METHODS: Ninety human molars with carious extension up to the middle third of occlusal dentin were included. The teeth were then arbitrarily allocated into three groups based on the type of surface conditioning received (n = 30) Group 1 (PA), Group 2 (FS laser), and Group 3 (Ery PS). Ten samples from each group underwent Ra analysis using a stylus profiler. Twenty samples from each cohort were distributed into two subcategories based on the application of unmodified EA (A) and Sep-infiltrated EA (B). Composite restoration was built followed by SBS and failure mode analysis. Scanning electron microscopy and Energy dispersive X-ray EDX were assessed of sepiolite NPs. Degree of conversion (DC) and rheological analysis of the modified adhesive and unmodified adhesive were also performed. One-way analysis of variance (ANOVA) and the Tukey post hoc test were employed to conduct comparisons between the different groups.

RESULTS: The highest score of Ra and bond strength were displayed by Group 1B (PA + Sep-NPs filled EA) (17.32 ± 1.43 MPa) samples. Nevertheless, the lowest values were established by Group 3A (Ery-PS + EA) (13.45 ± 0.80 MPa) treated teeth. An increase in Ra resulted in a rise in SBS.DC decreased with the incorporation of 1 % Sep-NPs in EA compared to unmodified EA.

Materials and Methods: A library of 120 phytochemical ligands was prepared, from which 5 were selected considering their absorption, distribution, metabolism, and excretion (ADMET) and quantitative structure-activity relationship (QSAR) profiles. The protein active sites and belonging quantum tunnels were defined to conduct supramolecular docking of the aforementioned ligands. The hydrogen bond formation and hydrophobic interactions between the ligand-receptor complexes were studied following the molecular docking steps. A comprehensive molecular dynamic simulation (MDS) was conducted for each of the ligand-receptor complexes to figure out the values - root mean square deviation (RMSD) (Å), root mean square fluctuation (RMSF) (Å), H-bonds, Cα, solvent accessible surface area (SASA) (Å2), molecular surface area (MolSA) (Å2), Rg (nm), and polar surface area (PSA) (Å). Finally, computational programming and algorithms were used to interpret the dynamic simulation outputs into their graphical quantitative forms.

Results: ADMET and QSAR profiles revealed that the most active candidates from the library to be used were apigenin, isovitexin, piperolactam A, and quercetin as test ligands, whereas serpentine as the control. Based on the binding affinities of supramolecular docking and the parameters of molecular dynamic simulation, the strength of the test ligands can be classified as isovitexin > quercetin > piperolactam A > apigenin when complexed with the hACE2 receptor. Surprisingly, serpentine showed lower affinity (-8.6 kcal/mol) than that of isovitexin (-9.9 kcal/mol) and quercetin (-8.9 kcal/mol). The MDS analysis revealed all ligands except isovitexin having a value lower than 2.5 Ǻ. All the test ligands exhibited acceptable fluctuation ranges of RMSD (Å), RMSF (Å), H-bonds, Cα, SASA (Å2), MolSA (Å2), Rg (nm), and PSA (Å) values.