the relationships between the structure and function of the channel networks and a robust atomistic model of activation mechanisms and allosteric interactions in CYP enzymes.

Prospective computational design and in vitro bio-analytical tests of new chemical entities as potential selective CYP17A1 lyase inhibitors

The development and advancement of prostate cancer (PCa) into stage 4, where it metastasize, is a major problem mostly in elder males. The growth of PCa cells is stirred up by androgens and androgen receptor (AR). Therefore, therapeutic strategies such as blocking androgens synthesis and inhibiting AR binding have been explored in recent years. However, recently approved drugs (or in clinical phase) failed in improving the expected survival rates for this metastatic-castration resistant prostate cancer (mCRPC) patients. The selective CYP17A1 inhibition of 17,20-lyase route has emerged as a novel strategy. Such inhibition blocks the production of androgens everywhere they are found in the body. In this work, a three dimensional-quantitative structure activity relationship (3D-QSAR) pharmacophore model is developed on a diverse set of non-steroidal inhibitors of CYP17A1 enzyme. Highly active compounds are selected to define a six-point pharmacophore hypothesis with a unique geometrical arrangement fitting the following description: two hydrogen bond acceptors (A), two hydrogen bond donors (D) and two aromatic rings (R). The QSAR model showed adequate predictive statistics. The 3D-QSAR model is further used for database virtual screening of potential inhibitory hit structures. Density functional theory (DFT) optimization provides the electronic properties explaining the reactivity of the hits. Docking simulations discovers hydrogen bonding and hydrophobic interactions as responsible for the binding affinities of hits to the CYP17A1 Protein Data Bank structure. 13 hits from the database search (including five derivatives) are then synthesized in the laboratory as different scaffolds. Ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) in vitro experiments reveals three new chemical entities (NCEs) with half maximal inhibitory concentration (IC₅₀) values against the lyase route at mid-micromolar range with favorable selectivity to the lyase over the hydroxylase route (one of them with null hydroxylase inhibition). Thus, prospective computational design has enabled the design of potential lead lyase-selective inhibitors for further studies.

Structures of human steroidogenic cytochrome P450 17A1 with substrates

The human cytochrome P450 17A1 (CYP17A1) enzyme operates at a key juncture of human steroidogenesis, controlling the levels of mineralocorticoids influencing blood pressure, glucocorticoids involved in immune and stress responses, and androgens and estrogens involved in development and homeostasis of reproductive tissues. Understanding CYP17A1 multifunctional biochemistry is thus integral to treating prostate and breast cancer, subfertility, blood pressure, and other diseases. CYP17A1 structures with all four physiologically relevant steroid substrates suggest answers to four fundamental aspects of CYP17A1 function. First, all substrates bind in a similar overall orientation, rising ∼60° with respect to the heme. Second, both hydroxylase substrates pregnenolone and progesterone hydrogen bond to Asn(202) in orientations consistent with production of 17α-hydroxy major metabolites, but functional and structural evidence for an A105L mutation suggests that a minor conformation may yield the minor 16α-hydroxyprogesterone metabolite. Third, substrate specificity of the subsequent 17,20-lyase reaction may be explained by variation in substrate height above the heme. Although 17α-hydroxyprogesterone is only observed farther from the catalytic iron, 17α-hydroxypregnenolone is also observed closer to the heme. In conjunction with spectroscopic evidence, this suggests that only 17α-hydroxypregnenolone approaches and interacts with the proximal oxygen of the catalytic iron-peroxy intermediate, yielding efficient production of dehydroepiandrosterone as the key intermediate in human testosterone and estrogen synthesis. Fourth, differential positioning of 17α-hydroxypregnenolone offers a mechanism whereby allosteric binding of cytochrome b5 might selectively enhance the lyase reaction. In aggregate, these structures provide a structural basis for understanding multiple key reactions at the heart of human steroidogenesis.

Novel oxazolinyl derivatives of pregna-5,17(20)-diene as 17α-hydroxylase/17,20-lyase (CYP17A1) inhibitors

New oxazolinyl derivatives of [17(20)E]-pregna-5,17(20)-diene: 2'-{[(E)-3β-hydroxyandrost-5-en-17-ylidene]methyl}-4',5'-dihydro-1',3'-oxazole 1 and 2'-{[(E)-3β-hydroxyandrost-5-en-17-ylidene]methyl}-4',4'-dimethyl-4',5'-dihydro-1',3'-oxazole 2 were evaluated as potential CYP17A1 inhibitors in comparison with 17-(pyridin-3-yl)androsta-5,16-dien-3β-ol 3 (abiraterone). Differential absorption spectra of human recombinant CYP17A1 in the presence of compound 1 (λmax=422 nm, λmin=386 nm) and compound 2 (λmax=416 nm) indicated significant differences in enzyme/inhibitors complexes. CYP17A1 activity was measured using electrochemical methods. Inhibitory activity of compound 1 was comparable with abiraterone 3 (IC50=0.9±0.1 μM, and IC50=1.3±0.1 μM, for compounds 1 and 3, respectively), while compound 2 was found to be weaker inhibitor (IC50=13±1 μM). Docking of aforementioned compounds to CYP17A1 revealed that steroid fragments of compound 1 and abiraterone 3 occupied close positions; oxazoline cycle of compound 1 was coordinated with heme iron similarly to pyridine cycle of abiraterone 3. Configuration of substituents at 17(20) double bond in preferred docked position corresponded to Z-isomers of compounds 1 and 2. Presence of 4'-substituents in oxazoline ring of compound 2 prevents coordination of oxazoline nitrogen with heme iron and worsens its docking score in comparison with compound 1. These data indicate that oxazolinyl derivative of [17(20)E]-pregna-5,17(20)-diene 1 (rather than 4',4'-dimethyl derivative 2) may be considered as potential CYP17A1 inhibitor and template for development of new compounds affecting growth and proliferation of prostate cancer cells.

Human cytochrome P450 17A1 conformational selection: modulation by ligand and cytochrome b5

Crystallographic studies of different membrane cytochrome P450 enzymes have provided examples of distinct structural conformations, suggesting protein flexibility. It has been speculated that conformational selection is an integral component of substrate recognition and access, but direct evidence of such substate interconversion has thus far remained elusive. In the current study, solution NMR revealed multiple and exchanging backbone conformations for certain structural features of the human steroidogenic cytochrome P450 17A1 (CYP17A1). This bifunctional enzyme is responsible for pregnenolone C17 hydroxylation, followed by a 17,20-lyase reaction to produce dehydroepiandrosterone, the key intermediate in human synthesis of androgen and estrogen sex steroids. The distribution of CYP17A1 conformational states was influenced by temperature, binding of these two substrates, and binding of the soluble domain of cytochrome b5 (b5). Notably, titration of b5 to CYP17A1·pregnenolone induced a set of conformational states closely resembling those of CYP17A1·17α-hydroxypregnenolone without b5, providing structural evidence consistent with the reported ability of b5 to selectively enhance 17,20-lyase activity. Solution NMR thus revealed a set of conformations likely to modulate human steroidogenesis by CYP17A1, demonstrating that this approach has the potential to make similar contributions to understanding the functions of other membrane P450 enzymes involved in drug metabolism and disease states.

Relative stability of different DNA guanine quadruplex stem topologies derived using large-scale quantum-chemical computations

We provide theoretical predictions of the intrinsic stability of different arrangements of guanine quadruplex (G-DNA) stems. Most computational studies of nucleic acids have applied Molecular Mechanics (MM) approaches using simple pairwise-additive force fields. The principle limitation of such calculations is the highly approximate nature of the force fields. In this study, we for the first time apply accurate QM computations (DFT-D3 with large atomic orbital basis sets) to essentially complete DNA building blocks, seven different folds of the cation-stabilized two-quartet G-DNA stem, each having more than 250 atoms. The solvent effects are approximated by COSMO continuum solvent. We reveal sizable differences between MM and QM descriptions of relative energies of different G-DNA stems, which apparently reflect approximations of the DNA force field. Using the QM energy data, we propose correction to earlier free energy estimates of relative stabilities of different parallel, hybrid, and antiparallel G-stem folds based on classical simulations. The new energy ranking visibly improves the agreement between theory and experiment. We predict the 5'-anti-anti-3' GpG dinucleotide step to be the most stable one, closely followed by the 5'-syn-anti-3' step. The results are in good agreement with known experimental structures of 2-, 3-, and 4-quartet G-DNA stems. Besides providing specific results for G-DNA, our study highlights basic limitations of force field modeling of nucleic acids. Although QM computations have their own limitations, mainly the lack of conformational sampling and the approximate description of the solvent, they can substantially improve the quality of calculations currently relying exclusively on force fields.

Structure-phenotype correlations of human CYP21A2 mutations in congenital adrenal hyperplasia

Mutations in the cytochrome p450 (CYP)21A2 gene, which encodes the enzyme steroid 21-hydroxylase, cause the majority of cases in congenital adrenal hyperplasia, an autosomal recessive disorder. To date, more than 100 CYP21A2 mutations have been reported. These mutations can be associated either with severe salt-wasting or simple virilizing phenotypes or with milder nonclassical phenotypes. Not all CYP21A2 mutations have, however, been characterized biochemically, and the clinical consequences of these mutations remain unknown. Using the crystal structure of its bovine homolog as a template, we have constructed a humanized model of CYP21A2 to provide comprehensive structural explanations for the clinical manifestations caused by each of the known disease-causing missense mutations in CYP21A2. Mutations that affect membrane anchoring, disrupt heme and/or substrate binding, or impair stability of CYP21A2 cause complete loss of function and salt-wasting disease. In contrast, mutations altering the transmembrane region or conserved hydrophobic patches cause up to a 98% reduction in enzyme activity and simple virilizing disease. Mild nonclassical disease can result from interference in oxidoreductase interactions, salt-bridge and hydrogen-bonding networks, and nonconserved hydrophobic clusters. A simple in silico evaluation of previously uncharacterized gene mutations could, thus, potentially help predict the often diverse phenotypes of a monogenic disorder.

Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms

Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure–activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein–ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance.

Structures of cytochrome P450 17A1 with prostate cancer drugs abiraterone and TOK-001

Cytochrome P450 17A1 (P450c17) catalyzes the biosynthesis of androgens in humans¹. Since prostate cancer cells proliferate in response to androgen steroids^2,3, CYP17A1 inhibition is a new strategy to prevent androgen synthesis and treat lethal metastatic castration-resistant prostate cancer⁴, but drug development has been hampered by the lack of a CYP17A1 structure. Here we report the only known structures of CYP17A1, which contain either abiraterone, a first-in-class steroidal inhibitor recently approved by the FDA for late-stage prostate cancer⁵, or TOK-001, another inhibitor in clinical trials^4,6. Both bind the heme iron forming a 60° angle above the heme plane, packing against the central I helix with the 3β-OH interacting with N202 in the F helix. Importantly, this binding mode differs substantially from those predicted by homology models or from steroids in other cytochrome P450 enzymes with known structures, with some features more similar to steroid receptors. While the overall CYP17A1 structure provides a rationale for understanding many mutations found in patients with steroidogenic diseases, the active site reveals multiple steric and hydrogen bonding features that will facilitate better understanding of the enzyme’s dual hydroxylase and lyase catalytic capabilities and assist in rational drug design. Specifically, structure-based design is expected to aid development of inhibitors that bind only CYP17A1 and solely inhibit its androgen-generating lyase activity to improve treatment of prostate and other hormone-responsive cancers.

Evaluation of model quality predictions in CASP9

CASP has been assessing the state of the art in the a priori estimation of accuracy of protein structure prediction since 2006. The inclusion of model quality assessment category in CASP contributed to a rapid development of methods in this area. In the last experiment, 46 quality assessment groups tested their approaches to estimate the accuracy of protein models as a whole and/or on a per-residue basis. We assessed the performance of these methods predominantly on the basis of the correlation between the predicted and observed quality of the models on both global and local scales. The ability of the methods to identify the models closest to the best one, to differentiate between good and bad models, and to identify well modeled regions was also analyzed. Our evaluations demonstrate that even though global quality assessment methods seem to approach perfection point (weighted average per-target Pearson's correlation coefficients are as high as 0.97 for the best groups), there is still room for improvement. First, all top-performing methods use consensus approaches to generate quality estimates, and this strategy has its own limitations. Second, the methods that are based on the analysis of individual models lag far behind clustering techniques and need a boost in performance. The methods for estimating per-residue accuracy of models are less accurate than global quality assessment methods, with an average weighted per-model correlation coefficient in the range of 0.63-0.72 for the best 10 groups.