The occurrence, persistence, and accumulation of antibiotics and non-steroidal anti-inflammatory drugs (NSAIDs) represent a new environmental problem due to their harmful effects on human and aquatic life. A suitable absorbent for a particular type of pollutant does not necessarily absorb other types of compounds, so knowing the compatibility between a particular pollutant and a potential absorbent before experimentation seems to be fundamental. In this work, the molecular interactions between some pharmaceuticals (amoxicillin, ibuprofen, and tetracycline derivatives) with two potential absorbers, chitosan and graphene oxide models (pyrene, GO-1, and coronene, GO-2), were studied using the ωB97X-D/6-311G(2d,p) level of theory. The energetic interaction order found was amoxicillin/chitosan > amoxicillin/GO-1 > amoxicillin/GO-2 > ibuprofen/chitosan > ibuprofen/GO-2 > ibuprofen/GO-1, the negative sign for the interaction energy in all complex formations confirms good compatibility, while the size of E_int between 24–34 kcal/mol indicates physisorption processes. Moreover, the free energies of complex formation were negative, confirming the spontaneity of the processes. The larger interaction of amoxicillin Gos, compared to ibuprofen Gos, is consistent with previously reported experimental results, demonstrating the exceptional predictability of these methods. The second-order perturbation theory analysis shows that the amoxicillin complexes are mainly driven by hydrogen bonds, while van der Waals interactions with chitosan and hydrophobic interactions with graphene oxides are modelled for the ibuprofen complexes. Energy decomposition analysis (EDA) shows that electrostatic energy is a major contributor to the stabilization energy in all cases. The results obtained in this work promote the use of graphene oxides and chitosan as potential adsorbents for the removal of these emerging pollutants from water.

Understanding the non-covalent interactions in host-guest complexes is crucial to their stability, design and applications. Here, we use density functional theory to compare the ability of β-cyclodextrin (β-CD) and heptakis(2,6-di-O-methyl)-β-cyclodextrin (DM-β-CD) to encapsulate the model guest phenol. For both macrocycles, we quantify the intramolecular interactions before and after the formation of the complex, as well as the intermolecular host-guest and host-host dimer interactions. These are individually classified as van der Waals interactions or hydrogen bonds, respectively. The results show a stronger intramolecular binding energy of β-CD, with the absolute difference being −5.53 kcal/mol relative to DM-β-CD. Consequently, the intermolecular interactions of both cyclodextrins with phenol are affected, such that the free binding energy calculated for the DM-β-CD/phenol complex (−5.23 kcal/mol) is ≈50% more negative than for the complex with β-CD (−2.62 kcal/mol). The latter is in excellent agreement with the experimental data (−2.69 kcal/mol), which validates the level of theory (B97-3c) used. Taken together, the methylation of β-CD increases the stability of the host-guest complex with the here studied guest phenol through stronger van der Waals interactions and hydrogen bonds. We attribute this to the disruption of the hydrogen bond network in the primary face of β-CD upon methylation, which influences the flexibility of the host toward the guest as well as the strength of the intermolecular interactions. Our work provides fundamental insights into the impact of different non-covalent interactions on host-guest stability, and we suggest that this theoretical framework can be adapted to other host-guest complexes to evaluate and quantify their non-covalent interactions.

A series of aromatic Schiff bases, featuring 7-diethylamino-coumarin and with five different substituents at an adjacent phenyl ring, were synthesized and characterized. With the aim of assessing the stability of these dyes in acidic medium, their hydrolysis reactions were kinetically studied in the absence and presence of the macrocycle cucurbit[7]uril (CB[7]). Our results are consistent with a model containing three different forms of substrates (un-, mono-, and diprotonated) and three parallel reaction pathways. The pK_a values and the rate constants were estimated and discussed in terms of the presence of a hydroxyl group at the ortho position and electron-releasing groups on the phenyl ring of the dyes. The kinetic study in the presence of CB[7] led to two different behaviors. Promotion of the reaction by CB[7] was observed for the hydrolysis of the Schiff bases containing only one coordination site toward the macrocycle. Conversely, an inhibitor effect was observed for the hydrolysis of a Schiff base with two coordination sites toward CB[7]. The latter effect could be explained with a model as a function of a prototropic tautomeric equilibrium and the formation of a 2:1 host/guest complex, which prevents the attack of water. Therefore, the kinetic results demonstrated a supramolecular control of the macrocycle toward the reactivity and stability of 7-diethylaminocoumarin Schiff bases in acidic medium.

Background/Objectives: Acute myeloid leukemia (AML) presents significant therapeutic challenges, particularly in cases driven by mutations in the FLT3 tyrosine kinase. This study aimed to develop a robust and user-friendly machine learning-based quantitative structure–activity relationship (QSAR) model to predict the inhibitory potency (pIC₅₀ values) of FLT3 inhibitors, addressing the limitations of previous models in dataset size, diversity, and predictive accuracy. Methods: Using a dataset which was 14 times larger than those employed in prior studies (1350 compounds with 1269 molecular descriptors), we trained a random forest regressor, chosen due to its superior predictive performance and resistance to overfitting. Rigorous internal validation via leave-one-out and 10-fold cross-validation yielded ${\mathrm{Q}}^2$ values of 0.926 and 0.922, respectively, while external validation on 270 independent compounds resulted in an R² value of 0.941 with a standard deviation of 0.237. Results: Key molecular descriptors influencing the inhibitor potency were identified, thereby improving the interpretability of structural requirements. Additionally, a user-friendly computational tool was developed to enable rapid prediction of pIC₅₀ values and facilitate ligand-based virtual screening, leading to the identification of promising FLT3 inhibitors. Conclusions: These results represent a significant advancement in the field of FLT3 inhibitor discovery, offering a reliable, practical, and efficient approach for early-stage drug development, potentially accelerating the creation of targeted therapies for AML.

In this work, the minimum energy structures of 22 4-pyridone derivatives have been optimized at Density Functional Theory level, and several quantum molecular, including electronic and thermodynamic descriptors, were computed for these substrates in order to obtain a statistical and meaningful QSAR equation. In this sense, by using multiple linear regressions, five mathematical models have been obtained. The best model with only four descriptors (r² = 0.86, Q² = 0.92, S.E.P = 0.38) was validated by the leave-one-out cross-validation method. The antimalarial activity can be explained by the combination of the four mentioned descriptors e.g., electronic potential, dipolar momentum, partition coefficient and molar refractivity. The statistical parameters of this model suggest that it is robust enough to predict the antimalarial activity of new possible compounds; consequently, three small chemical modifications into the structural core of these compounds were performed specifically on the most active compound of the series (compound 13). These three new suggested compounds were leveled as 13A, 13B and 13C, and the predicted biological antimalarial activity is 0.02 µM, 0.03 µM, and 0.07 µM, respectively. In order to complement these results focused on the possible action mechanism of the substrates, a docking simulation was included for these new structures as well as for the compound 13 and the docking scores (binding affinity) obtained for the interaction of these substrates with the cytochrome bc1, were −7.5, −7.2, −6.9 and −7.5 kcal/mol for 13A, 13B, 13C and compound 13, respectively, which suggests that these compounds are good candidates for its biological application in this illness.