Comparative pharmacophore development for inhibitors of human and rat 5-alpha-reductase

Virtual screening approach for the discovery of selective 5α-reductase type II inhibitors for benign prostatic hyperplasia treatment

Background: 5α-Reductase type II (5αR2) inhibition is a promising strategy for benign prostatic hyperplasia treatment. A computational approach including virtual screening, ligand-based 3D pharmacophore modeling, 2D quantitative structure-activity relationship and molecular docking simulations were adopted to develop novel inhibitors. Results: Hits were first filtered via the validated pharmacophore and 2D quantitative structure-activity relationship models. Docking on the recently determined cocrystallized structure of 5αR2 showed three promising hits. Visual inspection results were compared with finasteride ligand and dihydrotestosterone as reference, to explain the role of binding to Glu57 and Tyr91 for 5αR2 selective inhibition. Conclusion: Alignment between Hit 2 and finasteride in the binding pocket showed similar binding modes. The biological activity prediction showed antitumor and androgen targeting activity of the new hits.

Novel and Predictive QSAR Model for Steroidal and Nonsteroidal 5α- Reductase Type II Inhibitors

AIMS AND OBJECTIVE

In this study, a novel quantitative structure activity relationship (QSAR) model has been developed for inhibitors of human 5-alpha reductase type II, which are used to treat benign prostate hypertrophy (BPH).

METHODS

The dataset consisted of 113 compounds-mainly nonsteroidal-with known inhibitory concentration. Then 3D structures of compounds were optimized and molecular structure descriptors were calculated. The stepwise multiple linear regression was used to select descriptors encoding the inhibitory activity of the compounds. Multiple linear regression (MLR) was used to build up the linear QSAR model.

RESULTS

The results obtained revealed that the descriptors which best describe the activity were atom type electropological state, carbon type, radial distribution function (RDF), barysz matrix and molecular linear free energy relation. The suggested model could achieve satisfied square correlation coefficient of R² = 0.72, higher than of many previous studies, indicating its superiority. Rigid validation criteria were met using external data with Q² ˃ 0.5 and R² = 0.75, reflecting the predictive power of the model.

CONCLUSION

The QSAR model was applied for screening botanical components of herbal preparations used to treat BPH, and could predict the activity of some, among others, making reasonable attribution to the proposed effect of these preparations. Gamma tocopherol was found to be an active inhibitor, in consistence with many previous studies, anticipating the power of this model in the prediction of new candidate molecules and suggesting further investigations.

Hypothesis on Serenoa repens (Bartram) small extract inhibition of prostatic 5α-reductase through an in silico approach on 5β-reductase x-ray structure

Benign prostatic hyperplasia is a common disease in men aged over 50 years old, with an incidence increasing to more than 80% over the age of 70, that is increasingly going to attract pharmaceutical interest. Within conventional therapies, such as α-adrenoreceptor antagonists and 5α-reductase inhibitor, there is a large requirement for treatments with less adverse events on, e.g., blood pressure and sexual function: phytotherapy may be the right way to fill this need. Serenoa repens standardized extract has been widely studied and its ability to reduce lower urinary tract symptoms related to benign prostatic hyperplasia is comprehensively described in literature. An innovative investigation on the mechanism of inhibition of 5α-reductase by Serenoa repens extract active principles is proposed in this work through computational methods, performing molecular docking simulations on the crystal structure of human liver 5β-reductase. The results confirm that both sterols and fatty acids can play a role in the inhibition of the enzyme, thus, suggesting a competitive mechanism of inhibition. This work proposes a further confirmation for the rational use of herbal products in the management of benign prostatic hyperplasia, and suggests computational methods as an innovative, low cost, and non-invasive process for the study of phytocomplex activity toward proteic targets.

Benign prostatic hyperplasia: An overview of existing treatment

Benign prostatic hyperplasia (BPH) is the most common condition in aging men, associated with lower urinary tract symptoms (LUTS). A better understanding of the prostate physiology, function, and pathogenesis has led to the development of promising agents, useful in the management of LUTS in men. The specific approach used to treat BPH depends upon number of factors like age, prostrate size, weight, prostate-specific antigen level, and severity of the symptoms. 5α-reductase inhibitors decrease the production of dihydrotestosterone within the prostate, which results in decreased prostate volume, increased peak urinary flow rate, improvement of symptoms, decreased risk of acute urinary retention, and need for surgical intervention. α(1)-adrenergic receptor (α(1)-AR) antagonists decrease LUTS and increase urinary flow rates in men with symptomatic BPH, but do not reduce the long-term risk of urinary retention or need for surgical intervention. Clinical efficacy of either 5α-reductase inhibitor or α(1)-AR antagonist has been further improved by using combination therapy; however, long-term outcomes are still awaited. Many more potential new therapies are under development that may improve the treatment of BPH. This article gives a brief account of rationale and efficacy of different treatment options presently available in the management of BPH.

Pharmacophore mapping of arylamino-substituted benzo[b]thiophenes as free radical scavengers

Predictive pharmacophore models have been developed for a series of arylamino-substituted benzo[b]thiophenes exhibiting free radical scavenging activity. 3D pharmacophore models were generated using a set of 20 training set compounds and subsequently validated by mapping 6 test set compounds using Discovery Studio 2.1 software. Further model validation was performed by randomizing the data using Fischer's validation technique at the 95% confidence level. The most predictive pharmacophore model developed using the conformers obtained from the BEST method showed a correlation coefficient (r) of 0.942 and consisted of three features: hydrogen bond donor, hydrogen bond acceptor and aromatic ring. Acceptable values of external validation parameters, like R2pred (0.853) and r2m(test) (0.844), also implied that the external predictivity of the model was significant. The development of further pharmacophore models using conformers obtained from the FAST method yielded a few models with good predictivity, with the best one (r=0.904) consisting of two features: hydrogen bond donor and hydrogen bond acceptor. Significant values of external validation parameters, R2pred (0.913) and r2m(test) (0.821), also reflect the high predictive ability of the model. Again, Fischer validation results implied that the models developed were robust enough and their good results were not based on mere chance. These validation approaches indicate the reliability of the predictive abilities of the 3D pharmacophore models developed here, which may thus be further utilized as a 3D query tool in the virtual screening of new chemical entities with potent antioxidant activities.

Biocatalytic synthesis of 4-pregnen-20,21-diol-3-one, a selective inhibitor of human 5alpha-reductase type II

Biocatalysis, the conversion of substrates into valuable products by the use of enzymes, has some striking advantages in comparison to standard organic chemistry for drug synthesis. By biocatalysis, substrates that contain several identical reactive groups at different positions can be converted with high regio-selectivity and enantio-selectivity. In this study, an E. coli isolate (E132) was identified which was able to convert the steroid desoxycorticosterone into the product 4-pregnen-20,21-diol-3-one in real terms. The product was purified from the cell culture supernatant by HPLC and its structure was demonstrated by mass spectrometry and NMR spectroscopy. It was tested on inhibition of human 5alpha-reductases type I and type II. At a concentration of 10 microM, inhibition was 49.0% for type I and 81.8% for type II, whereas there was no inhibition of human aromatase (CYP19) at 20 microM and human 17alpha-hydroxylase-C17,20-lyase (CYP17) at 2.5 microM detectable. The IC50 value of 4-pregnen-20,21-diol-3-one for human 5alpha-reductase type II was determined to be 1.56 microM.

Pharmacophore identification and virtual screening for methionyl-tRNA synthetase inhibitors

Aminoacyl-tRNA synthetases (aaRSs) are essential enzymes involved in protein biosynthesis in all living organisms and are an unexploited antibacterial targets, as many strains of bacteria have become resistant to all established classes of antibiotics. Therefore, the main aim of this study is to discover new lead molecules which would be useful as anti-bacterial compounds. Pharmacophore models were developed by using CATALYST HypoGen with a training set of 29 diverse methionyl-tRNA synthetase (MetRS) inhibitors. The best quantitative pharmacophore hypothesis (Hypo1) obtained a correlation coefficient of 0.975, root mean square deviation (RMSD) of 0.55 and cost difference (null cost-total cost) of 70.32. This Hypo1 was validated by two methods, first by using 104 test set molecules which resulted a correlation of 0.926 between HypoGen estimated activities versus experimental activities and secondly by Cat-Scramble validation method. This validated pharmacophore model was further used for screening databases for discovery of new MetRS inhibitors. The new lead compounds were further analyzed for drug-like properties. Homology modeled structure of Staphylococcus aureus MetRS was built and molecular docking studies were performed with many inhibitors using the newly built protein structure. Finally, it was found that the new leads exhibited good estimated inhibitory activity, calculated binding properties similar to experimentally proven compounds and also favorable drug-like properties.

Methyl esters of N-(dicyclohexyl)acetyl-piperidine-4-(benzylidene-4-carboxylic acids) as drugs and prodrugs: a new strategy for dual inhibition of 5 alpha-reductase type 1 and type 2

Steroid 5alpha-reductase (5alphaR) inhibitory potency of three N-(dicyclohexyl)acetyl-piperidine-4-(benzylidene-4-carboxylic acids) and their corresponding methyl esters was monitored for type 2 isoenzyme in a benign prostatic hyperplasia cell free preparation and for type 1 isoenzyme in DU145 cells and in a cell free assay. The hydrolytic stability of the esters and their bioconversion to the corresponding acids was assessed in aqueous buffered solution (pH 7.4) and in selected biological media having measurable esterase activities. The carboxylic acids 1, 2, and 3 with high type 2 inhibitory potencies displayed only little type 1 inhibition. The esters 1a, 2a, and 3a, originally designed as prodrugs to enhance cell permeation, proved to be potent type 1 inhibitors and are therefore acting as drugs themselves. They are stable in buffered salt solution (pH 7.4), Caco-2 cells, and human plasma, whereas all esters are cleaved into the corresponding acids in benign prostatic hyperplasia tissue homogenate. Methyl esters, applied as hydrolytically stable precursor drugs to facilitate cell permeation, will yield the corresponding carboxylic acids as type 2 inhibitors after hydrolysis in the target organ. The esters themselves--stable in human plasma and Caco-2 cells--are acting as potent drugs toward 5alphaR type 1. Thus, dual inhibition of 5alphaR type 1 and type 2 can be achieved by applying a single parent compound.

Generation of predictive pharmacophore model for SARS-coronavirus main proteinase

Pharmacophore-based virtual screening is an effective, inexpensive and fast approach to discovering useful starting points for drug discovery. In this study, we developed a pharmacophore model for the main proteinase of severe acute respiratory syndrome coronavirus (SARS-CoV). Then we used this pharmacophore model to search NCI 3D database including 250, 251 compounds and identified 30 existing drugs containing the pharmacophore query. Among them are six compounds that already exhibited anti-SARS-CoV activity experimentally. This means that our pharmacophore model can lead to the discovery of potent anti-SARS-CoV inhibitors or promising lead compounds for further SARS-CoV main proteinase inhibitor development.