Quantitative Structure-activity Relationship Analysis Research Articles

Influence of molecular descriptors of plant volatilomics on fumigant action against the three major stored product beetle pests.

Plant volatilomics such as essential oils (EOs) and volatile phytochemicals (PCs) are known as potential natural sources for the development of biofumigants as an alternative to conventional fumigant pesticides. This present work was aimed to evaluate the fumigant toxic effect of five selected EOs (cinnamon, garlic, lemon, orange, andpeppermint) and PCs (citronellol, limonene, linalool, piperitone, andterpineol) against the Callosobruchus maculatus, Sitophilus oryzae, and Tribolium castaneum adults. Furthermore, for the estimation of the relationship between molecular descriptors and fumigant toxicity of plant volatiles, quantitative structural activity relationship (QSAR) models were developed using principal component analysis and multiple linear regression. Amongst the tested EOs, garlic EO was found to be the most toxic fumigant. The PCs toxicity analysis revealed that terpineol, limonene, linalool, and piperitone as potential fumigants to C. maculatus (< 20 µL/L air of LC50), limonene and piperitone as potential fumigants to T. castaneum (14.35 and 154.11 µL/L air of LC50, respectively), and linalool and piperitone as potential fumigants to S. oryzae (192.27 and 69.10 µL/L air of LC50, respectively). QSAR analysis demonstrated the role of various molecular descriptors of EOs and PCs on the fumigant toxicity in insect pest species. In specific, dipole and Randic index influence the toxicity in C. maculatus, molecular weight and maximal projection area influence the toxicity in S. oryzae, and boiling point and Dreiding energy influence the toxicity in T. castaneum. The present findings may provide insight of a new strategy to select effective EOs and/or PCs against stored product insect pests.

Discovery and optimization of narrow spectrum inhibitors of Tousled like kinase 2 (TLK2) using quantitative structure activity relationships

The oxindole scaffold has been the center of several kinase drug discovery programs, some of which have led to approved medicines. A series of two oxindole matched pairs from the literature were identified where TLK2 was potently inhibited as an off-target kinase. The oxindole has long been considered a promiscuous kinase inhibitor template, but across these 4 specific literature oxindoles TLK2 activity was consistent, while the kinome profile was radically different ranging from narrow to broad spectrum coverage. We synthesized a large series of analogue, utilizing quantitative structure-activity relationship (QSAR) analysis, water mapping of the kinase ATP binding sites, kinome profiling and small-molecule x-ray structural analysis to optimize TLK2 inhibition and kinome selectivity. This resulted in the identification of several, narrow spectrum, sub-family selective, chemical tool compounds including 128 (UNC-CA2-103) that could enable elucidation of TLK2 biology.

Development and experimental validation of 3D QSAR models for the screening of thyroid peroxidase inhibitors using integrated methods of computational chemistry

The intricate network of glands and organs that makes up the endocrine system. Hormones are used to regulate and synchronize the nervous and physiological systems. The agents which perturbate an endocrine system are called endocrine disruptors and they can eventually affect cellular proliferation and differentiation in target tissues. A subclass of endocrine disruptors known as thyroid disruptors (TDs) or thyroid disrupting chemicals (TDCs) influence the hypothalamo-pituitary-thyroid axis or directly interfere with thyroid function by binding to thyroid hormone receptors. Thyroid hormone levels in circulation are now included in more test guidelines (OECD TG 441, 407, 408, 414, 421/422, 443/416). Although these might be adequate to recognize thyroid adversity, they are unable to explain the underlying mechanism of action. Thyroid peroxidase (TPO) and sodium iodide symporter (NIS), two proteins essential in the biosynthesis of thyroid hormones, are well-accepted molecular targets for inhibition. The screening of a large number of molecules using high throughput screening (HTS) requires a minimum quantity of sample, cost, and time consuming. Whereas 3-dimensional quantitative structure-activity relationship (3D-QSAR) analysis can screen the TDCs before synthesizing a compound. In the present study, the human TPO (hTPO) and NIS (hNIS) structures were modelled using homology modeling and the quality of the structures was validated satisfactorily using MD simulation for 100ns. Further, 190 human TPO inhibitors with IC50 were curated from Comptox and docked with the modelled structure of TPO using D238, H239 and D240 centric grid. The binding conformation of a molecule with low binding energy was used as a reference and the rest other molecules were aligned after generating the possible conformers. The activity-stratified partition was performed for aligned molecules and training set (139), test set (51) were defined. The machine learning models such as k Nearest Neighbor (kNN) and Random Forest (RF) models were built and validated using external experimental dataset containing 10 molecules. Among the 10 molecules, all 10 molecules were identified as TPO inhibitors and demonstrated 100 % accuracy qualitatively. To confirm the selective TPO inhibition all 10 molecules were docked with the modelled structure of hNIS and the results have demonstrated the selective TPO inhibition.

Mechanistic study of the electrochemical oxidation of fluoroquinolones: Ciprofloxacin, danofloxacin, enoxacin, levofloxacin and lomefloxacin

The fluoroquinolones ciprofloxacin, danofloxacin, enoxacin, levofloxacin and lomefloxacin, occur in water bodies worldwide and therefore pose a threat to the aquatic environment. Advanced purification procedures, such as electrochemical oxidation, may act as a remedy since they contribute to eliminating contaminants and prevent micropollutants from entering open water bodies. By electrochemical treatment in a micro-flow reactor equipped with a boron-doped diamond (BDD) electrode, the fluoroquinolones were efficiently degraded. A total of 15 new products were identified using high-performance high-resolution chromatography coupled with high-resolution multifragmentation mass spectrometry. The ecotoxicity of the emerging transformation products was estimated through in silico quantitative structure activity relationship analysis. Almost all transformation products were predicted less ecotoxic than the initial compounds. The fluoroquinolone degradation followed three major mechanisms depending on the voltage during the electrochemical oxidation. At approximately 1 V, the reactions started with the elimination of molecular hydrogen from the piperazine moiety. At approx. 1.25 V, methyl and methylene groups were eliminated. At 1.5 V, hydroxyl radicals, generated at the BDD electrode, led to substitution at the piperazine ring. This novel finding of the three reactions depending on voltage contributes to the mechanistic understanding of electrochemical oxidation as potential remedy against fluoroquinolones in the aquatic environment.

Assessing biologic/toxicologic effects of extractables from plastic contact materials for advanced therapy manufacturing using cell painting assay and cytotoxicity screening

Plastic components are essential in the pharmaceutical industry, encompassing container closure systems, laboratory handling equipment, and single-use systems. As part of their material qualification process, studies on interactions between plastic contact materials and process solutions or drug products are conducted. The assessment of single-use systems includes their potential impact on patient safety, product quality, and process performance. This is particularly crucial in cell and gene therapy applications since interactions with the plastic contact material may result in an adverse effect on the isolated therapeutic human cells. We utilized the cell painting assay (CPA), a non-targeted method, for profiling the morphological characteristics of U2OS human osteosarcoma cells in contact with chemicals related to plastic contact materials. Specifically, we conducted a comprehensive analysis of 45 common plastic extractables, and two extracts from single-use systems. Results of the CPA are compared with a standard cytotoxicity assay, an osteogenesis differentiation assay, and in silico toxicity predictions. The findings of this feasibility study demonstrate that the device extracts and most of the tested compounds do not evoke any measurable biological changes on the cells (induction  ≤ 5%) among the 579 cell features measured at concentrations  ≤ 50 µM. CPA can serve as an important assay to reveal unique information not accessible through quantitative structure–activity relationship analysis and vice versa. The results highlight the need for a combination of in vitro and in silico methods in a comprehensive assessment of single-use equipment utilized in advanced therapy medicinal products manufacturing.

Photodegradation of polychlorinated biphenyls in water/nitrogen-doped silica and air/nitrogen-doped silica systems: Kinetics, mechanism and quantitative structure activity relationship (QSAR) analysis

Developing efficient and low-cost photocatalytic materials is essential for removing polychlorinated biphenyls (PCBs). In this work, the photodegradation process of fourteen representative polychlorinated biphenyls (PCBs) in both water/nitrogen-doped SiO2 (N-SiO2) and air/N-SiO2 systems was studied. The photodegradation kinetics of PCBs is consistent with the pseudo-first-order kinetic equation. The variation in the degradation effects of different PCBs in the two systems is primarily related to the position of the Cl substituent and the effective absorption wavelength range of PCBs. A total of fourteen intermediates for 4′-Dichlorobiphenyl (PCB-15), 2,2′,4,4′,6,6′-Hexachlorobiphenyl (PCB-155), and 2,2′,3,3′,4,4′,5,5′,6,6′-Decachlorobiphenyl (PCB-209) generated from four reaction pathways were identified based on both mass spectrometry analysis and theoretical calculations. Using the values of lnk (k denotes pseudo-first-order kinetic constants) for the 11 PCBs in the training set and the calculated molecular and structural parameters, quantitative structure-activity relationship (QSAR) models for the two systems were constructed by using multiple linear regression (MLR) method to better understand the factors affecting the photodegradation rate of PCBs. The QSAR equations were obtained with Cl atom substitution at position 3 (N3) as the main parameter, which were lnk = −1.98 - 0.19 N3 for the water/N-SiO2 system and lnk = −1.56 - 0.34 N3 for the air/N-SiO2 system, with the correlation coefficient (R2) of 0.66 and 0.73, leave-one-out cross-validation (Q2LOO) of 0.51 and 0.59, respectively, and bootstrapping validation coefficients (Q2BOOT) values of both 0.74, confirming that the models were well fitted and showed high robustness and prediction ability. This study provides valuable insights into photocatalytic degradation studies of PCBs.

A Linear and Nonlinear QSAR Analysis of Benzimidazole Derivative XY123 in Prostate Cancer Treatment

Background: Metastatic Castration-Resistant Prostate Cancer (mCRPC) represents a critical challenge in current prostate cancer treatment. Benzimidazole Derivative XY123 has emerged as a novel inhibitor for its treatment. Objective: This study aims to establish a robust Quantitative Structure-Activity Relationship (QSAR) model for predicting the activity of Benzimidazole Derivative XY123 derivatives, aiding the development of novel anti-prostate cancer drugs. Methods: Utilizing CODESSA software, descriptors were computed based on various moieties of Benzimidazole Derivative XY123 derivatives. Multiple linear regression models were constructed, and both linear and nonlinear QSAR models were developed using heuristics and gene expression programming. Results: The linear model with two descriptors demonstrated the best predictive capacity for inhibitor activity, while the nonlinear model generated through Gene Expression Programming (GEP) exhibited correlation coefficients of 0.83 and 0.82 for the training and test sets, respectively. The average errors were 0.03 and 0.05, indicating the stability and the improved predictive ability of the nonlinear model. Conclusion: The QSAR linear model has an advantage over the nonlinear model in optimizing Benzimidazole Derivative XY123, providing a direction for the development of effective drugs for mCRPC treatment.

Doping tungsten in iron-cobalt layered double hydroxides with interwoven ultra-thin nanosheet structures enhances the degradation of metronidazole by activating calcium sulfite

Tungsten-doped iron-cobalt layered bimetallic hydroxides (CoFeW-LDHs) were used for activating sulfite to degrade metronidazole (MTZ) in this study. The characterization results confirmed the presence of vertically aligned hierarchical ultrathin nanosheets forming a porous network, which enhances the material's ability to activate CaSO3. The study investigated the optimal Co/Fe/W atomic ratio in the catalysts and examined the impact of various parameters, such as catalyst dosage, CaSO3 concentration, initial pH, and MTZ concentration. Under the best experimental conditions identified, the degradation rate of MTZ reached 95% within 60 min. Mechanism analysis revealed that W doping promoted oxidation–reduction reactions between Co(Ⅱ)/Co(Ⅲ) and Fe(Ⅲ)/Fe(Ⅱ) on the catalyst surface, facilitating CaSO3 activation and the continuous generation of reactive oxygen species (ROS) like 1O2 and SO4•−. Based on experimental, density functional theory (DFT), and quantitative structure–activity relationship analyses, the study proposed a degradation pathway and evaluated the ecotoxicity of MTZ and its intermediates. MTZ was found to be converted via three pathways into low or non-toxic intermediates, ultimately mineralizing into small inorganic molecules. Even after five cycles, Co3FeW-LDHs maintained a removal efficiency of over 90% for MTZ. The material's ease of synthesis, high activity, and stability suggest significant potential for practical application in environmental cleanup efforts.

Per- and polyfluoroalkyl substances inhibit human and rat 17β-hydroxysteroid dehydrogenase 1: Quantitative structure-activity relationship and molecular docking analysis

Per- and polyfluoroalkyl (PFAS) substances are enduring industrial materials. 17β-Hydroxysteroid dehydrogenase isoform 1 (17β-HSD1) is an estrogen metabolizing enzyme, which transforms estrone into estradiol in human placenta and rat ovary. Whether PFAS inhibit 17β-HSD1 and what the structure-activity relationship (SAR) remains unexplored. We screened 18 PFAS for inhibiting human and rat 17β-HSD1 in microsomes and studied their SAR and mode of action(MOA). Of the 11 perfluorocarboxylic acids (PFCAs), C8-C14 PFCAs at a concentration of 100 μM substantially inhibited human 17β-HSD1, with order of C11 (half-maximal inhibition concentration, IC50, 8.94 μM) > C10 (10.52 μM) > C12 (14.90 μM) > C13 (30.97 μM) > C9 (43.20 μM) > C14 (44.83 μM) > C8 (73.38 μM) > others. Of the 7 per- and poly-fluorosulfonic acids (PFSAs), the potency was C8S (IC50, 14.93 μM) > C7S (80.70 μM) > C6S (177.80 μM) > others. Of the PFCAs, C8-C14 PFCAs at 100 μM markedly reduced rat 17β-HSD1 activity, with order of C11 (IC50, 9.11 μM) > C12 (14.30 μM) > C10 (18.24 μM) > C13 (25.61 μM) > C9 (67.96 μM) > C8 (204.39 μM) > others. Of the PFSAs, the potency was C8S (IC50, 37.19 μM) > C7S (49.38 μM) > others. In contrast to PFOS (C6S), the partially fluorinated compound 6:2 FTS with an equivalent number of carbon atoms demonstrated no inhibition of human and rat 17β-HSD1 activity at a concentration of 100 μM. The inhibition of human and rat enzymes by PFAS followed a V-shaped trend from C4 to C14, with a nadir at C11. Moreover, human 17β-HSD1 was more sensitive than rat enzyme. PFAS inhibited human and rat 17β-HSD1 in a mixed mode. Docking analysis revealed that they bind to the NADPH and steroid binding site of both 17β-HSD1 enzymes. The 3D quantitative SAR (3D-QSAR) showed that hydrophobic region, hydrogen bond acceptor and donor are key factors in binding to 17β-HSD1 active sites. In conclusion, PFAS exhibit inhibitory effects on human and rat 17β-HSD1 depending on factors such as carbon chain length, degree of fluorination, and the presence of carboxylic acid or sulfonic acid groups, with a notable V-shaped shift observed at C11.

Origins of Selective Oxidation in Carbon-Based Nonradical Oxidation Processes toward Organic Pollutants: Quantitative Structure-Activity Relationships (QSARs).

Metal-free carbon material-mediated nonradical oxidation processes (C-NOPs) have emerged as a research hotspot due to their excellent performance in selectively eliminating organic pollutants in aqueous environments. However, the selective oxidation mechanisms of C-NOPs remain obscure due to the diversity of organic pollutants and nonradical active species. Herein, quantitative structure-activity relationship (QSAR) models were employed to unveil the origins of C-NOP selectivity toward organic pollutants in different oxidant systems. QSAR analysis based on adsorption and oxidation descriptors revealed that C-NOP selectivity depends on the oxidation potentials of organic pollutants rather than on adsorption interactions. However, the dominance of electronic effects in selective oxidation decreases with increasing structural complexity of organic pollutants. Moreover, the oxidation threshold solely depends on the inherent electronic nature of organic pollutants and not on the reactivity of nonradical active species. Notably, the accuracy of substituent descriptors (Hammett constants) and theoretical descriptors (e.g., highest occupied molecular orbital energy, ionization potential, and single-electron oxidation potential) is significantly influenced by the complexity and molecular state of organic pollutants. Overall, the study findings reveal the origins of organic pollutant-oriented selective oxidation and provide insight into the application of descriptors in QSAR analysis.

QSAR modelling to predict structural features of certain sulfonamide as Urokinase-type Plasminogen Activator inhibitors

The serine hydrolase family includes serine proteases. It is essential for hydrolyzing protein peptide bonds and breaking them. The urokinase-type plasminogen activator (uPA) selectively binds to the uPAR on numerous cell types, including cancer cells. Pericellular proteolysis of cell-bound proteins requires this interaction. High uPA and uPAR levels regularly worsen cancer prognoses. Thus, small chemical active-site inhibitors that block uPA may diminish cancer cell invasion and metastasis. In compliance with Organization for Economic Corporation and Development guidelines, this research performed a complete Quantitative structure activity relationship analysis of sulfonamide compounds as Urokinase-type Plasminogen Activator inhibitors. Py-Descriptors were used for this investigation. PyDescriptor uses PyMOL standards and idioms to calculate 11,145 simple molecular descriptors. This plugin calculates molecular descriptors irrespective of molecular representation properties like atom numbering or labelling, spatial reference frame, translational and rotational invariance, etc. The investigation sought to find essential and hidden structural characteristics that regulate sulfonamide-type drugs' Urokinase-type Plasminogen Activator Inhibitory action. Twenty-eight sulfonamide chemicals are used in the Quantitative structure activity relationship study to generate statistically robust and highly predictive univariate and multivariate models. All models were thoroughly evaluated and meet several statistical parameter thresholds (e.g., R2 =0.9259–0.9280, Q2Loo= 0.8579–0.8558, Q2LMO= 0.8013–0.7865). The analysis reveal that occurance of ring carbon atoms exactly at 3 A0 from carbon atom, number of negatively charged atoms from sulphur atoms within 5 bonds, presence of hydrogen atom exactly at 3 bonds from donar atoms, presence of carbon atom exactly at 4 A0 from donar atom, presence of acceptor atom exactly at 5 A0 from sulphur atom and sum of partial charges of lipo atoms within 6 bonds from sulphur atom are important pharmacophoric features for Urokinase-type Plasminogen Activator Inhibition binding affinity. Thus, the developed Quantitative structure activity relationship study has an equilibrium of quantitative and qualitative tactics. The results could be useful for future optimizations of sulfonamide analogues.

Computer-Aided Strategy on 5-(Substituted benzylidene) Thiazolidine-2,4-Diones to Develop New and Potent PTP1B Inhibitors: QSAR Modeling, Molecular Docking, Molecular Dynamics, PASS Predictions, and DFT Investigations.

A set of 5-(substituted benzylidene) thiazolidine-2,4-dione derivatives was explored to study the main structural requirement for the design of protein tyrosine phosphatase 1B (PTP1B) inhibitors. Utilizing multiple linear regression (MLR) analysis, we constructed a robust quantitative structure-activity relationship (QSAR) model to predict inhibitory activity, resulting in a noteworthy correlation coefficient (R2) of 0.942. Rigorous cross-validation using the leave-one-out (LOO) technique and statistical parameter calculations affirmed the model's reliability, with the QSAR analysis revealing 10 distinct structural patterns influencing PTP1B inhibitory activity. Compound 7e(ref) emerged as the optimal scaffold for drug design. Seven new PTP1B inhibitors were designed based on the QSAR model, followed by molecular docking studies to predict interactions and identify structural features. Pharmacokinetics properties were assessed through drug-likeness and ADMET studies. After that density functional theory (DFT) was conducted to assess the stability and reactivity of potential diabetes mellitus drug candidates. The subsequent dynamic simulation phase provided additional insights into stability and interactions dynamics of the top-ranked compound 11c. This comprehensive approach enhances our understanding of potential drug candidates for treating diabetes mellitus.

Identification of Novel EGFR Inhibitors for the Targeted Therapy of Colorectal Cancer Using Pharmacophore Modelling, Docking, Molecular Dynamic Simulation and Biological Activity Prediction.

Colorectal cancer (CRC) is considered the second deadliest cancer in the world. One of the reasons for the occurrence of this cancer is the deregulation of the Epidermal Growth Factor Receptor (EGFR), which plays a critical role in regulating cell division, persistence, differentiation, and migration. The overexpression of the EGFR protein leads to its dysregulation and causes CRC. Hence, this work aims to identify and validate novel EGFR inhibitors for the treatment of colorectal cancer employing various computer aided techniques such as pharmacophore modeling, docking, molecular dynamic simulation and Quantitative Structure-Activity Relationship (QSAR) analysis. In this work, a shared-featured ligand-based pharmacophore model was generated using the known inhibitors of EGFR. The best model was validated and screened against ZincPharmer and Maybridge databases, and 143 hits were obtained. Pharmacokinetic and toxicological properties of these hits were studied, and the acceptable ligands were docked against EGFR. The best five protein-ligand complexes with binding energy less than -5 kcal/mol were selected. The molecular dynamic simulation studies of these complexes were conducted for 100 nanoseconds (ns), and the results were analyzed. The biological activity of this ligand was calculated using QSAR analysis. The best complex with Root Mean Square Deviation (RMSD) 3.429 A0 and Radius of Gyration (RoG) 20.181 A0 was selected. The Root Mean Square Fluctuations (RMSF) results were also found to be satisfactory. The biological activity of this ligand was found to be 1.38 µM. This work hereby proposes the ligand 2-((1,6-dimethyl-4-oxo-1,4-dihydropyridin-3-yl)oxy)-N- (1H-indol-4-yl)acetamide as a potential EGFR inhibitor for the treatment of colorectal cancer. The wet lab analysis must be conducted, however, to confirm this hypothesis.

4D-QSAR and MIA-QSAR Studies of Aminobenzimidazole Derivatives as Fourth-generation EGFR Inhibitors.

The epidermal growth factor receptor (EGFR) protein has been intensively studied as a therapeutic target for non-small cell lung cancer (NSCLC). The aminobenzimidazole derivatives as the fourth-generation EGFR inhibitors have achieved promising results and overcame EGFR mutations at C797S, del19 and T790M in NSCLC. In order to understand the quantitative structure-activity relationship (QSAR) of aminobenzimidazole derivatives as EGFRdel19 T790M C797S inhibitors, the four-dimensional QSAR (4D-QSAR) and multivariate image analysis (MIA-QSAR) have been performed on the data of 45 known aminobenzimidazole derivatives. The 4D-QSAR descriptors were acquired by calculating the association energies between probes and aligned conformational ensemble profiles (CEP), and the regression models were established by partial least squares (PLS). In order to further understand and verify the 4D-QSAR model, MIA-QSAR was constructed by using chemical structure pictures to generate descriptors and PLS regression. Furthermore, the molecular docking and averaged noncovalent interactions (aNCI) analysis were also performed to further understand the interactions between ligands and the EGFR targets, which was in good agreement with the 4D-QSAR model. The established 4D-QSAR and MIA-QSAR models have strong stability and good external prediction ability. These results will provide theoretical guidance for the research and development of aminobenzimidazole derivatives as new EGFRdel19 T790M C797S inhibitors.

SAR study of N′-(Salicylidene)heteroarenecarbohydrazides as promising antifungal agents

Clinically available antifungal drugs have therapeutic limitations due to toxicity, narrow spectrum of activity, and intrinsic or acquired drug resistance. Thus, there is an urgent need for new broad-spectrum antifungal agents with low toxicity and a novel mechanism of action. In this context, we have successfully identified several highly promising lead compounds, i.e., aromatic N′-(salicylidene)carbohydrazides, exhibiting excellent antifungal activities against Cryptococcus neoformans, Candida albicans, Aspergillus fumigatus and several other fungi both in vitro and in vivo. Building upon these highly promising results, 71 novel N′-(salicylidene)heteroarenecarbohydrazides 5 were designed, synthesized and their antifungal activities examined against fungi. Based on the SAR study, four highly promising lead compounds, i.e., 5.6a, 5.6b, 5.7b and 5.13a were identified, which exhibited excellent potency against C. neoformans, C. albicans and A. fumigatus, and displayed impressive time-kill profiles against C. neoformans with exceptionally high selectivity indices (SI ≥ 500). These four lead compounds also showed synergy with clinical antifungal drugs, fluconazole, caspofungin (CS) and amphotericin B against C. neoformans. For the SAR study, we also employed quantitative structure–activity relationship (QSAR) analysis by taking advantage of the accumulated data on a large number of aromatic and heteroaromatic N′-(salicylidene)carbohydrazides, which successfully led to rational design and selection of promising compounds for chemical synthesis and biological evaluation.

Synthesis and Biological Evaluation of 2-Azolylmethylene-3-(2H)-benzofuranone Derivatives as Potent Monoamine Oxidases Inhibitors.

A series of 2-azolylmethylene-3-(2H)-benzofuranone derivatives, 2-indolylmethylene-3-(2H)-benzofuranone and 2-pyrrolylmethylene-3-(2H)-benzofuranone derivatives, were synthesized, and their monoamine oxidase (MAO) A and B inhibitory activities were evaluated. Compounds 1b, 3b, 6b, 7b, and 10b showed strong inhibitory activity against MAO-A, and compound 3b showed the highest potency and selectivity, with an IC50 value of 21 nM and a MAO-A selectivity index of 48. Compounds 3c, 4c, 9a, 9c, 10c, 11a, and 11c showed strong inhibitory activity against MAO-B, and compound 4c showed the highest potency and selectivity, with an IC50 value of 16 nM and a MAO-B selectivity index of >1100. Further analysis of these compounds indicated that compound 3b for MAO-A and compound 4c for MAO-B were competitive inhibitors, with Ki values of 10 and 6.1 nM, respectively. Furthermore, computational analyses, such as quantitative structure-activity relationship (QSAR) analysis of the 2-azolylmethylene-3-(2H)-benzofuranone derivatives conducting their pIC50 values with the Molecular Operating Environment (MOE) and Mordred, and molecular docking analysis using MOE-Dock supported that the 2-azolylmethylene-3-(2H)-benzofuranone derivatives are a privileged scaffold for the design and development of novel MAO inhibitors.

Comparison of photoinduced and electrochemically induced degradation of venlafaxine.

The European Union requires environmental monitoring of the antidepressant drug venlafaxine. Advanced oxidation processes provide a remedy against the spread of micropollutants. In this study, the photoinduced and electrochemical decompositions of venlafaxine were investigated in terms of mechanism and efficacy using high-performance liquid chromatography coupled to high-resolution multifragmentation mass spectrometry. Kinetic analysis, structure elucidation, matrix variation, and radical scavenging indicated the dominance of a hydroxyl-mediated indirect mechanism during photodegradation and hydroxyl and direct electrochemical oxidation for electrochemical degradation. Oxidants, sulfate, and chloride ions acted as accelerants, which reduced venlafaxine half-lives from 62 to 25 min. Humic acid decelerated degradation during ultra-violet irradiation up to 50%, but accelerated during electrochemical oxidation up to 56%. In silico quantitative structure activity relationship analysis predicted decreased environmental hazard after advanced oxidation process treatment. In general, photoirradiation proved more efficient due to faster decomposition and slightly less toxic transformation products. Yet, matrix effects would have to be carefully evaluated when potential applications as a fourth purification stage were to be considered.

Visible-light photocatalytic activity of rare-earth-metal-doped TiO2: Experimental analysis and machine learning for virtual design

Modification with rare-earth (RE) metals has emerged as an important approach for enhancing the properties of titanium dioxide. Herein, the visible-light photocatalytic activity of RE-TiO2 (RE: Tm, Er, Nd, Dy, Lu, La, Ho, Pr, Tb, Sc, Ce, Yb, Sm, Gd, Y, or Eu) was investigated using a combination of computer simulations and experimental techniques. The RE-TiO2 photocatalysts were characterised using advanced experimental techniques, including X-ray diffraction, X-ray photoelectron spectroscopy, luminescence, diffuse reflectance spectroscopy, and specific surface area measurements. Furthermore, a quantitative structure–activity relationship analysis was conducted by applying a partial least-squares machine learning algorithm. The Ho-TiO2 sample exhibited the highest photocatalytic activity under visible-light irradiation. Notably, the observed activity was not due to an up-conversion process, originating instead from slight bandgap narrowing caused by new sub-bandgap states from the RE 4 f levels.

The substitution sites of hydroxyl and galloyl groups determine the inhibitory activity of human pancreatic α-amylase in twelve tea polyphenol monomers

Tea polyphenols have been reported as potential α-amylase inhibitors. However, the quantitative structure–activity relationship (QSAR) between tea polyphenols and human pancreas α-amylase (HPA) is not well understood. Herein, the inhibitory effect of twelve tea polyphenol monomers on HPA was investigated in terms of inhibitory activity, as well as QSAR analysis and interaction mechanism. The results revealed that the HPA inhibitory activity of theaflavins (TFs), especially theaflavin-3′-gallate (TF-3′-G, IC50: 0.313 mg/mL), was much stronger than that of catechins (IC50: 18.387–458.932 mg/mL). The QSAR analysis demonstrated that the determinant for the inhibitory activity of HPA was not the number of hydroxyl and galloyl groups in tea polyphenol monomers, while the substitution sites of these groups potentially might play a more important role in modulating the inhibitory activity. The inhibition kinetics and molecular docking revealed that TF-3′-G as a mixed-type inhibitor had the lowest inhibition constant and bound to the active sites of HPA with the lowest binding energy (−7.74 kcal/mol). These findings could provide valuable insights into the structures-activity relationships between tea polyphenols and the HPA inhibitors.

Synthesis of Acrylopimaric Acid Triazole Derivatives and Their Antioomycete Activity against Phytophthora capsici.

To develop new antioomycete agents against plant pathogens, two series of acrylopimaric acid triazole derivatives from rosin were synthesized. The in vitro antioomycete activity of these derivatives was evaluated and screened against Pseudoperonospora cubensisi, Plasmopara viticola, Phytophthora sojae, Phytophthora infestans, and Phytophthora capsici. Compound 5m showed the highest antioomycete activity against P. capsici, with a half-maximal effective concentration (EC50) value that was lower than that of the positive control metalaxyl (1.391 and 1.815 mg/L, respectively). Compound 5m demonstrated satisfactory protective and curative efficacy against P. capsici in pepper in in vivo antioomycete activity studies. Physiological and biochemical testing showed that the action mechanism of compound 5m on P. capsici involved altering the morphology and ultrastructure of the mycelium, increasing cell membrane permeability, inducing dysfunction of the nucleus and mitochondria, and ultimately causing cell necrosis. In addition, the analysis of three-dimensional quantitative structure-activity relationship (3D-QSAR) revealed the significance of the molecular structure and charge distribution in the interaction between compound 5m and its target. Collectively, these findings indicate that compound 5m has the potential as an antioomycete candidate.