QSAR and Molecular Docking Studies of the Inhibitory Activity of Novel Heterocyclic GABA Analogues over GABA-AT

A Computational Method for the Binding Mode Prediction of COX-1 and COX-2 Inhibitors: Analyzing the Union of Coxibs, Oxicams, Propionic and Acetic Acids

Among the biological targets extensively investigated to improve inflammation and chronic inflammatory conditions, cyclooxygenase enzymes (COXs) occupy a prominent position. The inhibition of these enzymes, essential for mitigating inflammatory processes, is chiefly achieved through Non-Steroidal Anti-Inflammatory Drugs (NSAIDs). In this work, we introduce a novel method-based on computational molecular docking-that could aid in the structure-based design of new compounds or the description of the anti-inflammatory activity of already-tested compounds. For this, we used eight crystal complexes (four COX-1 and COX-2 each), and each pair had a specific NSAID: Celecoxib, Meloxicam, Ibuprofen, and Indomethacin. This selection was based on the ligand selectivity towards COX-1 or COX-2 and their binding mode. An interaction profile of each NSAID was compiled to detect the residues that are key for their binding mode, highlighting the interaction made by the Me group. Furthermore, we rigorously validated our models based on structural accuracy (RMSD < 1) and (R2 > 70) using eight NSAIDs and thirteen compounds with IC50 values for each enzyme. Therefore, this model can be used for the binding mode prediction of small and structurally rigid compounds that work as COX inhibitors or the prediction of new compounds that are designed by means of a structure-based approach.

Evaluation of the Usefulness of Topological Indices for Predicting Selected Physicochemical Properties of Bioactive Substances with Anti-Androgenic and Hypouricemic Activity

Due to the observed increase in the importance of computational methods in determining selected physicochemical parameters of biologically active compounds that are key to understanding their ADME/T profile, such as lipophilicity, there is a great need to work on accurate and precise in silico models based on some structural descriptors, such as topological indices for predicting lipophilicity of certain anti-androgenic and hypouricemic agents and their derivatives, for which the experimental lipophilicity parameter is not accurately described in the available literature, e.g., febuxostat, oxypurinol, ailanthone, abiraterone and teriflunomide. Therefore, the following topological indices were accurately calculated in this paper: Gutman (M, Mν), Randić (0χ, 1χ, 0χν, 1χν), Wiener (W), Rouvray-Crafford (R) and Pyka (A, 0B, 1B) for the selected anti-androgenic drugs (abiraterone, bicalutamide, flutamide, nilutamide, leflunomide, teriflunomide, ailanthone) and some hypouricemic compounds (allopurinol, oxypurinol, febuxostat). Linear regression analysis was used to create simple linear correlations between the newly calculated topological indices and some physicochemical parameters, including lipophilicity descriptors of the tested compounds (previously obtained by TLC and theoretical methods). Our studies confirmed the usefulness of the obtained linear regression equations based on topological indices to predict ADME/T important parameters, such as lipophilicity descriptors of tested compounds with anti-androgenic and hypouricemic effects. The proposed calculation method based on topological indices is fast, easy to use and avoids valuable and lengthy laboratory experiments required in the case of experimental ADME/T studies.

Pharmacophore Modeling and 3D-QSAR Study of Indole and Isatin Derivatives as Antiamyloidogenic Agents Targeting Alzheimer's Disease

Thirty-six novel indole-containing compounds, mainly 3-(2-phenylhydrazono) isatins and structurally related 1H-indole-3-carbaldehyde derivatives, were synthesized and assayed as inhibitors of beta amyloid (Aβ) aggregation, a hallmark of pathophysiology of Alzheimer’s disease. The newly synthesized molecules spanned their IC₅₀ values from sub- to two-digit micromolar range, bearing further information into structure-activity relationships. Some of the new compounds showed interesting multitarget activity, by inhibiting monoamine oxidases A and B. A cell-based assay in tau overexpressing bacterial cells disclosed a promising additional activity of some derivatives against tau aggregation. The accumulated data of either about ninety published and thirty-six newly synthesized molecules were used to generate a pharmacophore hypothesis of antiamyloidogenic activity exerted in a wide range of potencies, satisfactorily discriminating the ‘active’ compounds from the ‘inactive’ (poorly active) ones. An atom-based 3D-QSAR model was also derived for about 80% of ‘active’ compounds, i.e., those achieving finite IC₅₀ values lower than 100 μM. The 3D-QSAR model (encompassing 4 PLS factors), featuring acceptable predictive statistics either in the training set (n = 45, q² = 0.596) and in the external test set (n = 14, r²_ext = 0.695), usefully complemented the pharmacophore model by identifying the physicochemical features mainly correlated with the Aβ anti-aggregating potency of the indole and isatin derivatives studied herein.