Caffeine is a widely consumed psychoactive compound known to influence drug metabolism and efficacy through interactions with key enzymes such as cytochrome P450 3A4 (CYP3A4). This study investigates the molecular impact of caffeine on the binding behavior of imatinib, a first-line BCR-ABL tyrosine kinase inhibitor, using molecular docking simulations. Structural optimization and lipophilicity analyses were conducted using HyperChem, while docking was performed with HEX software (Version 8.0.0) against the CYP3A4 receptor (PDB ID: 1W0E). Two administration scenarios were evaluated: concurrent caffeine–imatinib complex formation and sequential administration with caffeine pre-bound to CYP3A4. The caffeine–imatinib complex exhibited a predicted increase in lipophilicity (logP = 3.09) compared to imatinib alone (logP = −1.29), which may indicate the potential for enhanced membrane permeability and tissue distribution. Docking simulations revealed stronger binding affinity of the complex to CYP3A4 (−350.53 kcal/mol) compared to individual compounds, and improved imatinib binding when CYP3A4 was pre-complexed with caffeine (−294.14 kcal/mol vs. −288.19 kcal/mol). Frontier molecular orbital analysis indicated increased reactivity of the complex (ΔE = 7.74 eV), supporting the hypothesis of altered pharmacodynamic behavior. These findings suggest that caffeine may modulate imatinib’s metabolic profile and therapeutic efficacy by enhancing receptor binding and altering drug distribution. The study underscores the importance of evaluating dietary components during drug development and therapeutic planning, particularly for agents metabolized by CYP3A4.

The aim of this study was to investigate the molecular interactions of heparin, diclofenac, and their supramolecular complexes with cyclooxygenase enzymes (COX-1 and COX-2) using computational docking techniques. Diclofenac is a widely used nonsteroidal anti-inflammatory drug (NSAID) that inhibits COX isoforms, whereas heparin is a polyanionic glycosaminoglycan with established anticoagulant and emerging anti-inflammatory properties. Supramolecular association between these agents may modulate their physicochemical behavior and target engagement. Molecular modeling, dual-drug docking, and molecular dynamics (MD) simulations were employed to characterize the interactions of heparin, diclofenac, and pre-formed heparin–diclofenac complexes with COX-1 and COX-2. Geometry optimization and lipophilicity (logP) estimates were obtained using HyperChem, while protein–ligand docking was performed in HEX using crystallographic COX structures from the Protein Data Bank. Docking poses were analyzed in Chimera, and selected complexes were refined through short MD simulations. Pre-formed heparin–diclofenac assemblies exhibited markedly enhanced docking scores toward both COX isoforms compared with single ligands. Binding orientation strongly influenced affinity: for COX-1, the heparin–diclofenac configuration yielded the most favorable interaction, whereas for COX-2 the diclofenac–heparin configuration was preferred. Both assemblies adopted binding modes distinct from free diclofenac, suggesting cooperative electrostatic and hydrophobic contacts at the enzyme surface. Supramolecular complexation also altered calculated logP values relative to the individual compounds. MD simulations supported the relative stability of the top-ranked complex–COX assemblies. These findings indicate that heparin–diclofenac assemblies may enhance and reorganize predicted COX interactions in a configuration-dependent manner and illustrate the utility of dual-drug docking for modeling potential synergistic effects. Such insights may inform the design of localized or topical formulations, potentially incorporating non-anticoagulant heparin derivatives, to achieve effective COX inhibition with reduced systemic exposure. However, the results rely on simplified heparin fragments, legacy docking tools, and short MD simulations, and should therefore be interpreted qualitatively. Experimental studies will be essential to confirm whether such supramolecular assemblies form under physiological conditions and whether they influence COX inhibition in vivo.

Combination analgesic therapy is commonly used to improve pain control, yet conventional molecular docking approaches typically evaluate individual ligands and provide limited insight into potential intermolecular associations between co-administered drugs. In this study, paracetamol, codeine, and their proposed 1:1 and 2:1 non-covalent assemblies were investigated using lipophilicity analysis, molecular docking, short molecular dynamics relaxation, electrostatic potential surface mapping, and HOMO–LUMO analysis. Docking simulations were performed against cyclooxygenase-1 (COX-1), cyclooxygenase-2 (COX-2), and the μ-opioid receptor (MOR). The proposed assemblies produced docking scores that differed from those of the individual compounds, with the most pronounced differences observed for the cyclooxygenase targets. The 2:1 assemblies generally exhibited the most favorable docking scores, whereas the predicted interaction profiles at MOR appeared to be more dependent on molecular orientation. Molecular dynamics relaxation and electronic structure analyses further revealed differences in the energetic and electronic characteristics of the investigated configurations. These findings support the theoretical feasibility of distinct interaction patterns among the proposed paracetamol–codeine assemblies within the applied computational framework. However, the reported docking scores represent relative computational values rather than experimentally validated binding affinities, and the short-timescale molecular dynamics simulations provide only preliminary information regarding conformational stability. Furthermore, the existence and biological relevance of the proposed assemblies under physiological conditions remain to be established. This study provides a computational basis for future investigations of intermolecular associations in multicomponent drug systems.

The aim of this study is to investigate the molecular interactions of heparin, diclofenac, and their complexes with cyclooxygenase enzymes (COX-1 and COX-2) using computational docking techniques. Molecular modeling and docking simulations were performed with HyperChem and HEX software, utilizing receptor structures from the Protein Data Bank (PDB). Binding energies and lipophilicity (logP) values were analyzed to evaluate the interaction strength and hydrophobic properties of the complexes compared to the individual drugs. The results demonstrated that both the heparin-diclofenac and diclofenac-heparin complexes exhibit stronger binding affinities to COX-1 and COX-2 than the drugs alone. Notably, the heparin-diclofenac complex showed the strongest binding, sug-gesting that molecular orientation significantly influences interaction efficiency. Further-more, differences in binding behavior between COX-1 and COX-2 were observed, likely due to structural variations in their active sites, with COX-2 providing a more favorable environment for complex interactions. The analysis also highlighted the impact of lipophilicity on binding properties, emphasizing the relevance of physicochemical characteristics in drug-receptor dynamics. These findings suggest that the formation of heparin-diclofenac complexes may enhance COX inhibition, presenting a potential strategy for developing more effective pain management therapies.

Glycogen synthase kinase-3 is a fascinating enzyme involved in a series of physiological processes, and its activity is associated with the pathological features of various diseases, such as type 2 diabetes, Alzheimer's disease, chronic inflammation, cancer, and bipolar affective disorder. GSK-3 inhibitors are currently being tested for their therapeutic effects on these diseases. In this work, the inhibition of GSK-3β by aloisines is investigated by structure-activity correlation studies, the best model obtained being characterized by R2 = 0.8865. The identification of the molecular fragments that contribute most to the formation of biological activity is carried out using fingerprint descriptors, such as the electronegativity of the OMO/UMO quantum molecular states. For an even better understanding of the relationship between chemical structure and observed biological activity, an aloisine/GSK-3β complex structure was obtained using molecular docking. The two types of studies (correlation and docking) are in good and complementary agreement. Therefore, our study suggests that the aloisine molecules are potent and selective for GSK-3β.