Comparisons of Prostate Cancer Inhibitors Abiraterone and TOK-001 Binding with CYP17A1 through Molecular Dynamics

Identification of inhibitors from a functional food-based plant Perillae Folium against hyperuricemia via metabolomics profiling, network pharmacology and all-atom molecular dynamics simulations

Introduction

Hyperuricemia (HUA) is a metabolic disorder caused by purine metabolism dysfunction in which the increasing purine levels can be partially attributed to seafood consumption. Perillae Folium (PF), a widely used plant in functional food, has been historically used to mitigate seafood-induced diseases. However, its efficacy against HUA and the underlying mechanism remain unclear.

Methods

A network pharmacology analysis was performed to identify candidate targets and potential mechanisms involved in PF treating HUA. The candidate targets were determined based on TCMSP, SwissTargetPrediction, Open Targets Platform, GeneCards, Comparative Toxicogenomics Database, and DrugBank. The potential mechanisms were predicted via Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) analyses. Molecular docking in AutoDock Vina and PyRx were performed to predict the binding affinity and pose between herbal compounds and HUA-related targets. A chemical structure analysis of PF compounds was performed using OSIRIS DataWarrior and ClassyFire. We then conducted virtual pharmacokinetic and toxicity screening to filter potential inhibitors. We further performed verifications of these inhibitors' roles in HUA through molecular dynamics (MD) simulations, text-mining, and untargeted metabolomics analysis.

Results

We obtained 8200 predicted binding results between 328 herbal compounds and 25 potential targets, and xanthine dehydrogenase (XDH) exhibited the highest average binding affinity. We screened out five promising ligands (scutellarein, benzyl alpha-D-mannopyranoside, elemol, diisobutyl phthalate, and (3R)-hydroxy-beta-ionone) and performed MD simulations up to 50 ns for XDH complexed to them. The scutellarein-XDH complex exhibited the most satisfactory stability. Furthermore, the text-mining study provided laboratory evidence of scutellarein's function. The metabolomics approach identified 543 compounds and confirmed the presence of scutellarein. Extending MD simulations to 200 ns further indicated the sustained impact of scutellarein on XDH structure.

Conclusion

Our study provides a computational and biomedical basis for PF treating HUA and fully elucidates scutellarein's great potential as an XDH inhibitor at the molecular level, holding promise for future drug design and development.

Abiraterone induces SLCO1B3 expression in prostate cancer via microRNA-579-3p

Understanding mechanisms of resistance to abiraterone, one of the primary drugs approved for the treatment of castration resistant prostate cancer, remains a priority. The organic anion polypeptide 1B3 (OATP1B3, encoded by SLCO1B3) transporter has been shown to transport androgens into prostate cancer cells. In this study we observed and investigated the mechanism of induction of SLCO1B3 by abiraterone. Prostate cancer cells (22Rv1, LNCaP, and VCAP) were treated with anti-androgens and assessed for SLCO1B3 expression by qPCR analysis. Abiraterone treatment increased SLCO1B3 expression in 22Rv1 cells in vitro and in the 22Rv1 xenograft model in vivo. MicroRNA profiling of abiraterone-treated 22Rv1 cells was performed using a NanoString nCounter miRNA panel followed by miRNA target prediction. TargetScan and miRanda prediction tools identified hsa-miR-579-3p as binding to the 3'-untranslated region (3'UTR) of the SLCO1B3. Using dual luciferase reporter assays, we verified that hsa-miR-579-3p indeed binds to the SLCO1B3 3'UTR and significantly inhibited SLCO1B3 reporter activity. Treatment with abiraterone significantly downregulated hsa-miR-579-3p, indicating its potential role in upregulating SLCO1B3 expression. In this study, we demonstrated a novel miRNA-mediated mechanism of abiraterone-induced SLCO1B3 expression, a transporter that is also responsible for driving androgen deprivation therapy resistance. Understanding mechanisms of abiraterone resistance mediated via differential miRNA expression will assist in the identification of potential miRNA biomarkers of treatment resistance and the development of future therapeutics.

Abiraterone and D4, 3-keto Abiraterone binding to CYP17A1, a structural comparison study by molecular dynamic simulation

The importance of computer-aided drug design and development is clear nowadays. These approaches smooth the way of designing some efficient candidates based on drugs in use. At this place, we studied the mechanism of D4-abiraterone (D4A), the active metabolite of Abiraterone (Abi), binding to CYP17A1 compared with Abi. The molecular dynamics simulation results reveal that the metabolite, which lacks the key 3β-OH group, has a varied H-bond forming pattern. The critical H-bond between 3β-OH of Abi with Asn_202 turns to 3 Keto-O of D4A with Arg_239 in the substrate-binding site. This interaction causes a remarkable distance of 0.63 nm between D4A nitrogen and Fe in heme, which reduces its 17,20 lyase selectivity. The D4A keto moiety presents an immense number of H-bond with surrounding solvent molecules compared with the Abi hydroxyl group. As a result, D4A develops a weaker H-bond network with the enzyme. Otherwise, the heterocyclic nature of inhibitors helps for noticeable van der Waals interaction formation with CYP17A1. However, Abi stabilized position in the binding site helps more van der Waals interactions deposition than D4A. These results convinced the importance of the conserved H-bond for acquiring the proper position by the substrate or inhibitor in the binding site.

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.

Investigating the role of N-terminal domain in phosphodiesterase 4B-inhibition by molecular dynamics simulation

Phosphodiesterase 4B (PDE4B) is a potential therapeutic target for the inflammatory respiratory diseases such as congestive obstructive pulmonary disease (COPD) and asthma. The sequence identity of ∼88% with its isoform PDE4D is the key barrier in developing selective PDE4B inhibitors which may help to overcome associated side effects. Despite high sequence identity, both isoforms differ in few residues present in N-terminal (UCR2) and C-terminal (CR3) involved in catalytic site formation. Previously, we designed and tested specific PDE4B inhibitors considering N-terminal residues as a part of the catalytic cavity. In continuation, current work thoroughly presents an MD simulation-based analysis of N-terminal residues and their role in ligand binding. The various parameters viz. root mean square deviation (RMSD), radius of gyration (Rg), root mean square fluctuation (RMSF), principal component analysis (PCA), dynamical cross-correlation matrix (DCCM) analysis, secondary structure analysis and residue interaction mapping were investigated to establish rational. Results showed that UCR2 reduced RMSF values for the metal binding pocket (31.5 ± 11 to 13.12 ± 6 Ų) and the substrate-binding pocket (38.8 ± 32 to 17.3 ± 11 Ų). UCR2 enhanced anti-correlated motion at the active site region that led to the improved ligand-binding affinity of PDE4B from -24.57 ± 3 to -35.54 ± 2 kcal/mol. Further, the atomic-level analysis indicated that T-π and π-π interactions between inhibitors and residues are vital forces that regulate inhibitor association to PDE4B with high affinity. In conclusion, UCR2, the N-terminal domain, embraces the dynamics of PDE4B active site and stabilizes PDE4B inhibitor interactions. Therefore the N-terminal domain needs to be considered while designing next-generation, selective PDE4B-inhibitors as potential anti-inflammatory drugs. Communicated by Ramaswamy H. Sarma.

New steroidal oxazolines, benzoxazoles and benzimidazoles related to abiraterone and galeterone

Seven new oxazoline, benzoxazole and benzimidazole derivatives were synthesized from 3β-acetoxyandrosta-5,16-dien-17-carboxylic, 3β-acetoxyandrost-5-en-17β-carboxylic and 3β-acetoxypregn-5-en-21-oic acids. Docking to active site of human 17α-hydroxylase/17,20-lyase revealed that all oxazolines, as well as benzoxazoles and benzimidazoles comprising Δ¹⁶ could form stable complexes with enzyme, in which steroid moiety is positioned similarly to that of abiraterone and galeterone, and nitrogen atom coordinates heme iron, while 16,17-saturated benzoxazoles and benzimidazoles could only bind in a position where heterocycle is located nearly parallel to heme plane. Modeling of the interaction of new benzoxazole and benzimidazole derivatives with androgen receptor revealed the destabilization of helix 12, constituting activation function 2 (AF2) site, by mentioned compounds, similar to one induced by known antagonist galeterone. The synthesized compounds inhibited growth of prostate carcinoma LNCaP and PC-3 cells at 96 h incubation; the potency of 2'-(3β-hydroxyandrosta-5,16-dien-17-yl)-4',5'-dihydro-1',3'-oxazole and 2'-(3β-hydroxyandrosta-5,16-dien-17-yl)-benzimidazole was superior and could inspire further investigations of these compounds as potential anti-cancer agents.

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.

[Synthesis and evaluation of N-alkynylaminosteroids as potential CYP450 17A1 inhibitors]

Four isomeric dehydroepiandrosterone- and pregnenolone-based N-alkynylaminosteroids were synthesized and tested in vitro for inhibition of heterologously expressed CYP17A1. The highest inhibitory activity was observed when the optimal number of side chain atoms was met. The conjugate based on pregnenolone containing an N-propynyl moiety was found to interefere with enzymatic activity most effectively and consistently in the micromolar range.

Bioinformatics and functional analyses of key genes in smoking-associated lung adenocarcinoma

Smoking is one of the most important factors associated with the development of lung cancer. However, the signaling pathways and driver genes in smoking-associated lung adenocarcinoma remain unknown. The present study analyzed 433 samples of smoking-associated lung adenocarcinoma and 75 samples of non-smoking lung adenocarcinoma from the Cancer Genome Atlas database. Gene Ontology (GO) analysis was performed using the Database for Annotation, Visualization and Integrated Discovery and the ggplot2 R/Bioconductor package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the R packages RSQLite and org.Hs.eg.db. Multivariate Cox regression analysis was performed to screen factors associated with patient survival. Kaplan-Meier and receiver operating characteristic curves were used to analyze the potential clinical significance of the identified biomarkers as molecular prognostic markers for the five-year overall survival time. A total of 373 differentially expressed genes (DEGs; |log2-fold change|≥2.0 and P<0.01) were identified, of which 71 were downregulated and 302 were upregulated. These DEGs were associated with 28 significant GO functions and 11 significant KEGG pathways (false discovery rate <0.05). Two hundred thirty-eight proteins were associated with the 373 differentially expressed genes, and a protein-protein interaction network was constructed. Multivariate regression analysis revealed that 7 mRNAs, cytochrome P450 family 17 subfamily A member 1, PKHD1 like 1, retinoid isomerohydrolase RPE65, neurotensin receptor 1, fetuin B, insulin-like growth factor binding protein 1 and glucose-6-phosphatase catalytic subunit, significantly distinguished between non-smoking and smoking-associated adenocarcinomas. Kaplan-Meier analysis demonstrated that patients in the 7 mRNAs-high-risk group had a significantly worse prognosis than those of the low-risk group. The data obtained in the current study suggested that these genes may serve as potential novel prognostic biomarkers of smoking-associated lung adenocarcinoma.

Comparative study of the binding mode between cytochrome P450 17A1 and prostate cancer drugs in the absence of haem iron

According to the X-ray crystal structures of CYP17A1 (including its complexes with inhibitors), it is shown that a hydrogen bond exists between CYP17A1 and its inhibitors (such as abiraterone and TOK-001). Previous short MD simulations (50 ns) suggested that the binding of abiraterone to CYP17A1 is stronger than that of TOK-001. In this work, by carrying out long atomistic MD simulations (200 ns) of CYP17A1 and its complexes with abiraterone and TOK-001, we observed a binding mode between CYP17A1 and abiraterone, which is different from the binding mode between CYP17A1 and TOK-001. In the case of abiraterone binding, the unfilled volume in the active site cavity increases the freedom of movement of abiraterone within CYP17A1, leading to the collective motions of the helices G and B' as well as the breaking of hydrogen bond existing between the 3β-OH group of abiraterone and N202 of CYP17A1. However, the unfilled volume in the active site cavity can be occupied by the benzimidazole ring of TOK-001, restraining the motion of TOK-001. By pulling the two inhibitors (abiraterone and TOK-001) out of the binding pocket in CYP17A1, we discovered that abiraterone and TOK-001 were moved from their binding sites to the surface of protein similarly through the channels formed by the helices G and B'. In addition, based on the free energy calculations, one can see that it is energetically favorable for the two inhibitors (abiraterone and TOK-001) to enter into the binding pocket in CYP17A1.

Structure-based optimisation of non-steroidal cytochrome P450 17A1 inhibitors

Five new non-steroidal inhibitors for cytochrome P450 17A1 were identified by structure-based optimisation.

Transcriptome Analysis of WHV/c-myc Transgenic Mice Implicates Cytochrome P450 Enzyme 17A1 as a Promising Biomarker for Hepatocellular Carcinoma

Early detection of hepatocellular carcinoma (HCC) is critical for successful treatment and favorable prognosis. To identify novel HCC biomarkers, we used the WHV/c-myc transgenic (Tg) mice, an animal model of hepatocarcinogenesis. By analyzing their gene expression profiling, we investigated differentially expressed genes in livers of wild-type and Tg mice. The cytochrome P450, family 17, subfamily A, polypeptide 1 (CYP17A1), a hepatic P450 enzyme, was revealed to be overexpressed in the liver tissues of Tg mice at both preneoplastic and neoplastic stages. Mouse-to-human validation demonstrated that CYP17A1 mRNA and protein were also significantly increased in human HCC tissues compared with paired nontumor tissues (P = 0.00041 and 0.00011, respectively). Immunohistochemical studies showed that CYP17A1 was overexpressed in 67% (58 of 87) of HCC, and strong staining of CYP17A1 was observed in well-differentiated HCCs. Consistent with this, the median serum levels of CYP17A1 were also significantly higher in patients with HCC (140.2 ng/mL, n = 776) compared with healthy controls (31.4 ng/mL, n = 366) and to those with hepatitis B virus (57.5 ng/mL, n = 160), cirrhosis (46.1 ng/mL, n = 147), lung cancer (27.4 ng/mL, n = 109), and prostate cancer (42.1 ng/mL, n = 130; all P < 0.001). Notably, the elevations were seen in most AFP-negative HCC cases. Altogether, through mouse-to-human search and validation, we found that CYP17A1 is overexpressed in HCCs and it has great potentiality as a noninvasive marker for HCC detection. These results provide a rationale for the future development and clinical application of CYP17A1 measurement to diagnose HCC more precisely. Cancer Prev Res; 9(9); 739-49. ©2016 AACR.