Search Results (168)

A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis incorporating ligand-receptor docking alignment and molecular dynamic (MD) simulations was conducted to elucidate the potent inhibitory effects of a series of benzamide derivatives on histone deacetylase 1 (HDAC1). A comparison between ligand-based (LB) and receptor-based (RB) 3D-QSAR models using molecular docking alignment produced statistically significant results. Steric and electrostatic contour maps provided insights into the interactions surrounding the benzamide ring, revealing that an increase in electron density enhances inhibitory activity. Furthermore, MD simulations were employed to investigate protein-ligand interactions in greater detail, yielding outcomes consistent with those from 3D-QSAR and molecular docking studies. This integrated approach of molecular docking, 3D-QSAR, and energy decomposition analysis derived from MD simulations, provides a valuable framework for the rational design of more potent HDAC1 inhibitors, facilitating the synthesis of highly effective anti-tumor compounds based on benzamide scaffolds. Full article

Dopamine D2-like receptors, including D2, D3, and D4, are members of the aminergic G protein-coupled receptor (GPCR) family and are targets for neurological disorders. The development of subtype selective ligands is important for enhanced therapeutics and reduced side effects; however, it is challenging to design and develop selective ligands owing to the high degree of sequence homology among D2-like subtypes. To gain insight into the structural basis of subtype selectivity of piperazinylalkyl pyrazole/isoxazole analogs for D2-like dopamine receptors, we carried out 3D quantitative structure–activity relationship (3D-QSAR) and molecular docking studies. The 3D-QSAR models for the D2, D3, and D4 subtypes showed robust correlation coefficients (r²) of 0.960, 0.912, and 0.946, as well as reliable predictive values (Q²) of 0.511, 0.808, and 0.560, respectively. Contour map analysis revealed key structural determinants for ligand activity, highlighting the distinct steric and electrostatic requirements for each subtype. These findings were further rationalized by molecular docking studies, which confirmed that interactions with non-conserved residues modulate binding affinity. Crucially, our analysis identified a critical structural basis for D4 subtype selectivity. This selectivity is attributed to a spatial constraint within the hydrophobic pocket formed by TMs 3, 5, and 6. This constraint restricts the orientation of bulky substituents on the 4-phenylpiperazine moiety. These findings provide actionable structural insights for the rational design of next-generation subtype-selective antagonists for D2-like dopamine receptors. Full article

Cathepsin L (CatL) is a critical protease involved in cleaving the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), facilitating viral entry into host cells. Inhibition of CatL is essential for preventing SARS-CoV-2 cell entry, making it a potential therapeutic target for drug development. Six QSAR models were established to predict the inhibitory activity (expressed as IC₅₀ values) of candidate compounds against CatL. These models were developed using statistical method heuristic methods (HMs), the evolutionary algorithm gene expression programming (GEP), and the ensemble method random forest (RF), along with the kernel-based machine learning algorithm support vector regression (SVR) configured with various kernels: radial basis function (RBF), linear-RBF hybrid (LMIX2-SVR), and linear-RBF-polynomial hybrid (LMIX3-SVR). The particle swarm optimization algorithm was applied to optimize multi-parameter SVM models, ensuring low complexity and fast convergence. The properties of novel CatL inhibitors were explored through molecular docking analysis. The LMIX3-SVR model exhibited the best performance, with an $R^2$ of 0.9676 and 0.9632 for the training set and test set and RMSE values of 0.0834 and 0.0322. Five-fold cross-validation $R_{5-fold}^2$ = 0.9043 and leave-one-out cross-validation $R_{loo}^2$ = 0.9525 demonstrated the strong prediction ability and robustness of the model, which fully proved the correctness of the five selected descriptors. Based on these results, the IC₅₀ values of 578 newly designed compounds were predicted using the HM model, and the top five candidate compounds with the best physicochemical properties were further verified by Property Explorer Applet (PEA). The LMIX3-SVR model significantly advances QSAR modeling for drug discovery, providing a robust tool for designing and screening new drug molecules. This study contributes to the identification of novel CatL inhibitors, which aids in the development of effective therapeutics for SARS-CoV-2. Full article

Hormone-dependent breast cancer, particularly in its treatment-resistant forms, remains a significant therapeutic challenge. In this study, we applied a fully computational strategy to design steroid-based compounds capable of simultaneously targeting three key receptors involved in disease progression: progesterone receptor (PR), estrogen receptor alpha (ER-α), and HER2. Using a robust 3D-QSAR model (R² = 0.86; Q²_LOO = 0.86) built from 52 steroidal structures, we identified molecular features associated with high anticancer potential, specifically increased polarizability and reduced electronegativity. From a virtual library of 271 DFT-optimized analogs, 31 compounds were selected based on predicted potency (pIC₅₀ > 7.0) and screened via molecular docking against PR (PDB 2W8Y), HER2 (PDB 7JXH), and ER-α (PDB 6VJD). Seven candidates showed strong binding affinities (ΔG ≤ −9 kcal/mol for at least two targets), with Estero-255 emerging as the most promising. This compound demonstrated excellent conformational stability, a robust hydrogen-bonding network, and consistent multitarget engagement. Molecular dynamics simulations over 100 nanoseconds confirmed the structural integrity of the top ligands, with low RMSD values, compact radii of gyration, and stable binding energy profiles. Key interactions included hydrophobic contacts, π–π stacking, halogen–π interactions, and classical hydrogen bonds with conserved residues across all three targets. These findings highlight Estero-255, alongside Estero-261 and Estero-264, as strong multitarget candidates for further development. By potentially disrupting the PI3K/AKT/mTOR signaling pathway, these compounds offer a promising strategy for overcoming resistance in hormone-driven breast cancer. Experimental validation, including cytotoxicity assays and ADME/Tox profiling, is recommended to confirm their therapeutic potential. Full article

Background/Objectives: Bcr-Abl inhibitors such as imatinib have been used to treat chronic myeloid leukemia (CML). However, the efficacy of these drugs has diminished due to mutations in the kinase domain, notably the T315I mutation. Therefore, in this study, new purine derivatives were designed as Bcr-Abl inhibitors based on 3D-QSAR studies. Methods: A database of 58 purines that inhibit Bcr-Abl was used to construct 3D-QSAR models. Using chemical information from these models, a small group of new purines was designed, synthesized, and evaluated in Bcr-Abl. Viability assays were conducted on imatinib-sensitive CML cells (K562 and KCL22) and imatinib-resistant cells (KCL22-B8). In silico analyses were performed to confirm the results. Results: Seven purines were easily synthesized (7a–g). Compounds 7a and 7c demonstrated the highest inhibition activity on Bcr-Abl (IC₅₀ = 0.13 and 0.19 μM), surpassing the potency of imatinib (IC₅₀ = 0.33 μM). 7c exhibited the highest potency, with GI₅₀ = 0.30 μM on K562 cells and 1.54 μM on KCL22 cells. The GI₅₀ values obtained for non-neoplastic HEK293T cells indicated that 7c was less toxic than imatinib. Interestingly, KCL22-B8 cells (expressing Bcr-Abl^T315I) showed greater sensitivity to 7e and 7f than to imatinib (GI₅₀ = 13.80 and 15.43 vs. >20 μM, respectively). In silico analyses, including docking and molecular dynamics studies of Bcr-Abl^T315I, were conducted to elucidate the enhanced potency of 7e and 7f. Thus, this study provides in silico models to identify novel inhibitors that target a kinase of significance in CML. Full article

Mycobacterium tuberculosis, the infectious agent behind tuberculosis (TB), underscores the significance of targeting enzymes such as arabinosyltransferases in drug development efforts. Benzothiozinone derivatives, which have been assessed for their effectiveness against TB, present a promising avenue for treatment. Utilizing a high virtual screening quantitative structure–activity relationship (QSAR-VS), a set of forty Benzothiozinone (C1–C40) compounds were investigated to build a robust model with satisfactory performance metrics (R² = 0.82, R²_adj = 0.78, N_test = 10, R²_test = 0.70). This model enabled the creation of databases containing new derivatives for screening drug-like properties and predicting MIC activity in TB treatment. The best-scoring compounds were screened by molecular docking with Mycobacterium tuberculosis kinases A and B (PDB code: 6B2P) and validated by molecular dynamics simulations to elucidate the most stable drug–protein interactions. Additionally, the MM-PBSA analysis shows that the strongest binding occurs in complexes X3, X4, and X6 with ΔG_bind values of −8.2, −15.3, and −12.0 kcal/mol, respectively. Our in silico study aims to prospect these new anti-tubercular drugs and their potential development through perspective in vitro and in vivo assays. Full article

Dopamine D₃ receptor (D₃R) is a key receptor for regulating motor, cognitive, and other functions. In this study, 50 2-phenylcyclopropylmethylamine (PCPMA) derivatives with good selectivity for D₃R were investigated using a three-dimensional quantitative structure–activity relationship (3D-QSAR) method. The CoMFA and CoMSIA model results showed good predictive ability, as evidenced by high r² and q² values. 3D-QSAR results showed that steric, electrostatic, and hydrophobic fields played important roles in the binding of PCPMAs to D₃R. Based on above results, four novel PCPMAs were designed, which were predicted to have a stronger affinity with D₃R. Molecular docking combined with 300 ns molecular dynamics simulations were performed to reveal the mode of interaction between D₃R and PCPMAs. Additionally, a combination of free energy calculations and energy decomposition results indicated strong interaction between the ligands and residues in the binding pocket of the D₃ receptor. This work provides suggestions for exploring more selective D₃R ligands, and this theoretical framework also lays the foundation for future experimental investigations to evaluate the pharmacological characteristics and binding affinities of novel derivatives. Full article

Although the present use of pesticides in plant protection has limited the occurrence and development of plant diseases and pests, resistance to pesticides and their environmental and health hazards indicates an urgent need for new active ingredients in plant protection products. Recently synthesized coumarin-1,2,4-triazole hybrid compounds have been proven effective against plant pathogenic fungi and safe for soil-beneficial bacteria. Drosophila melanogaster, the common fruit fly, has been used as a model organism for scientific research. Additionally, it is considered a pest since it damages fruits and serves as a carrier for various plant diseases. On the contrary, Orius laevigatus is a beneficial true bug that biologically controls harmful arthropods in agricultural production. In the present study, we performed an adulticidal bioassay against D. melanogaster and O. laevigatus using coumarin-1,2,4-triazole hybrids. Quantitative structure–activity relationship studies (QSARs) and in silico ecotoxicity evaluation elucidated the structural features underlying the compounds’ insecticidal activity. The derivative of 4-methylcoumarin-1,2,4-triazole with a 3-bromophenyl group showed great insecticidal potential. A molecular docking study indicated that the most active compound probably binds to glutamate-gated chloride channels. Full article

γ-amino butyric acid (GABA) is an inhibitory neurotransmitter whose deficiency has been associated with various neurological disorders. However, its low liposolubility limits its use as a supplement. Thus, multiple investigations have focused on searching for lipophilic GABA analogs that can modulate the activity of the GABA_B receptor, which could be associated with the etiology of some central nervous system disorders. The GABA analogs available on the market are Vigabatrin, Gabapentin as well as Pregabalin and Baclofen. In this work, we report on the synthesis of GABA analogs, taking the scaffold of GABA, Pregabalin, and Baclofen as a starting point. The analogs include structural features that could favor the affinity of the molecules for the GABA_B receptor, such as heterocyclic rings in the γ-position and alkyl or p-Cl-phenyl substituents (in analogy to Pregabalin and Baclofen, respectively). These analogs were synthesized by a sequence of reactions involving an N-alkylation, a 1,4-conjugated addition of dialkyl and diarylcuprates and a basic hydrolysis. Furthermore, a computational molecular docking over the GABA_B receptor was performed to evaluate the interaction of each compound in the Baclofen binding site. With this information, we evaluated our compounds as GABA_B agonists through a QSAR analysis. Finally, by means of molecular similarity analysis, and in silico ADME prediction, we support our three best compounds (8a–b, 8d) as potential GABA_B receptor agonists. Full article

Scientific research on stilbenes is conducted for their chemopreventive and therapeutic properties. In experimental studies, natural and synthetic trans-stilbenes exhibit antioxidant, anti-inflammatory, cardioprotective, and anticancer effects. The antitumor activity of some natural and synthetic stilbenes is associated with their interaction with cytochrome P450 family 1, which leads to the inhibition of procarcinogen activation. In the present study, three-dimensional quantitative structure–activity relationship analysis (3D-QSAR) was performed on a series of forty-one trans-stilbene derivatives to identify the most significant features of the molecules responsible for their CYP1B1 inhibitory activity. The developed 3D-QSAR model presented a cross-validated correlation coefficient Q² of 0.554. The model’s predictive ability was confirmed by external validation (r² = 0.808). The information provided by 3D-QSAR analysis is expected to be valuable for the rational design of novel CYP1B1 inhibitors. Full article

Nakaseomyces glabrata (Candida glabrata), the second most prevalent Candida pathogen globally, has emerged as a major clinical threat due to its ability to develop high-level azole resistance. In this study, two new 5,6-dihydrotetrazolo[1,5-c]quinazoline derivatives (c11 and c12) were synthesized and characterized using IR, LC-MS, ¹H, and ¹³C NMR spectra. Along with 13 previously reported analogues, these compounds underwent in vitro antifungal testing against clinical N. glabrata isolates using a serial dilution method (0.125–64 mg/L). Remarkably, compounds c5 and c1 exhibited potent antifungal activity, with minimum inhibitory concentrations of 0.37 μM and 0.47 μM, respectively—about a 20-fold improvement in μM concentration over standard drugs like amphotericin B, caspofungin, and micafungin. A detailed structure–activity relationship analysis revealed crucial molecular features enhancing antifungal potency. Extensive molecular docking studies across 18 protein targets explored potential binding pockets and affinities of the lead compounds. A robust 3D-QSAR model, incorporating molecular descriptors Mor26m and Mor29e, displayed good predictive ability for antifungal activity. In silico predictions indicated an absence of herbicidal effect, negligible environmental toxicity (to honeybees, avian species, and aquatic organisms), and mild human toxicity concerns for these compounds. This comprehensive approach aims to develop novel and effective antifungal compounds against the clinically relevant pathogen N. glabrata. Full article

Background/Objectives: Alterations in the actin cytoskeleton correlates to tumor progression and affect critical cellular processes such as adhesion, migration and invasion. Rho-associated coiled-coil-containing protein kinases (ROCK1 and ROCK2), important regulators of the actin cytoskeleton, are frequently overexpressed in various malignancies. The aim of this study was therefore to identify the key structural features of ROCK1/ROCK2 inhibitors using computer-aided drug design (CADD) approaches. In addition, new developed ROCK inhibitors provided a significant framework for the development of multitarget therapeutics—ROCK/HDAC (histone deacetylases) multitarget inhibitors. Methods: 3D-QSAR (Quantitative structure-activity relationship study) and molecular docking study were employed in order to identify key structural features that positively correlate with ROCK inhibition. MDA-MB-231, HCC1937, Panc-1 and Mia PaCa-2 cells were used for evaluation of anticancer properties of synthesized compounds. Results: C-19 showed potent anti-cancer properties, especially enhancement of apoptosis and cell cycle modulation in pancreatic cancer cell lines. In addition, C-19 and C-22 showed potent anti-migratory and anti-invasive effects comparable to the well-known ROCK inhibitor fasudil. Conclusions: In light of the results of this study, we propose a novel multi-target approach focusing on developing dual HDAC/ROCK inhibitors based on the structure of both C-19 and C-22, exploiting the synergistic potential of these two signaling pathways to improve therapeutic efficacy in metastatic tumors. Our results emphasize the potential of multi-target ROCK inhibitors as a basis for future cancer therapies. Full article

The search for anticancer drugs that target ferroptosis is a promising avenue of research. SLC7A11, a key protein involved in ferroptosis, has been identified as a potential target for drug development. Through screening efforts, novel inhibitors of SLC7A11 have been designed with the aim of promoting ferroptosis and ultimately eliminating cancer cells. We initially screened 563 small molecules using pharmacophore and 2D-QSAR models. Molecular docking and ADMET toxicity predictions, with Erastin as a positive control, identified the small molecules 42711 and 27363 as lead compounds with strong inhibitory activity against SLC7A11. Further optimization resulted in the development of a new inhibitor structure (42711_11). Molecular docking and ADMET re-screening demonstrated successful fragment substitution for this small molecule. Final molecular dynamics simulations also confirmed its stable interaction with the protein. These findings represent a significant step towards the development of new therapeutic strategies for ferroptosis-related diseases. Full article

Considering the escalating global prevalence and the huge therapeutic demand for the treatment of hypertension, there is a persistent need to identify novel target sites for vasodilator action. This study aimed to investigate the role of TRPA1 channels in carvacrol-induced vasodilation and to design novel compounds based on carvacrol structure with improved activities. In an isolated tissue bath experiment, it was shown that 1 µM of the selective TRPA1 antagonist A967079 significantly (p < 0.001) reduced vasodilation induced by 3 mM of carvacrol. A reliable 3D-QSAR model with good statistical parameters was created (R² = 0.83; Q² = 0.59 and ${\mathrm{R}}_{\mathrm{p}\mathrm{r}\mathrm{e}\mathrm{d}}^2$ = 0.84) using 29 TRPA1 agonists. Obtained results from this model were used for the design of novel TRPA1 activators, and to predict their activity against TRPA1. Predicted pEC50 activities of these molecules range between 4.996 to 5.235 compared to experimental pEC50 of 4.77 for carvacrol. Molecular docking studies showed that designed molecules interact with similar amino acid residues of the TRPA1 channel as carvacrol, with eight compounds showing lower binding energies. In conclusion, carvacrol-induced vasodilation is partly mediated by the activation of TRPA1 channels. Combining different in silico approaches pointed out that the molecule D27 (2-[2-(hydroxymethyl)-4-methylphenyl]acetamide) is the best candidate for further synthesis and experimental evaluation in in vitro conditions. Full article

Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer’s disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R² = 0.701, R²test = 0.76, Q²CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model’s robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer’s activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (−12.6 kcal/mol), (−13 kcal/mol), and (−12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (−10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors. Full article