Evaluating solubility, stability, and inclusion complexation of oxyresveratrol with various ß-cyclodextrin derivatives using advanced computational techniques and experimental validation.

Oxyresveratrol (OXY), a natural stilbenoid in mulberry fruits, is known for its diverse pharmacological properties. However, its clinical use is hindered by low water solubility and limited bioavailability. In the present study, the inclusion complexes of OXY with ß-cyclodextrin (ßCD) and its three analogs, dimethyl-ß-cyclodextrin (DMßCD), hydroxypropyl-ß-cyclodextrin (HPßCD) and sulfobutylether-ß-cyclodextrin (SBEßCD), were investigated using in silico and in vitro studies. Molecular docking revealed two binding orientations of OXY, namely, 4',6'-dihydroxyphenyl (A-form) and 5,7-benzenediol ring (B-form). Molecular Dynamics simulations suggested the formation of inclusion complexes with ßCDs through two distinct orientations, with OXY/SBEßCD exhibiting maximum atom contacts and the lowest solvent-exposed area in the hydrophobic cavity. These results corresponded well with the highest binding affinity observed in OXY/SBEßCD when assessed using the MM/GBSA method. Beyond traditional simulation methods, Ligand-binding Parallel Cascade Selection Molecular Dynamics method was employed to investigate how the drug enters and accommodates within the hydrophobic cavity. The in silico results aligned with stability constants: SBEßCD (2060 M-1), HPßCD (1860 M-1), DMßCD (1700 M-1), and ßCD (1420 M-1). All complexes exhibited a 1:1 binding mode (AL type), with SBEßCD enhancing OXY solubility (25-fold). SEM micrographs, DSC thermograms, FT-IR and 1H NMR spectra confirm the inclusion complex formation, revealing novel surface morphologies, distinctive thermal behaviors, and new peaks. Notably, the inhibitory impact on the proliferation of breast cancer cell lines, MCF-7, exhibited by inclusion complexes particularly OXY/DMßCD, OXY/HPßCD, and OXY/SBEßCD were markedly superior compared to that of OXY alone.

Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on designing organoselenium-based inhibitors targeting the SARS-CoV-2 main protease (Mpro). The ligand-binding pathway sampling method based on parallel cascade selection molecular dynamics (LB-PaCS-MD) simulations was employed to elucidate plausible paths and conformations of ebselen, a synthetic organoselenium drug, within the Mpro catalytic site. Ebselen effectively engaged the active site, adopting proximity to H41 and interacting through the benzoisoselenazole ring in a π-π T-shaped arrangement, with an additional π-sulfur interaction with C145. In addition, the ligand-based drug design using the QSAR with GFA-MLR, RF, and ANN models were employed for biological activity prediction. The QSAR-ANN model showed robust statistical performance, with an r2training exceeding 0.98 and an RMSEtest of 0.21, indicating its suitability for predicting biological activities. Integration the ANN model with the LB-PaCS-MD insights enabled the rational design of novel compounds anchored in the ebselen core structure, identifying promising candidates with favorable predicted IC50 values. The designed compounds exhibited suitable drug-like characteristics and adopted an active conformation similar to ebselen, inhibiting Mpro function. These findings represent a synergistic approach merging ligand and structure-based drug design; with the potential to guide experimental synthesis and enzyme assay testing.