Search Results (5)

Selective androgen receptor modulators (SARMs) are commonly described as tissue-selective anabolic agents, yet the extent to which this selectivity is reflected at the level of receptor-binding energetics remains uncertain. This study evaluated the receptor interaction profiles of the steroidal SARM YK11 and the nonsteroidal SARM ostarine across five steroid hormone nuclear receptors. Flexible molecular docking was performed with AutoDock 4.2 against the androgen (AR), estrogen (ER), progesterone (PR), glucocorticoid (GR), and mineralocorticoid (MR) receptors, using testosterone, estradiol, progesterone, cortisol, and aldosterone as endogenous reference ligands. Binding free energy, docking-derived inhibition constants, intermolecular interaction energies, conformational sampling, and two-dimensional interaction maps were analyzed. Ostarine showed favorable binding across all receptor systems, with binding energies ranging from −10.42 to −12.05 kcal/mol and no pronounced energetic preference for the androgen receptor. YK11 displayed stronger predicted binding, particularly toward the glucocorticoid, progesterone, and androgen receptors, with a docking energy trend of GR > PR > AR > MR > ER. Interaction analysis revealed conserved polar anchoring residues across receptor pockets, together with scaffold-specific contacts that may explain cross-receptor compatibility. These findings indicate that, within the AutoDock 4.2 flexible docking framework applied in this study, docking-derived binding energies primarily describe thermodynamic compatibility with nuclear receptor ligand-binding domains and should not be interpreted as direct predictors of functional SARM tissue selectivity. The observed discordance between predicted receptor affinity and the established tissue-selective pharmacology of ostarine highlights the need for caution when using single-method docking workflows to infer selectivity among closely related steroid hormone receptors. The novelty of this study lies in demonstrating, using a defined AutoDock 4.2-based comparative protocol, that receptor-binding energetics alone do not recapitulate the functional tissue-selective behavior attributed to SARMs. Full article

The present study was designed to evaluate the in vitro and in silico potential of the Schiff bases (Z)-4-ethoxy-N-((5-nitrothiophen-2-yl)methylene)benzenamine (1) and (Z)-2,4-diiodo-6-((2-methyl-3-nitrophenylimino)methyl)phenol (2). These Schiff bases were synthesized according to a reported method using ethanol as a solvent, and each reaction was monitored on a TLC until completion of the reaction. The structures of both compounds were elucidated using spectroscopic techniques such as UV–Vis, FTIR, ¹H NMR and ¹³C NMR. Molecular structure was determined using single-crystal XRD, which revealed that compounds 1 and 2 were monoclinic and triclinic, respectively. Hirshfeld surface analysis (HS) and 2D fingerprint plots were used to determine the intermolecular interactions along the contact contribution in the crystalline molecules. The structures of both compounds were optimized through a hybrid functional method B3LYP using the 6-31G(d,p) basis set, and various structural parameters were studied. The experimental and theoretical parameters (bond angle and bond length) of the compounds were compared with each other and are in close agreement. The in vitro esterase potential of the synthesized compounds was checked using a spectrophotometric model, while in silico molecular docking studies were performed with AutoDock against two enzymes of the esterase family. The docking studies and the in vitro assessment predicted that such molecules could be used as enzyme inhibitors against the tested enzymes: acetylcholine esterase (AChE) and butyrylcholine esterase (BChE). Full article

The neuronal nicotinic acetylcholine receptors (nAChRs) belong to the ligand-gated ion channel (GLIC) group, presenting a crucial role in several biological processes and neuronal disorders. The α4β2 and α7 nAChRs are the most abundant in the central nervous system (CNS), being involved in challenging diseases such as epilepsy, Alzheimer’s disease, schizophrenia, and anxiety disorder, as well as alcohol and nicotine dependencies. In addition, in silico-based strategies may contribute to revealing new insights into drug design and virtual screening to find new drug candidates to treat CNS disorders. In this context, the pharmacophore maps were constructed and validated for the orthosteric sites of α4β2 and α7 nAChRs, through a docking-based Comparative Intermolecular Contacts Analysis (dbCICA). In this sense, bioactive ligands were retrieved from the literature for each receptor. A molecular docking protocol was developed for all ligands in both receptors by using GOLD software, considering GoldScore, ChemScore, ASP, and ChemPLP scoring functions. Output GOLD results were post-processed through dbCICA to identify critical contacts involved in protein-ligand interactions. Moreover, Crossminer software was used to construct a pharmacophoric map based on the most well-behaved ligands and negative contacts from the dbCICA model for each receptor. Both pharmacophore maps were validated by using a ROC curve. The results revealed important features for the ligands, such as the presence of hydrophobic regions, a planar ring, and hydrogen bond donor and acceptor atoms for α4β2. Parallelly, a non-planar ring region was identified for α7. These results can enable fragment-based drug design (FBDD) strategies, such as fragment growing, linking, and merging, allowing an increase in the activity of known fragments. Thus, our results can contribute to a further understanding of structural subunits presenting the potential for key ligand-receptor interactions, favoring the search in molecular databases and the design of novel ligands. Full article

Natural products based on imidazole scaffolds have inspired the discovery of a wide variety of bioactive compounds. Herein, a series of imidazoles that act as competitive and potent cruzain inhibitors was investigated using a combination of ligand- and structure-based drug design strategies. Quantitative structure–activity relationships (QSARs) were generated along with the investigation of enzyme–inhibitor molecular interactions. Predictive hologram QSAR (HQSAR, r²_pred = 0.80) and AutoQSAR (q² = 0.90) models were built, and key structural properties that underpin cruzain inhibition were identified. Moreover, comparative molecular field analysis (CoMFA, r²_pred = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r²_pred = 0.73) revealed 3D molecular features that strongly affect the activity of the inhibitors. These findings were examined along with molecular docking studies and were highly compatible with the intermolecular contacts that take place between cruzain and the inhibitors. The results gathered herein revealed the main factors that determine the activity of the imidazoles studied and provide novel knowledge for the design of improved cruzain inhibitors. Full article

Aurora-A kinase plays a central role in mitosis, where aberrant activation contributes to cancer by promoting cell cycle progression, genomic instability, epithelial-mesenchymal transition, and cancer stemness. Aurora-A kinase inhibitors have shown encouraging results in clinical trials but have not gained Food and Drug Administration (FDA) approval. An innovative computational workflow named Docking-based Comparative Intermolecular Contacts Analysis (dbCICA) was applied—aiming to identify novel Aurora-A kinase inhibitors—using seventy-nine reported Aurora-A kinase inhibitors to specify the best possible docking settings needed to fit into the active-site binding pocket of Aurora-A kinase crystal structure, in a process that only potent ligands contact critical binding-site spots, distinct from those occupied by less-active ligands. Optimal dbCICA models were transformed into two corresponding pharmacophores. The optimal one, in capturing active hits and discarding inactive ones, validated by receiver operating characteristic analysis, was used as a virtual in-silico search query for screening new molecules from the National Cancer Institute database. A fluorescence resonance energy transfer (FRET)-based assay was used to assess the activity of captured molecules and five promising Aurora-A kinase inhibitors were identified. The activity was next validated using a cell culture anti-proliferative assay (MTT) and revealed a most potent lead 85(NCI 14040) molecule after 72 h of incubation, scoring IC₅₀ values of 3.5–11.0 μM against PANC1 (pancreas), PC-3 (prostate), T-47D and MDA-MB-231 (breast)cancer cells, and showing favorable safety profiles (27.5 μM IC₅₀ on fibroblasts). Our results provide new clues for further development of Aurora-A kinase inhibitors as anticancer molecules. Full article