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.

Several genome-wide association studies have identified single-nucleotide polymorphisms (SNPs), such as rs4409766, rs1004467, and rs3824755 in CYP17A1 and rs2021783 in CYP21A2, as new hypertension susceptibility genetic variants in the Chinese population. This study aimed to look into the relationship between preeclampsia (PE) and these SNPs in Chinese Han women.
Overall, 5021 unrelated pregnant women were recruited, including 2002 patients with PE and 3019 normal healthy controls. The real-time PCR (TaqMan) method was applied to genotype these four polymorphisms.
A statistically obvious difference in the allelic frequencies was observed in CYP21A2 rs2021783 between cases and controls (χ2 = 7.201, Pc = 0.028 by allele), and the T allele was associated with the occurrence and development of PE (OR = 1.151, 95% CI 1.039-1.275). We also found a significant association between rs2021783 and the development of early-onset PE (Pc = 0.008 by genotype, Pc = 0.004 by allele). For rs1004467 and rs3824755, the distribution of allelic frequencies differed markedly between mild PE and control groups (χ2 = 6.843, Pc = 0.036; χ2 = 6.869, Pc = 0.036), and patients with the TT genotype of rs1004467 were less easy to develop mild PE than were those carrying the CT or CC genotype (χ2 = 7.002, Pc = 0.032, OR = 1.306, 95% CI 1.071-1.593). The GG genotype of rs3824755 appeared to a protective effect on the occurrence of mild PE (OR = 0.766, 95% CI 0.629-0.934).
CYP21A2 rs2021783 appears to be closely related to PE susceptibility, and CYP17A1 rs1004467 and rs3824755 seem to be closely associated with mild PE in Han women.

OBJECTIVE: Polycystic ovary syndrome (PCOS) is a complex multifactorial endocrine disorder affecting approximately 5-10% of women of reproductive age. Affected women have menstrual disturbances due to anovulation, infertility, and hyperandrogenism. Ovarian androgen overproduction is the key physiopathologic feature of PCOS. A number of genes encoding major enzymes of the androgen metabolic pathways, such as HSD17B6, CYP19A1, CYP11A1, CYP17A1, and INSR, have been examined. Very few studies have been done in North India. There is an increasing prevalence of PCOS in women in Punjab and it is the leading cause of female infertility. In view of the strong evidence implicating the importance of CYP19A1 and CYP17A1 in androgen metabolic pathways, we investigated the association of rs700519, rs2414096, and rs743572 (- 34T>C) polymorphisms on susceptibility of developing PCOS, in North India.
METHODS: A total of 500 subjects (women of reproductive age) including 250 PCOS cases and 250 healthy age-matched controls were included in the present study. DNA was extracted from venous blood for all samples, and association analysis for rs2414096, rs700519, and rs743572 was done by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. Lipid profile was done using a biochemical analyzer and body mass index (BMI) was measured for all cases. Statistical analysis was performed.
RESULTS: Significant association of - 34T>C polymorphism of CYP17A1 was found with PCOS (p = 0.0005). BMI was statistically different between PCOS cases and controls (p = 0.000). Triglycerides were high in PCOS women. Variations of CYP19A1 were not statistically significant with PCOS.
CONCLUSIONS: These data suggest that - 34T>C polymorphism in CYP17A1 is associated with PCOS in North India. No polymorphism of CYP19A1 was found to be associated.

BACKGROUND: Genome-wide association studies have linked CYP17A1 coding for the steroid hormone synthesizing enzyme 17α-hydroxylase (CYP17A1) to blood pressure (BP). We hypothesized that the genetic signal may translate into a correlation of ambulatory BP (ABP) with apparent CYP17A1 activity in a family-based population study and estimated the heritability of CYP17A1 activity.
METHODS: In the Swiss Kidney Project on Genes in Hypertension, day and night urinary excretions of steroid hormone metabolites were measured in 518 participants (220 men, 298 women), randomly selected from the general population. CYP17A1 activity was assessed by 2 ratios of urinary steroid metabolites: one estimating the combined 17α-hydroxylase/17,20-lyase activity (ratio 1) and the other predominantly 17α-hydroxylase activity (ratio 2). A mixed linear model was used to investigate the association of ABP with log-transformed CYP17A1 activities exploring effect modification by urinary sodium excretion.
RESULTS: Daytime ABP was positively associated with ratio 1 under conditions of high, but not low urinary sodium excretion (P interaction <0.05). Ratio 2 was not associated with ABP. Heritability estimates (SE) for day and night CYP17A1 activities were 0.39 (0.10) and 0.40 (0.09) for ratio 1, and 0.71 (0.09) and 0.55 (0.09) for ratio 2 (P values <0.001). CYP17A1 activities, assessed with ratio 1, were lower in older participants.
CONCLUSIONS: Low apparent CYP17A1 activity (assessed with ratio 1) is associated with elevated daytime ABP when salt intake is high. CYP17A1 activity is heritable and diminished in the elderly. These observations highlight the modifying effect of salt intake on the association of CYP17A1 with BP.

BACKGROUND: Prostate cancer (PCa) is an androgen-dependent disease. Nonetheless, the role of single nucleotide polymorphisms (SNPs) in genes encoding androgen metabolism remains an unexplored area.
OBJECTIVE: To investigate the role of germline variations in cytochrome P450 17A1 (CYP17A1) and steroid-5α-reductase, α-polypeptides 1 and 2 (SRD5A1 and SRD5A2) genes in PCa.
METHODS: In total, 494 consecutive Spanish patients diagnosed with nonmetastatic localized PCa were included in this multicenter study and were genotyped for 32 SNPs in SRD5A1, SRD5A2, and CYP17A1 genes using a Biotrove OpenArray NT Cycler. Clinical data were available. Genotypic and allelic frequencies, as well as haplotype analyses, were determined using the web-based environment SNPator. All additional statistical analyses comparing clinical data and SNPs were performed using PASW Statistics 15.
RESULTS: The call rate obtained (determined as the percentage of successful determinations) was 97.3% of detection. A total of 2 SNPs in SRD5A1-rs3822430 and rs1691053-were associated with prostate-specific antigen level at diagnosis. Moreover, G carriers for both SNPs were at higher risk of presenting initial prostate-specific antigen levels>20ng/ml (Exp(B) = 2.812, 95% CI: 1.397-5.657, P = 0.004) than those who are AA-AA carriers. Haplotype analyses showed that patients with PCa nonhomozygous for the haplotype GCTTGTAGTA were at an elevated risk of presenting bigger clinical tumor size (Exp(B) = 3.823, 95% CI: 1.280-11.416, P = 0.016), and higher Gleason score (Exp(B) = 2.808, 95% CI: 1.134-6.953, P = 0.026).
CONCLUSIONS: SNPs in SRD5A1 seem to affect the clinical characteristics of Spanish patients with PCa.

The herbicide linuron (LIN) is an endocrine disruptor with an anti-androgenic mode of action. The objectives of this study were to (1) improve knowledge of androgen and anti-androgen signaling in the teleostean ovary and to (2) assess the ability of gene networks and machine learning to classify LIN as an anti-androgen using transcriptomic data. Ovarian explants from vitellogenic fathead minnows (FHMs) were exposed to three concentrations of either 5α-dihydrotestosterone (DHT), flutamide (FLUT), or LIN for 12h. Ovaries exposed to DHT showed a significant increase in 17β-estradiol (E2) production while FLUT and LIN had no effect on E2. To improve understanding of androgen receptor signaling in the ovary, a reciprocal gene expression network was constructed for DHT and FLUT using pathway analysis and these data suggested that steroid metabolism, translation, and DNA replication are processes regulated through AR signaling in the ovary. Sub-network enrichment analysis revealed that FLUT and LIN shared more regulated gene networks in common compared to DHT. Using transcriptomic datasets from different fish species, machine learning algorithms classified LIN successfully with other anti-androgens. This study advances knowledge regarding molecular signaling cascades in the ovary that are responsive to androgens and anti-androgens and provides proof of concept that gene network analysis and machine learning can classify priority chemicals using experimental transcriptomic data collected from different fish species.

An approach for evaluating and integrating genomic data in chemical risk assessment was developed based on the lessons learned from performing a case study for the chemical dibutyl phthalate. A case study prototype approach was first developed in accordance with EPA guidance and recommendations of the scientific community. Dibutyl phthalate (DBP) was selected for the case study exercise. The scoping phase of the dibutyl phthalate case study was conducted by considering the available DBP genomic data, taken together with the entire data set, for whether they could inform various risk assessment aspects, such as toxicodynamics, toxicokinetics, and dose-response. A description of weighing the available dibutyl phthalate data set for utility in risk assessment provides an example for considering genomic data for future chemical assessments. As a result of conducting the scoping process, two questions--Do the DBP toxicogenomic data inform 1) the mechanisms or modes of action?, and 2) the interspecies differences in toxicodynamics?--were selected to focus the case study exercise. Principles of the general approach include considering the genomics data in conjunction with all other data to determine their ability to inform the various qualitative and/or quantitative aspects of risk assessment, and evaluating the relationship between the available genomic and toxicity outcome data with respect to study comparability and phenotypic anchoring. Based on experience from the DBP case study, recommendations and a general approach for integrating genomic data in chemical assessment were developed to advance the broader effort to utilize 21st century data in risk assessment.