Current Pharmaceutical Design - Volume 31, Issue 26, 2025

Polycystic ovarian syndrome (PCOS) is a hormonal disorder caused by excessive secretion of male sex hormones in females. Herbal remedies for PCOS are lightning up as they bypass the adverse effects and are profoundly safe on prolonged usage.

The present study included a selection of 34 herbs pursuing biological effects on the uterus, and their major chemical constituents were subjected to a series of in silico techniques using different software. The proteins contributing majorly to the hormonal functions like human cytochrome P450 CYP17A1 (3RUK), progesterone (1E3K), and estrogen receptor (1X7R) were selected for the study.

Molecular docking studies were performed using AutoDock 1.5.7. The pharmacokinetic properties were predicted using the SwissADME online tool, while toxicity parameters were assessed with OSIRIS toxicity explorer and pkCSM. Molecular dynamics simulations and free energy calculations were performed using the Schrödinger suite.

Constituents with a basic steroidal nucleus demonstrated high binding energy values. An analysis of all the in silico techniques showed that Sarsasapogenin from Asparagus racemosus exhibited strong binding energies of -10.88 kcal/mol, -10.51 kcal/mol, and -9.79 kcal/mol with the selected specific proteins. In molecular dynamics simulations, Sarsasapogenin displayed ideal stability, with RMSD fluctuations below 3 Å and RMSF slightly higher than the corresponding peak of apoprotein. Additionally, it showed a favorable drug-likeness profile and non-toxic effects across all screened parameters.

From the list of the selected constituents, Sarsasapogenin was found to be ideal, and further research on it for targeting PCOS is expected to yield promising results.

Ritonavir (RTV) is an antiviral drug that prevents human immunodeficiency virus (HIV). However, it has low bioavailability, which can be improved with the assistance of Solid Lipid Nanoparticles (SLNs).

The present work aimed to formulate and optimize RTV-loaded SLNs using Box–Behnken design and evaluate the permeability coefficient using ex vivo permeation studies.

RTV-SLNs were prepared using the ultrasonication technique. The SLN formulation was optimized based on particle size, % entrapment efficiency, and % cumulative drug release using response surface methodology resulting from Box-Behnken design. The Fourier-Transform Infrared spectroscopy (FT-IR), Differential Scanning Calorimetry (DSC), and transmission Electron Microscopy (TEM) studies were carried out for the characterization of optimized SLN formulation. Ex vivo permeation studies were also performed using chicken ileum.

The optimized RTV-SLNs had a particle size of 270.34 nm, polydispersity index of 0.157, and zeta potential of -25.2 mV. The % entrapment efficiency and % cumulative drug release were found to be 94.33% and 67.13%, respectively. The FT-IR study revealed that SLNs showed no significant interactions between the drug and lipid in the formulation. The % crystalline index of the RTV-loaded SLN formulation was found to be 44.31% compared to the reference value of 100% for lipids. TEM analysis showed spherical nanoparticles that were uniform in shape. The release kinetics data demonstrated the drug release behavior, followed by the Korsmeyer-Peppas model, and suggested that the release from SLNs followed the non-fiction diffusion. The permeability coefficient of optimized SLN formulation was found to be significantly (p < 0.05) more compared to free RTV suspension. The enhancement ratio results suggested that RTV-SLNs permeated significantly (p < 0.05) faster (approximately 3.5 times) as compared to free RTV suspension.

The optimized RTV-SLNs could be a promising carrier for improving the oral bioavailability of RTV.

The well-known histamine H3 receptor antagonists are based on an imidazole scaffold. However, the interaction between hepatic CYP450 and imidazole-based drugs leads to some side effects, such as low potential, physicochemical problems, etc. Therefore, another category of chemical class, benzimidazolone has been explored as an antihistaminic H3 agent.

In this study, the histamine H3 binding affinity of benzimidazolone derivatives has been quantitatively investigated using Dragon descriptors.

The models were developed from statistically corroborated quantitative structure-activity relationship (QSAR) models that delivered rationales for the description of the binding affinity of benzimidazolone-based derivatives. In addition, the identified descriptors through CP-MLR analysis for the histamine H3 binding affinity highlighted the role of symmetry, atomic mass, information content, electrostaticity, rings in the structures, number of chlorine atoms (nCL), and average valence connectivity index chi-3 (X3Av).

The PLS assessment validated the power of CP-MLR-identified descriptors. The applicability domain suggested that the model fulfills the superior feature parameters with good fit and predictive power.

All the compounds were found to be within the applicability domain of the recommended models.

Today, diabetes mellitus (DM) is considered a major global health problem and, especially diabetes mellitus type-2 (T2DM), which accounts for 90-95% of all diabetes cases. Among the novel glucose-lowering agents, dipeptidyl peptidase-4 (DPP-4) inhibitors have been extensively studied in recent years.

This paper integrates a QSAR study and docking analysis of a series of uracil-based benzoic acid and ester derivatives as novel DPP-4 inhibitors.

The correlation of chemical structure with the biological activity in CP-MLR led to the detection of eleven descriptors from various classes of Dragon descriptors for modeling the activity. The resulting QSAR model has been validated internally and externally using CP-MLR and PLS. Further, the applicability domain analysis revealed the acceptable predictivity of the highest significant model.

The best QSAR model displays the r²Test value of 0.715, Q²LOO value of 0.797 and Q²L5O value of 0.809 and this model is used to predict novel compounds with high potency. Further docking study was executed using Autodock 4.2 against DPP-4 protein (PDB ID: 2RGU) that reflects the significant binding potential in newly proposed compounds.

From the results, four new congeners have been predicted and validated with good inhibitory activity against DPP-4. Present work reflects that with further optimization of these scaffolds, more selective, potent, and bioavailable DPP-4 inhibitors can be developed for the treatment of T2DM.