The objective of this study was to synthesize thiazoline-2-thione derivatives (1a, 2b, 3c and 4d) and examine their anti-inflammatory properties as potential alternatives to Aspirin (NSAID), which is known for its side effects, including liver damage. The study employed a multifaceted approach that integrated in vitro assays, molecular docking, ADMET predictions, molecular dynamics simulations (300 ns for each system) and detailed DFT calculations. These four molecules were initially evaluated for their effectiveness in inhibiting the denaturation of bovine serum albumin (BSA), a key indicator of their potential anti-inflammatory activity. The results show that 4d displayed notable inhibitory potential against BSA denaturation, with an IC₅₀ value of 21.9 µg/mL, outperforming the efficacy of Aspirin (22 µg/mL). In comparison, 3c exhibited an IC₅₀ value of 31.7 µg/mL. Molecular docking studies with the BSA active site revealed that 4d and 3c had the highest binding affinities, with binding energies (∆G) of −5.274 and −4.731 kcal.mol⁻¹, respectively. Aspirin showed a ∆G of −4.641 kcal.mol⁻¹. These findings suggest that 4d and 3c molecules exhibit stronger interactions with BSA, indicating superior anti-inflammatory activity compared to Aspirin. In addition, molecular dynamics simulations, cross-dynamic correlation matrix (DCCM), free energy landscape (FEL), MM-PBSA and detailed DFT calculations provided further evidence that 4d formed stable molecular interactions with the BSA receptor. These analyses highlighted the strong binding stability of 4d, indicating that it maintains consistent interactions over time. The results also suggested that 4d exhibits favorable energy profiles, good pharmacokinetic features and optimal molecular behavior within the BSA active site. Finally, the results of this study are promising for the development of new anti-inflammatory drugs, highlighting potential compounds that could offer effective and safer alternatives to existing treatments.

Background/Objectives: RNA polymerase (NS5B), serves as a crucial target for pharmaceutical interventions aimed at combating the hepatitis C virus (HCV), which poses significant health challenges worldwide. The present research endeavors to explore and implement a variety of advanced molecular modeling techniques that aim to create and identify innovative and highly effective inhibitors that specifically target the RNA polymerase enzyme. Methods: In this study, a QSAR investigation was carried out on a set of thirty-eight isothiazole derivatives targeting NS5B inhibition and thus hepatitis C virus (HCV) treatment. The research methodology made use of various statistical techniques including multiple linear regression (MLR) and artificial neural networks (ANNs) to develop satisfactory models in terms of internal and external validation parameters, indicating their reliability in predicting the activity of new inhibitors. Accordingly, a series of potent NS5B inhibitors is designed, and their inhibitory potential is confirmed through molecular docking simulations. Results: These simulations showed that the interactions between these inhibitors and the active site 221 binding pocket of the NS5B protein are hydrophobic and hydrogen bond interactions, as well as carbon–hydrogen bonds and electrostatic interactions. Additionally, these newly formulated compounds displayed favorable ADMET characteristics, with molecular dynamics investigations revealing a stable energetic state and dynamic equilibrium. Conclusions: Our work highlights the importance of NS5B inhibition for the treatment of HCV.

In this study, we used Principal Component Analysis (PCA) to evaluate the physical and operational properties of palladium (Pd)-based membrane composites, focusing on variables like temperature, differential pressure (ΔP), thickness, hydrogen (H₂) permeability, and H₂ flux. The analysis revealed that the first two principal components explained 53.16% of the total variance, indicating moderate explanatory power. Interdependencies were observed among temperature, thickness, H₂ flux, and H₂ permeability, while ΔP functioned independently. This study found similarities among membranes, such as eco-friendly chitosan-based membranes, which performed comparably to conventional options like Pd–PSS and Pd–Cu/αAl₂O₃. Overall, PCA proved to be an invaluable tool for uncovering hidden patterns, optimizing experimental processes, and deepening the understanding of Pd-based membranes. The findings underscore PCA’s potential to enhance material performance and promote sustainable alternatives, with practical benefits for advancing hydrogen separation technologies. This study illustrates how data-driven approaches can refine material analysis and drive innovation in membrane design.