Search Results (97)

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

Biflavonoids are a unique subclass of dietary polyphenolic compounds known for their diverse bioactivities. Despite these benefits, these biflavonoids remain largely underexplored due to their limited natural availability and harsh conditions required for their synthesis, which restricts broader research and application in functional foods and nutraceuticals. To address this gap, we synthesized a library of rare biflavonoids using a radical–nucleophile coupling reaction previously reported by our group. The food grade coupling reaction under weakly alkaline water at room temperature led to isolation of 28 heterocoupled biflavones from 11 monomers, namely 3′,4′-dihydroxyflavone, 5,3′,4′-trihydroxyflavone, 6,3′,4′-trihydroxyflavone, 7,3′,4′-trihydroxyflavone, diosmetin, chrysin, acacetin, genistein, biochanin A, and wogonin. The structures of the dimers are characterized by nuclear magnetic resonance spectroscopy (NMR) and high-resolution mass spectroscopy (HRMS). In addition, we evaluated the antioxidant potential of these biflavones using a DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging assay and the DPPH value ranges between 0.75 to 1.82 mM of Trolox/mM of sample across the 28 synthesized dimers. Additionally, a three-dimensional quantitative structure–activity relationship (3D-QSAR) analysis was conducted to identify structural features associated with enhanced antioxidant activity. The partial least squares (PLS) regression QSAR model showed acceptable r² = 0.936 and q² = 0.869. Additionally, the average local ionization energy (ALIE), electrostatic potential (ESP), Fukui index (F-), and electron density (ED) were determined to identify the key structural moiety that was capable of donating electrons to neutralize reactive oxygen species. 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

Background/Objectives: The progression of three-dimensional (3D) quantitative structure–activity relationship (QSAR) methodologies has significantly contributed to the advancement of medicinal chemistry and pharmaceutical discovery. Comparative Molecular Similarity Indices Analysis (CoMSIA) is a widely used 3D-QSAR technique. However, its reliance on discontinued proprietary software creates accessibility challenges. This work aims to develop an open-source Python library to address these limitations and broaden access to grid-based 3D-QSAR methods. Methods: Py-CoMSIA was developed in Python using RDKit and NumPy for calculations and PyVista for visualizations. Results: Py-CoMSIA provides a functional open-source alternative to proprietary CoMSIA software. It successfully implements the core CoMSIA algorithm and generates comparable similarity indices, as demonstrated by testing several benchmarking datasets including the original CoMSIA steroid dataset. Conclusions: The Py-CoMSIA library addresses the accessibility issues associated with proprietary 3D-QSAR software by providing an open-source Python implementation of CoMSIA. This tool broadens access to complex grid-based 3D-QSAR methodologies and offers a flexible platform for integrating advanced statistical and machine learning techniques. 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

The hERG potassium channel serves as an annexed target for drug discovery because the associated off-target inhibitory activity may cause serious cardiotoxicity. Quantitative structure–activity relationship (QSAR) models were developed to predict inhibitory activities against the hERG potassium channel, utilizing the three-dimensional (3D) distribution of quantum mechanical electrostatic potential (ESP) as the molecular descriptor. To prepare the optimal atomic coordinates of dataset molecules, pairwise 3D structural alignments were carried out in order for the quantum mechanical cross correlation between the template and other molecules to be maximized. This alignment method stands out from the common atom-by-atom matching technique, as it can handle structurally diverse molecules as effectively as chemical derivatives that share an identical scaffold. The alignment problem prevalent in 3D-QSAR methods was ameliorated substantially by dividing the dataset molecules into seven subsets, each of which contained molecules with similar molecular weights. Using an artificial neural network algorithm to find the functional relationship between the quantum mechanical ESP descriptors and the experimental hERG inhibitory activities, highly predictive 3D-QSAR models were derived for all seven molecular subsets to the extent that the squared correlation coefficients exceeded 0.79. Given their simplicity in model development and strong predictability, the 3D-QSAR models developed in this study are expected to function as an effective virtual screening tool for assessing the potential cardiotoxicity of drug candidate molecules. Full article

Humanity is facing a vast prevalence of neurodegenerative diseases, with Alzheimer’s disease (AD) being the most dominant, without efficacious drugs, and with only a few therapeutic targets identified. In this scenario, we aim to find molecular entities that modulate imidazoline I₂ receptors (I₂-IRs) that have been pointed out as relevant targets in AD. In this work, we explored structural modifications of well-established I₂-IR ligands, giving access to derivatives with an imidazole-linked heterocycle as a common key feature. We report the synthesis, the affinity in human I₂-IRs, the brain penetration capabilities, the in silico ADMET studies, and the three-dimensional quantitative structure-activity relationship (3D-QSAR) studies of this new bunch of I₂-IR ligands. Selected compounds showed neuroprotective properties and beneficial effects in an in vitro model of Parkinson’s disease, rescued the human dopaminergic cell line SH-SY5Y from death after treatment with 6-hydroxydopamine, and showed crucial anti-inflammatory effects in a cellular model of neuroinflammation. After a preliminary pharmacokinetic study, we explored the action of our representative 2-(benzo[b]thiophen-2-yl)-1H-imidazole LSL33 in a mouse model of AD (5xFAD). Oral administration of LSL33 at 2 mg/Kg for 4 weeks ameliorated 5XFAD cognitive impairment and synaptic plasticity, as well as reduced neuroinflammation markers. In summary, this new I₂-IR ligand that promoted beneficial effects in a well-established AD mouse model should be considered a promising therapeutic strategy for neurodegeneration. Full article

Commercially available cathinones are drugs of long-term abuse drugs whose pharmacology is fairly well understood. While their psychedelic effects are associated with 5-HT_2AR, the enclosed study summarizes efforts to shed light on the pharmacodynamic profiles, not yet known at the receptor level, using molecular docking and three-dimensional quantitative structure–activity relationship (3-D QSAR) studies. The bioactive conformations of cathinones were modeled by AutoDock Vina and were used to build structure-based (SB) 3-D QSAR models using the Open3DQSAR engine. Graphical inspection of the results led to the depiction of a 3-D structure analysis-activity relationship (SAR) scheme that could be used as a guideline for molecular determinants by which any untested cathinone molecule can be predicted as a potential 5-HT_2AR binder prior to experimental evaluation. The obtained models, which showed a good agreement with the chemical properties of co-crystallized 5-HT_2AR ligands, proved to be valuable for future virtual screening campaigns to recognize unused cathinones and similar compounds, such as 5-HT_2AR ligands, minimizing both time and financial resources for the characterization of their psychedelic effects. Full article

The platelet-derived growth factor receptor (PDGFR) is a membrane tyrosine kinase receptor involved in several metabolic pathways, not only physiological but also pathological, as in tumor progression, immune-mediated diseases, and viral diseases. Considering this macromolecule as a druggable target for modulation/inhibition of these conditions, the aim of this work was to find new ligands or new information to design novel effective drugs. We performed an initial interaction screening with the human intracellular PDGFRα of about 7200 drugs and natural compounds contained in 5 independent databases/libraries implemented in the MTiOpenScreen web server. After the selection of 27 compounds, a structural analysis of the obtained complexes was performed. Three-dimensional quantitative structure–activity relationship (3D-QSAR) and absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were also performed to understand the physicochemical properties of identified compounds to increase affinity and selectivity for PDGFRα. Among these 27 compounds, the drugs Bafetinib, Radotinib, Flumatinib, and Imatinib showed higher affinity for this tyrosine kinase receptor, lying in the nanomolar order, while the natural products included in this group, such as curcumin, luteolin, and epigallocatechin gallate (EGCG), showed sub-micromolar affinities. Although experimental studies are mandatory to fully understand the mechanisms behind PDGFRα inhibitors, the structural information obtained through this study could provide useful insight into the future development of more effective and targeted treatments for PDGFRα-related diseases, such as cancer and fibrosis. Full article

As an effective herbicide, 1, 3, 5-Triazine herbicides (S-THs) are used widely in the pesticide market. However, due to their chemical properties, S-THs severely threaten the environment and human health (e.g., human lung cytotoxicity). In this study, molecular docking, Analytic Hierarchy Process—Technique for Order Preference by Similarity to the Ideal Solution (AHP-TOPSIS), and a three-dimensional quantitative structure-active relationship (3D-QSAR) model were used to design S-TH substitutes with high herbicidal functionality, high microbial degradability, and low human lung cytotoxicity. We discovered a substitute, Derivative-5, with excellent overall performance. Furthermore, Taguchi orthogonal experiments, full factorial design of experiments, and the molecular dynamics method were used to identify three chemicals (namely, the coexistence of aspartic acid, alanine, and glycine) that could promote the degradation of S-THs in maize cropping fields. Finally, density functional theory (DFT), Estimation Programs Interface (EPI), pharmacokinetic, and toxicokinetic methods were used to further verify the high microbial degradability, favorable aquatic environment, and human health friendliness of Derivative 5. This study provided a new direction for further optimizations of novel pesticide chemicals. Full article

To limit the dangers posed by Cu(II) pollution, chitosan-nanohybrid derivatives were developed for selective and rapid copper adsorption. A magnetic chitosan nanohybrid (r-MCS) was obtained via the co-precipitation nucleation of ferroferric oxide (Fe₃O₄) co-stabilized within chitosan, followed by further multifunctionalization with amine (diethylenetriamine) and amino acid moieties (alanine, cysteine, and serine types) to give the TA-type, A-type, C-type, and S-type, respectively. The physiochemical characteristics of the as-prepared adsorbents were thoroughly elucidated. The superparamagnetic Fe₃O₄ nanoparticles were mono-dispersed spherical shapes with typical sizes (~8.5–14.7 nm). The adsorption properties toward Cu(II) were compared, and the interaction behaviors were explained with XPS and FTIR analysis. The saturation adsorption capacities (in mmol.Cu.g⁻¹) have the following order: TA-type (3.29) > C-type (1.92) > S-type (1.75) > A-type(1.70) > r-MCS (0.99) at optimal pH₀ 5.0. The adsorption was endothermic with fast kinetics (except TA-type was exothermic). Langmuir and pseudo-second-order equations fit well with the experimental data. The nanohybrids exhibit selective adsorption for Cu(II) from multicomponent solutions. These adsorbents show high durability over multiple cycles with desorption efficiency > 93% over six cycles using acidified thiourea. Ultimately, QSAR tools (quantitative structure-activity relationships) were employed to examine the relationship between essential metal properties and adsorbent sensitivities. Moreover, the adsorption process was described quantitatively, using a novel three-dimensional (3D) nonlinear mathematical model. Full article

HIV-1 maturation is the final step in the retroviral lifecycle that is regulated by the proteolytic cleavage of the Gag precursor protein. As a first-in-class HIV-1 maturation inhibitor (MI), bevirimat blocks virion maturation by disrupting capsid-spacer peptide 1 (CA-SP1) cleavage, which acts as the target of MIs. Previous alterations of beesioside I (1) produced (20S,24S)-15ꞵ,16ꞵ-diacetoxy-18,24; 20,24-diepoxy-9,19-cyclolanostane-3ꞵ,25-diol 3-O-3′,3′-dimethylsuccinate (3, DSC), showing similar anti-HIV potency compared to bevirimat. To ascertain the binding modes of this derivative, further modification of compound 1 was conducted. Three-dimensional quantitative structure–activity relationship (3D-QSAR) analysis combined with docking simulations and molecular dynamics (MD) were conducted. Five new derivatives were synthesized, among which compound 3b showed significant activity against HIV-1_NL4-3 with an EC₅₀ value of 0.28 µM. The developed 3D-QSAR model resulted in great predictive ability with training set (r² = 0.99, q² = 0.55). Molecular docking studies were complementary to the 3D-QSAR analysis, showing that DSC was differently bound to CA-SP1 with higher affinity than that of bevirimat. MD studies revealed that the complex of the ligand and the protein was stable, with root mean square deviation (RMSD) values <2.5 Å. The above results provided valuable insights into the potential of DSC as a prototype to develop new antiviral agents. Full article

Restricted economic conditions and limited sewage treatment facilities in rural areas lead to the discharge of small-scale breeding wastewater containing higher values of residual beta-lactam antibiotics (β-lactams), which seriously threatens the aquatic environment. In this paper, molecular docking and a comprehensive method were performed to quantify and fit the source modification for the combined biodegradation of β-lactams. Using penicillin (PNC) as the target molecule, combined with contour maps for substitute modification, a three-dimensional quantitative structure–activity relationship (3D-QSAR) model was constructed for the high-performance combined biodegradation of β-lactams. The selected candidate with better environmental friendliness, functionality, and high performance was screened. By using the homology modeling algorithms, the mutant penicillin-binding proteins (PBPs) of Escherichia coli were constructed to have antibacterial resistance against β-lactams. The molecular docking was applied to obtain the target substitute by analyzing the degree of antibacterial resistance of β-lactam substitute. The combined biodegradation of β-lactams and substitute in the constructed wetland (CW) by different wetland plant root secretions was studied using molecular dynamics simulations. The result showed a 49.28% higher biodegradation of the substitutes than PNC when the combined wetland plant species of Eichhornia crassipes, Phragmites australis, and Canna indica L. were employed. Full article

Lysine-specific demethylase 1 (LSD1) is a histone-modifying enzyme, which is a significant target for anticancer drug research. In this work, 40 reported tetrahydroquinoline-derivative inhibitors targeting LSD1 were studied to establish the three-dimensional quantitative structure–activity relationship (3D-QSAR). The established models CoMFA (Comparative Molecular Field Analysis (q² = 0.778, ${\mathrm{R}}_{\mathrm{pred}}^2$ = 0.709)) and CoMSIA (Comparative Molecular Similarity Index Analysis (q² = 0.764, ${\mathrm{R}}_{\mathrm{pred}}^2$ = 0.713)) yielded good statistical and predictive properties. Based on the corresponding contour maps, seven novel tetrahydroquinoline derivatives were designed. For more information, three of the compounds (D1, D4, and Z17) and the template molecule 18x were explored with molecular dynamics simulations, binding free energy calculations by MM/PBSA method as well as the ADME (absorption, distribution, metabolism, and excretion) prediction. The results suggested that D1, D4, and Z17 performed better than template molecule 18x due to the introduction of the amino and hydrophobic groups, especially for the D1 and D4, which will provide guidance for the design of LSD1 inhibitors. Full article

Triple-negative breast cancer (TNBC) is defined as a kind of breast cancer that lacks estrogen receptors (ER), progesterone receptors (PR), and human epidermal growth factor receptors (HER2). This cancer accounts for 10–15% of all breast cancers and has the features of high invasiveness and metastatic potential. The treatment regimens are still lacking and need to develop novel inhibitors for therapeutic strategies. Three-dimensional quantitative structure-activity relationship (3D-QSAR) analyses, based on a series of forty-seven thieno-pyrimidine derivatives, were performed to identify the key structural features for the inhibitory biological activities. The established comparative molecular field analysis (CoMFA) presented a leave-one-out cross-validated correlation coefficient q² of 0.818 and a determination coefficient r² of 0.917. In comparative molecular similarity indices analysis (CoMSIA), a q² of 0.801 and an r² of 0.897 were exhibited. The predictive capability of these models was confirmed by using external validation and was further validated by the progressive scrambling stability test. From these results of validation, the models were determined to be statistically reliable and robust. This study could provide valuable information for further optimization and design of novel inhibitors against metastatic breast cancer. Full article