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Search Results (7,593)

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Keywords = molecular docking

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24 pages, 1413 KiB  
Article
Cheminformatic Identification of Tyrosyl-DNA Phosphodiesterase 1 (Tdp1) Inhibitors: A Comparative Study of SMILES-Based Supervised Machine Learning Models
by Conan Hong-Lun Lai, Alex Pak Ki Kwok and Kwong-Cheong Wong
J. Pers. Med. 2024, 14(9), 981; https://doi.org/10.3390/jpm14090981 (registering DOI) - 15 Sep 2024
Abstract
Background: Tyrosyl-DNA phosphodiesterase 1 (Tdp1) repairs damages in DNA induced by abortive topoisomerase 1 activity; however, maintenance of genetic integrity may sustain cellular division of neoplastic cells. It follows that Tdp1-targeting chemical inhibitors could synergize well with existing chemotherapy drugs to deny cancer [...] Read more.
Background: Tyrosyl-DNA phosphodiesterase 1 (Tdp1) repairs damages in DNA induced by abortive topoisomerase 1 activity; however, maintenance of genetic integrity may sustain cellular division of neoplastic cells. It follows that Tdp1-targeting chemical inhibitors could synergize well with existing chemotherapy drugs to deny cancer growth; therefore, identification of Tdp1 inhibitors may advance precision medicine in oncology. Objective: Current computational research efforts focus primarily on molecular docking simulations, though datasets involving three-dimensional molecular structures are often hard to curate and computationally expensive to store and process. We propose the use of simplified molecular input line entry system (SMILES) chemical representations to train supervised machine learning (ML) models, aiming to predict potential Tdp1 inhibitors. Methods: An open-sourced consensus dataset containing the inhibitory activity of numerous chemicals against Tdp1 was obtained from Kaggle. Various ML algorithms were trained, ranging from simple algorithms to ensemble methods and deep neural networks. For algorithms requiring numerical data, SMILES were converted to chemical descriptors using RDKit, an open-sourced Python cheminformatics library. Results: Out of 13 optimized ML models with rigorously tuned hyperparameters, the random forest model gave the best results, yielding a receiver operating characteristics-area under curve of 0.7421, testing accuracy of 0.6815, sensitivity of 0.6444, specificity of 0.7156, precision of 0.6753, and F1 score of 0.6595. Conclusions: Ensemble methods, especially the bootstrap aggregation mechanism adopted by random forest, outperformed other ML algorithms in classifying Tdp1 inhibitors from non-inhibitors using SMILES. The discovery of Tdp1 inhibitors could unlock more treatment regimens for cancer patients, allowing for therapies tailored to the patient’s condition. Full article
(This article belongs to the Special Issue Artificial Intelligence Applications in Precision Oncology)
22 pages, 1397 KiB  
Article
A Bis(Acridino)-Crown Ether for Recognizing Oligoamines in Spermine Biosynthesis
by Péter Kisfaludi, Sára Spátay, Marcell Krekó, Panna Vezse, Tünde Tóth, Péter Huszthy and Ádám Golcs
Molecules 2024, 29(18), 4390; https://doi.org/10.3390/molecules29184390 (registering DOI) - 15 Sep 2024
Abstract
Oligoamines in cellular metabolism carry extremely diverse biological functions (i.e., regulating Ca2+-influx, neuronal nitric oxide synthase, membrane potential, Na+, K+-ATPase activity in synaptosomes, etc.). Furthermore, they also act as longevity agents and have a determinative role in [...] Read more.
Oligoamines in cellular metabolism carry extremely diverse biological functions (i.e., regulating Ca2+-influx, neuronal nitric oxide synthase, membrane potential, Na+, K+-ATPase activity in synaptosomes, etc.). Furthermore, they also act as longevity agents and have a determinative role in autophagy, cell growth, proliferation, and death, while oligoamines dysregulation is a key in a variety of cancers. However, many of their mechanisms of actions have just begun to be understood. In addition to the numerous biosensing methods, only a very few simple small molecule-based tests are available for their selective but reversible tracking or fluorescent labeling. Motivated by this, we present herein a new fluorescent bis(acridino)-crown ether as a sensor molecule for biogenic oligoamines. The sensor molecule can selectively distinguish oligoamines from aliphatic mono- and diamino-analogues, while showing a reversible 1:2 (host:guest) complexation with a stepwise binding process accompanied by a turn-on fluorescence response. Both computational simulations on molecular docking and regression methods on titration experiments were carried out to reveal the oligoamine-recognition properties of the sensor molecule. The new fluorescent chemosensor molecule has a high potential for molecular-level functional studies on the oligoamine systems in cell processes (cellular uptake, transport, progression in cancers, etc.). Full article
15 pages, 3407 KiB  
Article
In Vitro In Silico Screening Strategy and Mechanism of Novel Tyrosinase Inhibitory Peptides from Nacre of Hyriopsis cumingii
by Haisheng Lin, Fei Li, Jiaao Kang, Shaohe Xie, Xiaoming Qin, Jialong Gao, Zhongqin Chen, Wenhong Cao, Huina Zheng and Wenkui Song
Mar. Drugs 2024, 22(9), 420; https://doi.org/10.3390/md22090420 (registering DOI) - 15 Sep 2024
Abstract
For thousands of years, pearl and nacre powders have been important traditional Chinese medicines known for their skin whitening effects. To prepare the enzymatic hydrolysates of Hyriopsis cumingii nacre powder (NP-HCH), complex enzymatic hydrolysis by pineapple protease and of neutral protease was carried [...] Read more.
For thousands of years, pearl and nacre powders have been important traditional Chinese medicines known for their skin whitening effects. To prepare the enzymatic hydrolysates of Hyriopsis cumingii nacre powder (NP-HCH), complex enzymatic hydrolysis by pineapple protease and of neutral protease was carried out after the powder was pre-treated with a high-temperature and high-pressure method. The peptides were identified using LC-MS/MS and picked out through molecular docking and molecular dynamics simulations. Subsequently, the tyrosinase inhibitory and antioxidant properties of novel tyrosinase inhibitory peptides were investigated in vitro. In addition, the enzymatic activity of tyrosinase in B16F10 cells as well as melanin content and antioxidant enzyme levels were also examined. The results showed that a tyosinase inhibitory peptide (Tyr-Pro-Asn-Pro-Tyr, YPNPY) with an efficient IC50 value of 0.545 ± 0.028 mM was identified. The in vitro interaction results showed that YPNPY is a reversible competitive inhibitor of tyrosinase, suggesting that it binds to the free enzyme. The B16F10 cell whitening test revealed that YPNPY can reduce the melanin content of B16F10 cells by directly inhibiting the activity of intracellular tyrosinase. Additionally, it indirectly affects melanin production by acting as an antioxidant. These results suggest that YPNPY could be widely used as a tyrosinase inhibitor in whitening foods and drugs. Full article
(This article belongs to the Special Issue Marine Alkaloids: Sources, Discovery, Diversity, and Bioactivities)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>(<b>A</b>) Tyrosinase inhibitory activity of enzymatic hydrolysis product NP-HCH. (<b>B</b>) Antioxidant activity of enzymatic hydrolysis product NP-HCH. Different letters indicate that there are significant differences in data (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>A</b>) The 3D and 2D visualizations of molecular docking of YPNPY, GYHFHSYP, and YVPGHG with tyrosinase (2Y9X). (<b>a</b>–<b>f</b>). (<b>B</b>) The 3D and 2D visualizations of molecular docking of Kojic acid.</p>
Full article ">Figure 3
<p>Molecular dynamics results of tyrosinase with YPNPY, GYHFHSYP, and YVPGHG: (<b>A</b>) RMSD; (<b>B</b>) RMSF; (<b>C</b>) Rg; (<b>D</b>) SASA; and (<b>E</b>) Hbond number.</p>
Full article ">Figure 4
<p>Scavenging capacity of peptides for DPPH and ABTS free radicals. Different letters indicate that there are significant differences in data (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>(<b>A</b>) Plots of enzymatic reaction rate versus tyrosinase concentration. (<b>B</b>) Plots of Lineweaver–Burk; the secondary plots of slope and Y-intercept versus concentration of YPNPY are shown in the inset.</p>
Full article ">Figure 6
<p>Effects of YPNPY on cell viability.</p>
Full article ">Figure 7
<p>(<b>A</b>) Effects of YPNPY and Kojic acid on tyrosinase activity in B16F10 cells. (<b>B</b>) Effects of YPNPY and Kojic acid on melanin production in B16F10 cells. c (Kojic acid) = 50 μg/mL. Different letters indicate that there are significant differences in data (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 8
<p>Effect of YPNPY on the intracellular antioxidant capacity in B16F10 cells: (<b>A</b>) CAT; (<b>B</b>) GSH-Px; and (<b>C</b>) SOD. Concentration of Kojic acid = 50 μg/mL. Different letters indicate that there are significant differences in data (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">
12 pages, 2847 KiB  
Article
Computational Insights into the Radical Scavenging Activity and Xanthine Oxidase Inhibition of the Five Anthocyanins Derived from Grape Skin
by Xiao-Qin Lu, Jindong Li, Bin Wang and Shu Qin
Antioxidants 2024, 13(9), 1117; https://doi.org/10.3390/antiox13091117 (registering DOI) - 15 Sep 2024
Viewed by 62
Abstract
Anthocyanins, typical polyphenol compounds in grape skin, have attracted increasing interest due to their health-promoting properties. In this body of work, five representative anthocyanins (Cy-3-O-glc, Dp-3-O-glc, Pn-3-O-glc, Mv-3-O-glc, and Pt-3-O-glc) were studied using [...] Read more.
Anthocyanins, typical polyphenol compounds in grape skin, have attracted increasing interest due to their health-promoting properties. In this body of work, five representative anthocyanins (Cy-3-O-glc, Dp-3-O-glc, Pn-3-O-glc, Mv-3-O-glc, and Pt-3-O-glc) were studied using the density functional theory (DFT) to elucidate structure–radical scavenging activity in the relationship and the reaction path underlying the radical-trapping process. Based on thermodynamic parameters involved in HAT, SET-PT, and SPLET mechanisms, along with the structural attributes, it was found that the C4′ hydroxyl group mainly contributes to the radical scavenging activities of the investigated compounds. Pt-3-O-glc exhibits a good antioxidant capacity among the five compounds. The preferred radical scavenging mechanisms vary in different phases. For the Pt-3-O-glc compound, the calculations indicate the thermodynamically favoured product is benzodioxole, rather than o-quinone, displaying considerably reduced energy in double HAT mechanisms. Additionally, the thermodynamic and kinetic calculations indicate that the reaction of OH into the 4′-OH site of Pt-3-O-glc has a lower energy barrier (7.6 kcal/mol), a higher rate constant (5.72 × 109 M−1 s−1), and exhibits potent OH radical scavenging properties. Molecular docking results have shown the strong affinity of the studied anthocyanins with the pro-oxidant enzyme xanthine oxidase, displaying their significant role in inhibiting ROS formation. Full article
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Figure 1

Figure 1
<p>Basis structure and atom numbering sites of anthocyanin and chemical structures of five anthocyanins derived from grape skin.</p>
Full article ">Figure 2
<p>Double HAT mechanism of Pt-3-<span class="html-italic">O</span>-glc in the gas phase and solvents (unit: kcal/mol).</p>
Full article ">Figure 3
<p>The PESs of reaction between Pt-3-<span class="html-italic">O</span>-glc and <sup>•</sup>OH via HAT pathway in the gas phase. The distances are shown in blue (unit: Å). The gray, red, and white balls represent the elements C, O, and H, respectively.</p>
Full article ">Figure 4
<p>The 3D and 2D interactions of the Pt-3-<span class="html-italic">O</span>-glc with XO, along with the corresponding binding poses.</p>
Full article ">
14 pages, 5606 KiB  
Article
Enantioselectivity in Vanadium-Dependent Haloperoxidases of Different Marine Sources for Sulfide Oxidation to Sulfoxides
by Yun-Han Zhang, Ya-Ting Zou, Yong-Yi Zeng, Lan Liu and Bi-Shuang Chen
Mar. Drugs 2024, 22(9), 419; https://doi.org/10.3390/md22090419 (registering DOI) - 14 Sep 2024
Viewed by 188
Abstract
This study explores the reasons behind the variations in the enantioselectivity of the sulfoxidation of methyl phenyl sulfide by marine-derived vanadium-dependent haloperoxidases (VHPOs). Twelve new VHPOs of marine organisms were overexpressed, purified, and tested for their ability to oxidize sulfide. Most of these [...] Read more.
This study explores the reasons behind the variations in the enantioselectivity of the sulfoxidation of methyl phenyl sulfide by marine-derived vanadium-dependent haloperoxidases (VHPOs). Twelve new VHPOs of marine organisms were overexpressed, purified, and tested for their ability to oxidize sulfide. Most of these marine enzymes exhibited nonenantioselective behavior, underscoring the uniqueness of AnVBPO from the brown seaweed Ascophyllum nodosum and CpVBPO from the red seaweed Corallina pilulifera, which produce (R)- and (S)-sulfoxides, respectively. The enantioselective sulfoxidation pathway is likely due to direct oxygen transfer within the VHPO active site. This was demonstrated through molecular docking and molecular dynamics simulations, which revealed differences in the positioning of sulfide within AnVBPO and CpVBPO, thus explaining their distinct enantioselectivities. Nonenantioselective VHPOs probably follow a different oxidation pathway, initiating with sulfide oxidation to form a positively charged radical. Further insights were gained from studying the catalytic effect of VO43− on H2O2-driven sulfoxidation. This research improves the understanding of VHPO-mediated sulfoxidation and aids in developing biocatalysts for sulfoxide synthesis. Full article
(This article belongs to the Special Issue Advances of Marine-Derived Enzymes)
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Figure 1

Figure 1
<p>The information of the newly discovered 12 VHPOs: (<b>a</b>) VHPOs selected from public databases, revealing their origin and similarity to probe enzymes; (<b>b</b>) VHPOs in sequence similarity networks (SSNs); (<b>c</b>) SDS-PAGE analysis of the overexpression of the newly discovered VHPOs in <span class="html-italic">E. coli</span>.</p>
Full article ">Figure 2
<p>The results of the oxidation of methyl phenyl sulfide catalyzed by newly discovered VHPOs compared to those of <span class="html-italic">An</span>VBPO/<span class="html-italic">Cp</span>VBPO/<span class="html-italic">Ci</span>VCPO. Reaction conditions: [methyl phenyl sulfide] = 5 mM (500 mM stock in acetonitrile), [H<sub>2</sub>O<sub>2</sub>] = 10 mM, [VHPO] = 1 μM in sodium acetate (100 mM, pH of 6.0) for 16 h at 30 °C. Note: for the reaction of <span class="html-italic">Cc</span>VCPO and <span class="html-italic">Et</span>VCPO, PBS buffer (100 mM, pH of 6.5) was used. <span class="html-italic">An</span>VBPO and <span class="html-italic">Cp</span>VBPO yielded (<span class="html-italic">R</span>)- and (<span class="html-italic">S</span>)-products, respectively. The data shown are the results from duplicate experiments. (For reactions exhibiting negligible enantioselectivity, a uniform ee value is adopted in the bar graphs to account for the analytical error associated with liquid chromatography, which is approximately 5%). %ee means enantiomeric excess (<math display="inline"><semantics> <mrow> <mi mathvariant="normal">%</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">e</mi> <mo>=</mo> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi mathvariant="normal">R</mi> </mrow> </mfenced> <mo>−</mo> <mo>[</mo> <mi mathvariant="normal">S</mi> <mo>]</mo> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi mathvariant="normal">R</mi> </mrow> </mfenced> <mo>+</mo> <mo>[</mo> <mi mathvariant="normal">S</mi> <mo>]</mo> </mrow> </mfrac> </mstyle> </mrow> </semantics></math> or <math display="inline"><semantics> <mrow> <mi mathvariant="normal">%</mi> <mi mathvariant="normal">e</mi> <mi mathvariant="normal">e</mi> <mo>=</mo> <mstyle scriptlevel="0" displaystyle="true"> <mfrac> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi mathvariant="normal">S</mi> </mrow> </mfenced> <mo>−</mo> <mo>[</mo> <mi mathvariant="normal">R</mi> <mo>]</mo> </mrow> <mrow> <mfenced open="[" close="]" separators="|"> <mrow> <mi mathvariant="normal">R</mi> </mrow> </mfenced> <mo>+</mo> <mo>[</mo> <mi mathvariant="normal">S</mi> <mo>]</mo> </mrow> </mfrac> </mstyle> </mrow> </semantics></math>).</p>
Full article ">Figure 3
<p>Binding of methyl phenyl sulfoxide to <span class="html-italic">An</span>VBPO. (<b>a</b>,<b>b</b>) The binding of MPS on the hydrophilic and hydrophobic surface of <span class="html-italic">An</span>VBPO and <span class="html-italic">Cp</span>VBPO, with blue and orange regions representing the hydrophilic and hydrophobic regions of the protein surface, respectively; (<b>c</b>,<b>d</b>) The two-dimensional binding mode of MPS-<span class="html-italic">An</span>VBPO and MPS-<span class="html-italic">Cp</span>VBPO, with red gears indicating hydrophobic interactions; (<b>e</b>,<b>f</b>) The three-dimensional binding mode of MPS-<span class="html-italic">An</span>VBPO and MPS-<span class="html-italic">Cp</span>VBPO, with purple dashed lines indicating the π-π interaction distance; the red dashed line represents the distance between catalytic atoms.</p>
Full article ">Figure 4
<p>Comparative analysis of the binding of MPS molecules at the active sites of <span class="html-italic">An</span>VBPO and <span class="html-italic">Cp</span>VBPO.</p>
Full article ">Figure 5
<p>Molecular dynamics (MD) simulations analysis. Backbone RMSD (<b>a</b>); Backbone Rg (<b>b</b>); Total SASA (<b>c</b>); The change in catalytic atomic distance between MPS and VO<sub>4</sub><sup>3−</sup> (<b>d</b>); The change in binding energy between MPS and the protein (<b>e</b>) versus simulation time.</p>
Full article ">Figure 6
<p>The distribution of root mean square fluctuation (RMSF) for both systems (<b>a</b>,<b>c</b>) and the corresponding regions exhibiting notable alterations in protein structure (<b>b</b>,<b>d</b>).</p>
Full article ">Figure 7
<p>The oxidation of sulfides to sulfoxides with H<sub>2</sub>O<sub>2</sub> catalyzed by Na<sub>3</sub>VO<sub>4</sub>. Reaction conditions of sulfides to sulfoxides: [sulfide] = 5 mM, [H<sub>2</sub>O<sub>2</sub>] = 10 mM, [Na<sub>3</sub>VO<sub>4</sub>] = 10 mM in 1 mL sodium acetate buffer (100 mM, pH of 6.0), 30 °C for 6 h. Triplicate experiments were performed and the average values are shown. Different product derivatives and their yields are shown.</p>
Full article ">Scheme 1
<p>Proposed enantioselective oxidation pathway of direct oxygen transfer to the sulfur atom.</p>
Full article ">Scheme 2
<p>Proposed nonenantioselective oxidation pathway of initiating with sulfide oxidation to form a positively charged radical, which migrates from the enzyme and is subsequently converted to the product via chemical steps.</p>
Full article ">
30 pages, 5738 KiB  
Article
The Counterion (SO42− and NO3) Effect on Crystallographic, Quantum-Chemical, Protein-, and DNA-Binding Properties of Two Novel Copper(II)–Pyridoxal-Aminoguanidine Complexes
by Violeta Jevtovic, Luka Golubović, Odeh A. O. Alshammari, Munirah Sulaiman Alhar, Tahani Y. A. Alanazi, Violeta Rakic, Rakesh Ganguly, Jasmina Dimitrić Marković, Aleksandra Rakić and Dušan Dimić
Crystals 2024, 14(9), 814; https://doi.org/10.3390/cryst14090814 (registering DOI) - 14 Sep 2024
Viewed by 171
Abstract
New Cu(II) complexes with pyridoxal-aminoguanidine (PLAG) ligands and different counterions (SO42− and NO3) were prepared and their crystal structures were solved by the X-ray crystallography. The geometries of the obtained complexes significantly depended on the counterions, leading to [...] Read more.
New Cu(II) complexes with pyridoxal-aminoguanidine (PLAG) ligands and different counterions (SO42− and NO3) were prepared and their crystal structures were solved by the X-ray crystallography. The geometries of the obtained complexes significantly depended on the counterions, leading to the square-pyramidal structure of [Cu(PLAG)NO3H2O]NO3 (complex 1) and square-planar structure of [Cu(PLAG)H2O]SO4 (complex 2). The intermolecular interactions were examined using the Hirshfeld surface analysis. The theoretical structures of these complexes were obtained by optimization at the B3LYP/6-311++G(d,p)(H,C,N,O,S)/LanL2DZ(Cu) level of theory. The Quantum Theory of Atoms in Molecules (QTAIM) was applied to assess the strength and type of the intramolecular interactions and the overall stability of the structures. The interactions between the complexes and transport proteins (human serum albumin (HSA)) and calf thymus DNA (CT-DNA) were examined by spectrofluorometric/spectrophotometric titration and molecular docking. The binding mechanism to DNA was assessed by potassium iodide quenching experiments. The importance of counterions for binding was shown by comparing the experimental and theoretical results and the examination of binding at the molecular level. Full article
24 pages, 11508 KiB  
Article
Discovery and Optimization of Ergosterol Peroxide Derivatives as Novel Glutaminase 1 Inhibitors for the Treatment of Triple-Negative Breast Cancer
by Ran Luo, Haoyi Zhao, Siqi Deng, Jiale Wu, Haijun Wang, Xiaoshan Guo, Cuicui Han, Wenkang Ren, Yinglong Han, Jianwen Zhou, Yu Lin and Ming Bu
Molecules 2024, 29(18), 4375; https://doi.org/10.3390/molecules29184375 (registering DOI) - 14 Sep 2024
Viewed by 178
Abstract
In this study, novel ergosterol peroxide (EP) derivatives were synthesized and evaluated to assess their antiproliferative activity against four human cancer cell lines (A549, HepG2, MCF-7, and MDA-MB-231). Compound 3g exhibited the most potent antiproliferative activity, with an IC50 value of 3.20 [...] Read more.
In this study, novel ergosterol peroxide (EP) derivatives were synthesized and evaluated to assess their antiproliferative activity against four human cancer cell lines (A549, HepG2, MCF-7, and MDA-MB-231). Compound 3g exhibited the most potent antiproliferative activity, with an IC50 value of 3.20 µM against MDA-MB-231. This value was 5.4-fold higher than that of the parental EP. Bioassay optimization further identified 3g as a novel glutaminase 1 (GLS1) inhibitor (IC50 = 3.77 µM). In MDA-MB-231 cells, 3g reduced the cellular glutamate levels by blocking the glutamine hydrolysis pathway, which triggered reactive oxygen species production and induced caspase-dependent apoptosis. Molecular docking indicated that 3g interacts with the reaction site of the variable binding pocket by forming multiple interactions with GLS1. In a mouse model of breast cancer, 3g showed remarkable therapeutic effects at a dose of 50 mg/kg, with no apparent toxicity. Based on these results, 3g could be further evaluated as a novel GLS1 inhibitor for triple-negative breast cancer (TNBC) therapy. Full article
(This article belongs to the Special Issue Bioactivity of Natural Compounds: From Plants to Humans)
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Figure 1

Figure 1
<p>Design of GLS1 inhibitors based on the EP and BPTES binding groups.</p>
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<p>The inhibitory effect of compound <b>3g</b> on GLS1 activity in MDA-MB-231 cells. (<b>A</b>) A GLS1 inhibitor screening kit was utilized to detect the GLS1 levels of EP, <b>3g</b>, and BPTES. (<b>B</b>) After treating MDA-MB-231 cells with different concentrations of <b>3g</b> for 48 h, the expression of the GLS1 protein was detected by Western blot. (<b>C</b>) Quantitative analysis. The data are expressed as the mean ± SD (<span class="html-italic">n</span> = 3), *** <span class="html-italic">p</span> &lt; 0.001, compared with the control group.</p>
Full article ">Figure 3
<p>Compound <b>3g</b> inhibited the proliferation of MDA-MB-231 cells. (<b>A</b>) Compound <b>3g</b> inhibited the colony formation of MDA-MB-231 cells. (<b>B</b>) Clonogenic suppression expressed as a percentage relative to the vehicle-treated controls. Data represent the mean ± SD (<span class="html-italic">n</span> = 3), ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared with the control group.</p>
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<p>Compound <b>3g</b> induced apoptosis of MDA-MB-231 cells. (<b>A</b>) MDA-MB-231 cells were treated with different concentrations of <b>3g</b> for 48 h; then, the cells were fixed and stained with Annexin V-FITC/PI and analyzed via flow cytometry. Annexin V-FITC and PI data are expressed as percentages (%) for each quadrant. (<b>B</b>) The apoptosis rate was quantitatively detected. (<b>C</b>) Western blot analysis. MDA-MB-MB-231 cells were treated with different concentrations of <b>3g</b> for 48 h, and the protein expressions of Bcl-2, Bax, Cyt C, caspase-9, cleaved caspase-9, caspase-3, and cleaved caspase-3 were detected via Western blot. (<b>D</b>) Quantitative analysis. Data represent the means ± SD (<span class="html-italic">n</span> = 3), ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared with the control group.</p>
Full article ">Figure 5
<p>The effect of compound <b>3g</b> and EP on the glutamate levels in MDA-MB-231 cells. MDA-MB-231 cells were treated with different concentrations of <b>3g</b> (2, 4, and 8 μM) and EP for 48 h. The changes in the glutamate levels of MDA-MB-231 cells were detected by using a glutamate kit. Data represent the means ± SD (<span class="html-italic">n</span> = 3), ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared with the control group.</p>
Full article ">Figure 6
<p>Compound <b>3g</b> induced an increase in the ROS levels in MDA-MB-231 cells. MDA-MB-231 cells were subjected to treatment with <b>3g</b> and EP at different concentrations for 48 h. (<b>A</b>) Fluorescence microscopy image of intracellular ROS production in MDA-MB-231 cells stained with DCFH-DA (green). (<b>B</b>) Quantification of ROS levels by flow cytometry. (<b>C</b>) Quantitative analysis. Data represent the means ± SD (<span class="html-italic">n</span> = 3), ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared with the control group.</p>
Full article ">Figure 7
<p>The eutectic structure of compound <b>3g</b> with GLS1 (PDB ID: 3UO9). (<b>A</b>) Modeled and enlarged close-up of the surface mosaic of the GLS1 tetramer and <b>3g</b> binding. (<b>B</b>) Close-up of the <b>3g</b> interactions in the GLS1 allosteric binding pocket. Here, <b>3g</b> is rendered as a rod and colored according to the atom type. Green denotes carbon, blue denotes nitrogen, and red denotes oxygen. The key residual atoms in GLS1 that interacted with the compound are denoted in cyan. The red dashed lines indicate hydrogen bonds, and the numbers are the hydrogen bond lengths.</p>
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<p>Compound <b>3g</b> inhibited the growth of 4T1 cells in vivo. (<b>A</b>) Tumor images of 4T1 tumor-bearing mice treated with <b>3g</b> or BPTES; and (<b>B</b>) tumor HE staining. Scale = 50 μm. (<b>C</b>) Changes in the tumor volume; (<b>D</b>) tumor weight; and (<b>E</b>) body weight of 4T1 tumor-bearing mice. Data represent the mean ± SD (<span class="html-italic">n</span> = 6), * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared with the control group. Scale = 50 μm.</p>
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<p>The effect of compound <b>3g</b> on organ damage in model mice. The hearts, livers, spleens, lungs, and kidneys of the mice were harvested and sectioned for HE staining. Scale bars = 50 μm.</p>
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<p>Synthesis of EP derivatives (<b>1a</b>–<b>h</b>, <b>2a</b>–<b>h</b>, <b>3a</b>–<b>h</b>, and <b>4a</b>–<b>h</b>). Reagents and conditions: (i) Et<sub>3</sub>N, CH<sub>2</sub>Cl<sub>2</sub>, SA (A), MA (B), GA (C), or PA (D), reflux, 24 h, 76–85%; and (ii) R<sub>2</sub>-H, HOBT·H<sub>2</sub>O, EDCI·HCl, pyridine, DMF, room temperature, 12–48 h, 77–88%.</p>
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18 pages, 3874 KiB  
Article
Baicalin Inhibits FIPV Infection In Vitro by Modulating the PI3K-AKT Pathway and Apoptosis Pathway
by Zhongda Cao, Nannan Ma, Maoyang Shan, Shiyan Wang, Jige Du, Jia Cheng, Panpan Sun, Na Sun, Lin Jin, Kuohai Fan, Wei Yin, Hongquan Li, Chunsheng Yin and Yaogui Sun
Int. J. Mol. Sci. 2024, 25(18), 9930; https://doi.org/10.3390/ijms25189930 (registering DOI) - 14 Sep 2024
Viewed by 290
Abstract
Feline infectious peritonitis (FIP), a serious infectious disease in cats, has become a challenging problem for pet owners and the industry due to the lack of effective vaccinations and medications for prevention and treatment. Currently, most natural compounds have been proven to have [...] Read more.
Feline infectious peritonitis (FIP), a serious infectious disease in cats, has become a challenging problem for pet owners and the industry due to the lack of effective vaccinations and medications for prevention and treatment. Currently, most natural compounds have been proven to have good antiviral activity. Hence, it is essential to develop efficacious novel natural compounds that inhibit FIPV infection. Our study aimed to screen compounds with in vitro anti-FIPV effects from nine natural compounds that have been proven to have antiviral activity and preliminarily investigate their mechanisms of action. In this study, the CCK-8 method was used to determine the maximum noncytotoxic concentration (MNTC), 50% cytotoxic concentration (CC50), and 50% effective concentration (EC50) of natural compounds on CRFK cells and the maximum inhibition ratio (MIR) of the compounds inhibit FIPV. The effect of natural compounds on FIPV-induced apoptosis was detected via Annexin V-FITC/PI assay. Network pharmacology (NP), molecular docking (MD), and 4D label-free quantitative (4D-LFQ) proteomic techniques were used in the joint analysis the mechanism of action of the screened natural compounds against FIPV infection. Finally, Western blotting was used to validate the analysis results. Among the nine natural compounds, baicalin had good antiviral effects, with an MIR > 50% and an SI > 3. Baicalin inhibited FIPV-induced apoptosis. NP and MD analyses showed that AKT1 was the best target of baicalin for inhibiting FIPV infection. 4D-LFQ proteomics analysis showed that baicalin might inhibit FIPV infection by modulating the PI3K-AKT pathway and the apoptosis pathway. The WB results showed that baicalin promoted the expression of EGFR, PI3K, and Bcl-2 and inhibited the expression of cleaved caspase 9 and Bax. This study found that baicalin regulated the PI3K-AKT pathway and the apoptosis pathway in vitro and inhibited FIPV-induced apoptosis, thus exerting anti-FIPV effects. Full article
(This article belongs to the Section Molecular Pharmacology)
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<p>These compounds inhibited FIPV infection: (<b>A</b>) inhibition rate of the compounds against FIPV infection; (<b>B</b>) concentration-inhibition curve of FIPV treated with baicalin; (<b>C</b>) concentration-inhibition curve of FIPV treated with GS-441524. The data are represented as the mean ± SEM (<span class="html-italic">n</span> = 3). Different lowercase letters (a–e) indicate significant differences between groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>The impact of baicalin on FIPV replication, adsorption, and its direct inactivation of FIPV: (<b>A</b>) the effect of baicalin on FIPV replication; (<b>B</b>) the effect of baicalin on FIPV adsorption; (<b>C</b>) results of direct inactivation of FIPV by baicalin. The data are represented as the mean ± SEM (<span class="html-italic">n</span> = 3). Different lowercase letters (a–d) indicate significant differences between groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of baicalin on FIPV-induced apoptosis: (<b>A</b>) results of fluorescence microscopy observation with a magnification of 100×; (<b>B</b>) results of comparison of fluorescence intensity per unit area of cells. C: cell control group; F: virus control group; T: baicalin-treated group. The data are represented as the mean ± SEM (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>(<b>A</b>) Venn diagram of baicalin target-FIPV targets; (<b>B</b>) PPI network of potential targets; (<b>C</b>) Sankey bubble plot of GO functional enrichment results; (<b>D</b>) Sankey bubble plot of KEGG pathway enrichment results; (<b>E</b>) results of topological analysis; (<b>F</b>) results of molecular docking binding free energy and number of hydrogen bonds; (<b>G1</b>,<b>H1</b>) overall maps of baicalin docked with AKT1 and ESR1, respectively; (<b>G2</b>,<b>H2</b>) local maps of baicalin docked with AKT1 and ESR1, respectively.</p>
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<p>(<b>A</b>) results of viral load in cells treated with baicalin for different durations. (<b>B</b>) KEGG pathway enrichment bubble map. (<b>C</b>) Heatmap and fold change map of the PI3K-AKT signaling pathway and apoptosis pathway. (<b>D</b>) Volcano plots of DEPs in the three comparative groups of FIPV/control, treatment/control, and treatment/FIPV, in which the key proteins EGFR, PIK3CA, AKT1, AKT2, AKT3, CASP9, BLC2L, and BAX in the PI3K-AKT signaling pathway and apoptosis pathway were locally annotated with green dots. (<b>E</b>) 4D-LFQ proteomics quantitative analysis results of the key proteins in the PI3K-AKT signaling pathway and apoptosis pathway: EGFR, PIK3CA, AKT1, AKT2, AKT3, CASP9, BLC2L1, and BAX. The red boxes are the focus of this research. The data are represented as the mean ± SEM (<span class="html-italic">n</span> = 2–3). Different lowercase letters (a–c) and “*” indicate significant differences between groups, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Identification of key proteins in the PI3K-AKT signaling pathway and apoptosis pathway by WB. (<b>A</b>) WB protein bands of EGFR, PI3K, AKT, C-caspase 9, Bcl-2, Bax, and GAPDH; (<b>B</b>) WB quantitative analysis of EGFR, PI3K, AKT, C-caspase 9, Bcl-2, and Bax relative to GAPDH; and results of Bcl-2/Bax relative expression. The data are represented as the mean ± SEM, <span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Results of proteomic analysis: (<b>A</b>) Venn diagram of proteins detected in control, treatment, and FIPV groups; (<b>B</b>) DEPs among the treatment/FIPV, treatment/control and FIPV/control groups; (<b>C</b>) DEP clustering results of groups C, F, and T. Control or C is the cell control group; treatment or T is the baicalin-treated group; and FIPV or F is the viral control group, the same as below. (<b>D</b>) GO functional enrichment results.</p>
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20 pages, 10282 KiB  
Article
Molecular Integrative Study on Inhibitory Effects of Pentapeptides on Polymerization and Cell Toxicity of Amyloid-β Peptide (1–42)
by Lianmeng Ye, Nuela Manka’a Che Ajuyo, Zhongyun Wu, Nan Yuan, Zhengpan Xiao, Wenyu Gu, Jiazheng Zhao, Yechun Pei, Yi Min and Dayong Wang
Curr. Issues Mol. Biol. 2024, 46(9), 10160-10179; https://doi.org/10.3390/cimb46090606 (registering DOI) - 14 Sep 2024
Viewed by 138
Abstract
Alzheimer’s Disease (AD) is a multifaceted neurodegenerative disease predominantly defined by the extracellular accumulation of amyloid-β (Aβ) peptide. In light of this, in the past decade, several clinical approaches have been used aiming at developing peptides for therapeutic use in AD. The use [...] Read more.
Alzheimer’s Disease (AD) is a multifaceted neurodegenerative disease predominantly defined by the extracellular accumulation of amyloid-β (Aβ) peptide. In light of this, in the past decade, several clinical approaches have been used aiming at developing peptides for therapeutic use in AD. The use of cationic arginine-rich peptides (CARPs) in targeting protein aggregations has been on the rise. Also, the process of peptide development employing computational approaches has attracted a lot of attention recently. Using a structure database containing pentapeptides made from 20 L-α amino acids, we employed molecular docking to sort pentapeptides that can bind to Aβ42, then performed molecular dynamics (MD) analyses, including analysis of the binding stability, interaction energy, and binding free energy to screen ligands. Transmission electron microscopy (TEM), circular dichroism (CD), thioflavin T (ThT) fluorescence detection of Aβ42 polymerization, MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) assay, and the flow cytometry of reactive oxygen species (ROS) were carried out to evaluate the influence of pentapeptides on the aggregation and cell toxicity of Aβ42. Two pentapeptides (TRRRR and ARRGR) were found to have strong effects on inhibiting the aggregation of Aβ42 and reducing the toxicity of Aβ42 secreted by SH-SY5Y cells, including cell death, reactive oxygen species (ROS) production, and apoptosis. Full article
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<p>Molecular docking of the five pentapeptides with Aβ<sub>42</sub>. (<b>A</b>) Binding of TRRRR with Aβ<sub>42</sub>. (<b>B</b>) Binding of RRRWR with Aβ<sub>42</sub>. (<b>C</b>) Binding of RRRDS with Aβ<sub>42</sub>. (<b>D</b>) Binding of ARRGR with Aβ<sub>42</sub>. (<b>E</b>) Binding of TRRAR with Aβ<sub>42</sub>. For clarity, only three strands taken from Aβ<sub>42</sub> pentamer are shown in this figure. The magenta mesh represents the molecular surface of the pentapeptides, and the gray mesh represents the boundary of van der Waal’s force. Arrows indicate the hydrogen bonds. TRRRR: Threonine-arginine-arginine-arginine-arginine; RRRWR: Arginine-arginine-arginine-tryptophan-arginine; RRRDS: Arginine-arginine-arginine-aspartic acid-serine; ARRGR: Alanine-arginine-arginine-glycine-arginine; TRRAR: Threonine-arginine-arginine-alanine-arginine.</p>
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<p>The binding stability and interaction energy of the pentapeptides at different hydrophobic regions. (<b>A</b>) The binding stability of pentapeptides to Aβ<sub>42</sub> pentamer. (<b>B</b>) The interaction energy between Aβ<sub>42</sub> pentamer and the pentapeptides. RMSD: The root mean square deviation of the positions of the heavy elements of a pentapeptide. The interaction energy is the algebraic sum of Lennard-Jones and Coulombic potential energy. TRRRR: Threonine-arginine-arginine-arginine-arginine; RRRWR: Arginine-arginine-arginine-tryptophan-arginine; RRRDS: Arginine-arginine-arginine-aspartic acid-serine; ARRGR: Alanine-arginine-arginine-glycine-arginine; TRRAR: Threonine-arginine-arginine-alanine-arginine.</p>
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<p>Variation in the lengths of hydrogen bonds formed between the pentapeptides and Aβ<sub>42</sub>. (<b>A</b>) ARRGR and Aβ<sub>42</sub>. (<b>B</b>) RRRDS and Aβ<sub>42</sub>. (<b>C</b>) RRRWR and Aβ<sub>42</sub>. (<b>D</b>) TRRAR and Aβ<sub>42</sub>. (<b>E</b>) TRRRR and Aβ<sub>42</sub>. TRRRR: Threonine-arginine-arginine-arginine-arginine; RRRWR: Arginine-arginine-arginine-tryptophan-arginine; RRRDS: Arginine-arginine-arginine-aspartic acid-serine; ARRGR: Alanine-arginine-arginine-glycine-arginine; TRRAR: Threonine-arginine-arginine-alanine-arginine.</p>
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<p>Variation in the angles of hydrogen bonds formed the pentapeptides and Aβ<sub>42</sub>. (<b>A</b>) <b>A</b>RRGR and Aβ<sub>42</sub>. (<b>B</b>) RRRDS and Aβ<sub>42</sub>. (<b>C</b>) RRRWR and Aβ<sub>42</sub>. (<b>D</b>) TRRAR and Aβ<sub>42</sub>. (<b>E</b>) TRRRR and Aβ<sub>42</sub>. TRRRR: Threonine-arginine-arginine-arginine-arginine; RRRWR: Arginine-arginine-arginine-tryptophan-arginine; RRRDS: Arginine-arginine-arginine-aspartic acid-serine; ARRGR: Alanine-arginine-arginine-glycine-arginine; TRRAR: Threonine-arginine-arginine-alanine-arginine.</p>
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<p>Binding free energy between the pentapeptides and Aβ<sub>42</sub>. (<b>A</b>) TRRRR and Aβ<sub>42</sub>. (<b>B</b>) RRRDS and Aβ<sub>42</sub>. (<b>C</b>) ARRGR and Aβ<sub>42</sub>. (<b>D</b>) RRRWR and Aβ<sub>42</sub>. (<b>E</b>) TRRAR and Aβ<sub>42</sub>. TRRRR: Threonine-arginine-arginine-arginine-arginine; RRRWR: Arginine-arginine-arginine-tryptophan-arginine; RRRDS: Arginine-arginine-arginine-aspartic acid-serine; ARRGR: Alanine-arginine-arginine-glycine-arginine; TRRAR: Threonine-arginine-arginine-alanine-arginine.</p>
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<p>Effects of pentapeptides on aggregation of Aβ<sub>42</sub> detected by ThT fluorescence assay. Results are expressed as means ± SD, <span class="html-italic">p</span> &lt; 0.01 among groups, tested by two-way ANOVA, n = 5.</p>
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<p>Effect of pentapeptides on aggregation of Aβ<sub>42</sub> detected by transmission electron microscopy. (<b>A</b>) Transmission electron microscopic images of 10 μM Aβ<sub>42</sub> before incubation. (<b>B</b>) The Atomic Fraction of Aβ<sub>42</sub> detected by HAADF-STEM imaging. (<b>C</b>) Transmission electron microscopic images of 10 μM Aβ<sub>42</sub> incubated for 48 h. (<b>D</b>) Transmission electron microscopic images of 10 μM Aβ<sub>42</sub> co-incubated with 40 μM TRRRR for 48 h. (<b>E</b>) Transmission electron microscopic image of 10 μM Aβ<sub>42</sub> co-incubated with 40 μM ARRGR for 48 h.</p>
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<p>Effects of TRRRR and ARRGR on Aβ<sub>42</sub> protein expression. Aβ<sub>42</sub><sup>–</sup>: SH-SY5Y cells not secreting Aβ<sub>42</sub>; Aβ<sub>42</sub><sup>+</sup>: SH-SY5Y cells secreting Aβ<sub>42</sub>. The results are expressed as means ± SD; ns: insignificant; ** <span class="html-italic">p</span> &lt; 0.01; the results were analyzed by one-way ANOVA, followed by the Tukey–Kramer test for multiple comparisons, with n = 3.</p>
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<p>Effects of TRRRR and ARRGR against cell toxicity of Aβ<sub>42</sub> secreted from SH-SY5Y. (<b>A</b>) The morphology of SH-SY5Y cells secreting Aβ<sub>42</sub>. Round-shaped cells with a bright edge are dying or dead. (<b>B</b>) Damaged cells detected with ethidium bromide, a nuclei acid tracer that cannot pass through an intact cell membrane. (<b>C</b>) Quantification of cell damage by using Image J. Results are expressed as means ± SD with ** <span class="html-italic">p</span> &lt; 0.01, and were analyzed by one-way ANOVA, followed by the Tukey–Kramer test for multiple comparisons, n = 3; ns: insignificant. In (<b>A</b>,<b>B</b>): (<b>a</b>) SH-SY5Y control cells that do not secrete Aβ<sub>42</sub>. (<b>b</b>) The control cells treated with TRRRR at 50 μM. (<b>c</b>) The control cells treated with ARRGR at 50 μM. (<b>d</b>) SH-SY5Y cells secreting Aβ<sub>42</sub>. (<b>e</b>) Aβ<sub>42</sub>-secreting SH-SY5Y cells treated with 10 μM TRRRR. (<b>f</b>) Aβ<sub>42</sub>-secreting SH-SY5Y cells treated with 10 μM ARRGR. (<b>g</b>) Aβ<sub>42</sub>-secreting SH-SY5Y cells treated with 50 μM TRRRR. (<b>h</b>) Aβ<sub>42</sub>-secreting SH-SY5Y cells treated with 50 μM ARRGR.</p>
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<p>Effects of the pentapeptides on ROS levels in SH-SY5Y cells secreting Aβ<sub>42</sub>. (<b>A</b>) ROS levels in the SH-SY5Y control cells that do not secrete Aβ<sub>42</sub>. (<b>B</b>) ROS levels in the control cells treated with 50 μM TRRRR. (<b>C</b>) ROS levels in the control cells treated with 50 μM ARRGR. (<b>D</b>) ROS levels in SH-SY5Y cells secreting Aβ<sub>42</sub>. (<b>E</b>) ROS levels in the Aβ<sub>42</sub>-secreting cells treated with 10 μM TRRRR. (<b>F</b>) ROS levels in the Aβ<sub>42</sub>-secreting cells treated with 10 μM ARRGR. (<b>G</b>) ROS levels in the Aβ<sub>42</sub>-secreting cells treated with 50 μM TRRRR. (<b>H</b>) ROS levels in the Aβ<sub>42</sub>-secreting cells treated with 50 μM ARRGR. (<b>I</b>) Overlay of the flow cytometry plots (<b>A</b>–<b>H</b>). (<b>J</b>) Quantification of the ROS levels in the cells. Results are expressed as means ± SD, ns: not significant, ** <span class="html-italic">p</span> &lt; 0.01, by one-way ANOVA, followed by the Tukey–Kramer test for multiple comparisons, with n = 3.</p>
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<p>Effects of pentapeptide on apoptosis of SY-SY5Y cells secreting Aβ<sub>42</sub>. (<b>A</b>) Apoptosis in the SH-SY5Y control cells that do not secrete Aβ<sub>42</sub>. (<b>B</b>) Apoptosis in the control cells treated with 50 μM TRRRR. (<b>C</b>) Apoptosis in the control cells treated with 50 μM ARRGR. (<b>D</b>) Apoptosis in SH-SY5Y cells secreting Aβ<sub>42</sub>. (<b>E</b>) Apoptosis in the Aβ<sub>42</sub>-secreting cells treated with 10 μM TRRRR. (<b>F</b>) Apoptosis in the Aβ<sub>42</sub>-secreting cells treated with 10 μM ARRGR. (<b>G</b>) Apoptosis in the Aβ<sub>42</sub>-secreting cells treated with 50 μM TRRRR. (<b>H</b>) Apoptosis in the Aβ<sub>42</sub>-secreting cells treated with 50 μM ARRGR. (<b>I</b>) Overlay of the flow cytometry plots (<b>A</b>–<b>H</b>). (<b>J</b>) Quantification of apoptosis in the cells. Results are expressed as means ± SD; ns: not significant, ** <span class="html-italic">p</span> &lt; 0.01; results were analyzed by one-way ANOVA, followed by the Tukey–Kramer test for multiple comparisons, with n = 3.</p>
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17 pages, 4465 KiB  
Article
Anxiolytic and Antidepressant Effects of Tribulus terrestris Ethanolic Extract in Scopolamine-Induced Amnesia in Zebrafish: Supported by Molecular Docking Investigation Targeting Monoamine Oxidase A
by Salwa Bouabdallah, Mona H. Ibrahim, Ion Brinza, Razvan Stefan Boiangiu, Iasmina Honceriu, Amr Amin, Mossadok Ben-Attia and Lucian Hritcu
Pharmaceuticals 2024, 17(9), 1208; https://doi.org/10.3390/ph17091208 - 13 Sep 2024
Viewed by 255
Abstract
Plants of the genus Tribulus have been used in folk medicine for wound healing, alleviating liver, stomach, and rheumatism pains, and as cognitive enhancers, sedatives, antiseptics, tonics, and stimulants. The present work aimed to evaluate whether Tribulus terrestris (Tt) administered for 15 days [...] Read more.
Plants of the genus Tribulus have been used in folk medicine for wound healing, alleviating liver, stomach, and rheumatism pains, and as cognitive enhancers, sedatives, antiseptics, tonics, and stimulants. The present work aimed to evaluate whether Tribulus terrestris (Tt) administered for 15 days attenuated cognitive deficits and exhibited anxiolytic and antidepressant profiles in scopolamine-induced amnesia in zebrafish. Animals were randomly divided into six groups (eight animals per group): (1)–(3) Tt treatment groups (1, 3 and 6 mg/L), (4) control, (5) scopolamine (SCOP, 0.7 mg/kg), and (6) galantamine (Gal, 1 mg/L). Exposure to SCOP (100 µM) resulted in anxiety in zebrafish, as assessed by the novel tank diving test (NTT) and novel approach test (NAT). When zebrafish were given SCOP and simultaneously given Tt (1, 3, and 6 mg/L once daily for 10 days), the deficits were averted. Molecular interactions of chemical compounds from the Tt fractions with the monoamine oxidase A (MAO-A) were investigated via molecular docking experiments. Using behavioral experiments, we showed that administration of Tt induces significant anxiolytic-antidepressant-like effects in SCOP-treated zebrafish. Our result indicated that flavonoids of Tt, namely kaempferol, quercetin, luteolin, apigetrin, and epigallocatechin, could act as promising phytopharmaceuticals for improving anxiety-related disorders. Full article
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<p>Novel tank dividing test (NTT) results for <span class="html-italic">Tribulus terrestris</span> (Tt: 1, 3 and 6 mg/L). (<b>A</b>) Representative tracking locomotion patterns; (<b>B</b>) Time spent in the top (s); (<b>C</b>) Distance travelled in the top (m); (<b>D</b>) Number of entries to the top (s); (<b>E</b>) Average entry duration; (<b>F</b>) Freezing duration (s); (<b>G</b>) Latency. Data are expressed as means ± S.E.M. (<span class="html-italic">n</span> = 8). * <span class="html-italic">p</span> &lt; 0.01, ** <span class="html-italic">p</span> &lt; 0.001, *** <span class="html-italic">p</span> &lt; 0.0001, and **** <span class="html-italic">p</span> &lt; 0.00001 (Tukey’s post hoc analyses). Galantamine (GAL, 1 mg/L) was used as a reference positive drug.</p>
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<p>Novel approach test (NAT) results for <span class="html-italic">Tribulus terrestris</span> (Tt: 1, 3, and 6 mg/L). (<b>A</b>) Representative tracking locomotion patterns; (<b>B</b>) Immobility (s); (<b>C</b>) Distance travelled (m); (<b>D</b>) latency; (<b>E</b>) Times in zones (s). Data are expressed as means ± S.E.M. (<span class="html-italic">n</span> = 8). * <span class="html-italic">p</span> &lt; 0.01, ** <span class="html-italic">p</span> &lt; 0.001, *** <span class="html-italic">p</span> &lt; 0.0001, and **** <span class="html-italic">p</span> &lt; 0.00001 (Tukey’s post hoc analyses). Galantamine (GAL, 1 mg/L) was used as a reference positive drug.</p>
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<p>The root means square deviation (RMSD) between the original and docked poses of the co-crystal ligands for the MAO-A enzyme (PDB: 2z5x) was 0.13 Å.</p>
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<p>2D and 3D representation of co-crystal ligand docked into binding site of MAO_A active site enzyme.</p>
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<p>2D and 3D representations of Kaempferol docked into binding site of MAO-A active site enzyme.</p>
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<p>2D and 3D representations of Quercetin docked into binding site of MAO-A active site enzyme.</p>
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<p>2D and 3D of Luteoline docked into binding site of MAO-A active site enzyme.</p>
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<p>The experimental design of the study (NTT and NAT test).</p>
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9 pages, 6587 KiB  
Communication
The Discovery of Substituted 5-(2-Hydroxybenzoyl)-2-Pyridone Analogues as Inhibitors of the Human Caf1/CNOT7 Ribonuclease
by Ishwinder Kaur, Gopal P. Jadhav, Peter M. Fischer and Gerlof Sebastiaan Winkler
Molecules 2024, 29(18), 4351; https://doi.org/10.3390/molecules29184351 - 13 Sep 2024
Viewed by 150
Abstract
The Caf1/CNOT7 nuclease is a catalytic component of the Ccr4-Not deadenylase complex, which is a key regulator of post-transcriptional gene regulation. In addition to providing catalytic activity, Caf1/CNOT7 and its paralogue Caf1/CNOT8 also contribute a structural function by mediating interactions between the large, [...] Read more.
The Caf1/CNOT7 nuclease is a catalytic component of the Ccr4-Not deadenylase complex, which is a key regulator of post-transcriptional gene regulation. In addition to providing catalytic activity, Caf1/CNOT7 and its paralogue Caf1/CNOT8 also contribute a structural function by mediating interactions between the large, non-catalytic subunit CNOT1, which forms the backbone of the Ccr4-Not complex and the second nuclease subunit Ccr4 (CNOT6/CNOT6L). To facilitate investigations into the role of Caf1/CNOT7 in gene regulation, we aimed to discover and develop non-nucleoside inhibitors of the enzyme. Here, we disclose that the tri-substituted 2-pyridone compound 5-(5-bromo-2-hydroxy-benzoyl)-1-(4-chloro-2-methoxy-5-methyl-phenyl)-2-oxo-pyridine-3-carbonitrile is an inhibitor of the Caf1/CNOT7 nuclease. Using a fluorescence-based nuclease assay, the activity of 16 structural analogues was determined, which predominantly explored substituents on the 1-phenyl group. While no compound with higher potency was identified among this set of structural analogues, the lowest potency was observed with the analogue lacking substituents on the 1-phenyl group. This indicates that substituents on the 1-phenyl group contribute significantly to binding. To identify possible binding modes of the inhibitors, molecular docking was carried out. This analysis suggested that the binding modes of the five most potent inhibitors may display similar conformations upon binding active site residues. Possible interactions include π-π interactions with His225, hydrogen bonding with the backbone of Phe43 and Van der Waals interactions with His225, Leu209, Leu112 and Leu115. Full article
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<p>Structure of 5-(5-bromo-2-hydroxybenzoyl)-1-(4-chloro-2-methoxy-5-methylphenyl)-2-oxo-1,2-dihydropyridine-3-carbonitrile, an inhibitor of the human Caf1/CNOT7 nuclease. The reported IC<sub>50</sub> value is 14.6 ± 3.1 μM [<a href="#B37-molecules-29-04351" class="html-bibr">37</a>].</p>
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<p>Molecular docking of inhibitors into the active site of human Caf1/CNOT7. (<b>A</b>) Catalytic site of the Caf1/CNOT7 enzyme. Shown is the position of the residues coordinating two Mg<sup>2+</sup> ions (bright green) in the active site of <span class="html-italic">Schizosaccharomyces pombe</span> Pop2 protein (PDB 2P51, slate blue) [<a href="#B9-molecules-29-04351" class="html-bibr">9</a>] and the corresponding coordinating residues of human Caf1/CNOT7 (PDB 7VOI, salmon red) [<a href="#B12-molecules-29-04351" class="html-bibr">12</a>]. (<b>B</b>) Model of human Caf1/CNOT7 bound to poly(A) RNA. The RNA was obtained by superposition of the structure of human Caf1/CNOT7 (PDB 7VOI) [<a href="#B12-molecules-29-04351" class="html-bibr">12</a>] and <span class="html-italic">Schizosaccharomyces pombe</span> Pan2 in complex with poly(A) RNA (PDB 6R9J) [<a href="#B45-molecules-29-04351" class="html-bibr">45</a>]. Shown are the surface views of the residues developing; polar interactions (red) and nonpolar interactions (white) with the analogues (<b>1</b>, <b>8</b>, <b>9</b>, <b>11</b>, <b>15</b> and <b>17</b>) in the active site. (<b>C</b>) Molecular docking of <b>1</b> (cyan) into the active site of Caf1/CNOT7. (<b>D</b>) Overlay of <b>1</b> (cyan) with the plausible conformation of the five most potent analogues <b>8</b> (light green), <b>9</b> (light yellow), <b>11</b> (slate blue), <b>15</b> (magenta) and <b>17</b> (white). (<b>E</b>) Molecular docking of <b>17</b> (white) into the active site of Caf1/CNOT7 (<b>F</b>) Overlay of <b>1</b> (cyan) with the plausible conformation of the most potent analogue <b>17</b>, into the active site of Caf1/CNOT7.</p>
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22 pages, 4974 KiB  
Article
E3 Ubiquitin Ligase CHIP Inhibits Haemocyte Proliferation and Differentiation via the Ubiquitination of Runx in the Pacific Oyster
by Miren Dong, Ying Song, Weilin Wang, Xiaorui Song, Wei Wu, Lingling Wang and Linsheng Song
Cells 2024, 13(18), 1535; https://doi.org/10.3390/cells13181535 - 13 Sep 2024
Viewed by 210
Abstract
Mollusca first evolve primitive immune cells (namely, haemocytes), which assemble a notable complex innate immune system, which are continuously produced through proliferation and differentiation and infused in the haemolymph. As a typical E3 ligase, CHIP is critical for immune cell turnover and homeostasis [...] Read more.
Mollusca first evolve primitive immune cells (namely, haemocytes), which assemble a notable complex innate immune system, which are continuously produced through proliferation and differentiation and infused in the haemolymph. As a typical E3 ligase, CHIP is critical for immune cell turnover and homeostasis in vertebrates. In this study, a CHIP homolog (CgCHIP) with a high expression in haemocytes was identified in oysters to investigate its role in the proliferation and differentiation of ancient innate immune cells. CgCHIP exhibited a widespread distribution across all haemocyte subpopulations, and the knockdown of CgCHIP altered the composition of haemocytes as examined by flow cytometry. Mechanistically screened with bioinformatics and immunoprecipitation, a key haematopoietic transcription factor CgRunx was identified as a substrate of CgCHIP. Moreover, amino acids in the interacted intervals of CgCHIP and CgRunx were determined by molecular docking. Experimental evidence from an in vitro culture model of an agranulocyte subpopulation and an in vivo oyster model revealed that the knockdown of CgCHIP and CgRunx had opposing effects on agranulocyte (precursor cells) differentiation and granulocyte (effector cells) proliferation. In summary, CgCHIP negatively regulated agranulocyte differentiation and granulocyte proliferation by mediating the ubiquitination and degradation of CgRunx in oysters. These results offer insight into the involvement of ubiquitylation in controlling haemocyte turnover in primitive invertebrates. Full article
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Figure 1

Figure 1
<p>Evolutionary properties of ubiquitin E3 ligase CHIP from oyster <span class="html-italic">C</span>. <span class="html-italic">gigas</span>. (<b>A</b>) Domain and tertiary structure prediction of CHIP from oyster <span class="html-italic">C</span><b>.</b> <span class="html-italic">gigas</span> by SMART and SWISS-MODEL program. (<b>B</b>) Domain and tertiary structure prediction of CHIP from <span class="html-italic">Homo sapiens</span> by SMART and SWISS-MODEL program. The pink box indicates a low complexity domain. (<b>C</b>) Multisequence alignment analysis of <span class="html-italic">Cg</span>CHIP with its homologues from other vertebrate and invertebrate species. Amino acids with 100% identity are in black, and similar amino acids are in gray. (<b>D</b>) A phylogenetic tree for CHIP was constructed with the amino acid sequences from the indicated species including <span class="html-italic">H. sapiens</span>, <span class="html-italic">M. musculus</span>, <span class="html-italic">D. rerio</span>, <span class="html-italic">L. anatine</span>, <span class="html-italic">D. melanogaster</span>, <span class="html-italic">A. californica</span>, <span class="html-italic">B. glabrata</span>, <span class="html-italic">M. yessoensis</span>, <span class="html-italic">C</span>. <span class="html-italic">gigas</span>, <span class="html-italic">C. virginica</span>, and <span class="html-italic">C. elegans</span>. The trees were constructed using the neighbor-joining (NJ) algorithm in the Mega 6.0 program based on multiple sequence alignment by ClustalW. Bootstrap values of 1000 replicates (%) are indicated for the branches. CHIP from <span class="html-italic">C</span>. <span class="html-italic">gigas</span> was marked with a grey arrow.</p>
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<p><span class="html-italic">Cg</span>CHIP is highly expressed in oyster haemocytes and alters the proportion of their three subpopulations. (<b>A</b>) The mRNA transcripts of <span class="html-italic">Cg</span>CHIP in the indicated tissues and haemocytes examined by qRT-PCR, normalized to <span class="html-italic">Cg</span>EF1-α. Hep: hepatopancreas; Man: mantle; Gon: gonad; Amu: adductor muscle; Lap: labial palp; Gil: gill; Hae: haemocytes. <span class="html-italic">p</span>-values, <sup>a</sup> <span class="html-italic">p</span> &gt; 0.05, <sup>b</sup> <span class="html-italic">p</span> &lt; 0.05, and <sup>c</sup> <span class="html-italic">p</span> &lt; 0.01, were calculated using a one-way ANOVA with Dunnett’s correction for multiple comparisons. (<b>B</b>) Relative temporal levels of <span class="html-italic">Cg</span>CHIP mRNA in haemocytes with or without <span class="html-italic">V. splendidus</span> infection examined by qRT-PCR, normalized to <span class="html-italic">Cg</span>EF1-α. Error bars show mean ± standard deviation. <span class="html-italic">p</span>-values, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, were calculated using a two-tailed, unpaired <span class="html-italic">t</span>-test. Error bars show mean ± standard deviation (<span class="html-italic">n</span> = 3). (<b>C</b>) SDS-PAGE analysis showed the recombinant-<span class="html-italic">Cg</span>CHIP (r<span class="html-italic">Cg</span>CHIP) proteins. Lane M: protein molecular marker; Lane 1: negative control (without IPTG induction); Lane 2: induced recombinant protein with IPTG; Lane 3: purified r<span class="html-italic">Cg</span>CHIP protein. (<b>D</b>) The specificity of the <span class="html-italic">Cg</span>CHIP polyclonal antibody determined by Western blotting. Lane M: protein molecular marker; Lane 1: in vitro recombinant proteins; Lane 2: haemocyte lysate. (<b>E</b>) Transcriptome data analysis shows the mRNA transcripts of <span class="html-italic">Cg</span>CHIP in the three haemocyte subpopulations (<span class="html-italic">n</span> = 7). <span class="html-italic">p</span>-values, * <span class="html-italic">p</span> &lt; 0.05, were calculated using a one-way ANOVA with Dunnett’s correction for multiple comparisons. ns indicates no significant difference. (<b>F</b>) Haemocytes collected from oyster haematocoel, and morphology observed under confocal. (<b>G</b>) Haemocytes observed following Giemsa staining. (<b>H</b>) Three subpopulations of haemocytes morphologically identified and separated as agranulocytes (A), semi-granulocytes (SG), and granulocytes (G), by flow cytometry. (<b>I</b>) Representative immunofluorescence image shows the localization of <span class="html-italic">Cg</span>CHIP (green) in haemocytes and the nuclei stained with DAPI (blue). The localization region marked with yellow circles. (<b>J</b>) Bar graph shows the mean fluorescence intensity of <span class="html-italic">Cg</span>CHIP in the three haemocyte subpopulations. The per cell compartment was outlined, and the fluorescence intensity of positive signals within per cell was measured using ImageJ software. For each haemocyte subpopulation, the mean fluorescence value of ten cells from five fields were calculated as one replicate, and there were three replicates (<span class="html-italic">n</span> = 3). Abbreviations: Ara: agranulocytes; Semi-gra: semi-granulocytes; and Gra: granulocytes. (<b>K</b>) The percentages of three subpopulations in total haemocytes measured by flow cytometry (<span class="html-italic">n</span> = 3). (<b>L</b>) The bar graph shows the percentage of three haemocyte subpopulations (<span class="html-italic">n</span> = 3). <span class="html-italic">p</span>-values, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, were calculated using a two-tailed, unpaired <span class="html-italic">t</span>-test.</p>
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<p><span class="html-italic">Cg</span>CHIP targets the <span class="html-italic">Cg</span>Runx protein. (<b>A</b>) CHIP was known to interact with Runx1 as predicted by UbiBrowser 2.0 program. (<b>B</b>) The typical and conserved ubiquitination sites within the Runx protein. The Runt domain is marked with a red box. A Met-1 ubiquitination site is marked with a blue asterisk. Four conserved Lys ubiquitination sites are labeled with a red triangle. (<b>C</b>) Co-IP-based interaction detection of <span class="html-italic">Cg</span>CHIP and <span class="html-italic">Cg</span>Runx in oyster haemocytes. (<b>D</b>) Docking model analysis of <span class="html-italic">Cg</span>CHIP and <span class="html-italic">Cg</span>Runx. (<b>E</b>) The binding coefficients of <span class="html-italic">Cg</span>CHIP and <span class="html-italic">Cg</span>Runx protein interaction sites. (<b>F</b>) Ubiquitination activity of <span class="html-italic">Cg</span>CHIP detected with Western blotting in vitro. (<b>G</b>) <span class="html-italic">Cg</span>Runx ubiquitination assessed by Western blotting. (<b>H</b>) The levels of <span class="html-italic">Cg</span>Runx in oyster haemocytes treated with MG132 (20 μM), quantified by Western blotting.</p>
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<p><span class="html-italic">Cg</span>CHIP enhances the ubiquitination and degradation of <span class="html-italic">Cg</span>Runx. (<b>A</b>) Representative immunofluorescence image shows the localization of <span class="html-italic">Cg</span>Runx (green) in haemocytes and the nuclei stained with DAPI (blue). (<b>B</b>) Transcriptome data analysis shows the mRNA transcripts of <span class="html-italic">Cg</span>Runx in the three haemocyte subpopulations (<span class="html-italic">n</span> = 7). <span class="html-italic">p</span>-values, * <span class="html-italic">p</span> &lt; 0.05, were calculated using a one-way ANOVA with Dunnett’s correction for multiple comparisons. ns indicates no significant difference. (<b>C</b>) Bar graph shows the mean fluorescence intensity of <span class="html-italic">Cg</span>Runx in the three haemocyte subpopulations. (<b>D</b>) An injection cartoon of dsRNA in the interference assay. (<b>E</b>) The RNAi efficiency of <span class="html-italic">Cg</span>CHIP in haemocytes quantified via qRT-PCR, normalized to <span class="html-italic">Cg</span>EF1-α. Error bars show mean ± standard deviation (<span class="html-italic">n</span> = 3). <span class="html-italic">p</span>-values, ** <span class="html-italic">p</span> &lt; 0.01, were calculated using a two-tailed, unpaired <span class="html-italic">t</span>-test. (<b>F</b>) Protein abundance of <span class="html-italic">Cg</span>CHIP (RNAi efficiency) and <span class="html-italic">Cg</span>Runx examined with Western blotting. (<b>G</b>) Gray analysis of protein band, normalized to β-Tubulin and Histone H3, respectively. <span class="html-italic">p</span>-values, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, were calculated using a two-tailed, unpaired <span class="html-italic">t</span>-test.</p>
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<p><span class="html-italic">Cg</span>CHIP inhibits agranulocyte differentiation. (<b>A</b>) Schematic of the induced differentiation in cultured agranulocytes. (<b>B</b>) Representative flow cytometry dot-plots show the gated semi-granulocyte and granulocyte populations differentiated from agranulocytes using the agranulocyte differentiation protocol. (<span class="html-italic">n</span> = 3). (<b>C</b>) The bar graph shows the percentage of differentiated agranulocytes (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, determined by a two-tailed Student’s <span class="html-italic">t</span>-test. (<b>D</b>,<b>E</b>) Protein expression levels of the proliferative marker <span class="html-italic">Cg</span>PCNA, immature agranulocyte marker <span class="html-italic">Cg</span>Integrin α4, and mature granulocyte marker <span class="html-italic">Cg</span>AATase, in agranulocytes. β-Tubulin was used as an internal control. Error bars show mean ± standard deviation (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, determined by a two-tailed Student’s <span class="html-italic">t</span>-test.</p>
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<p><span class="html-italic">Cg</span>CHIP inhibits granulocyte proliferation. (<b>A</b>) Representative flow cytometry peak diagrams show the proliferation rate of gated EdU labeling agranulocytes in total agranulocytes. (<b>B</b>) The bar graph shows the proliferation rate of agranulocytes (<span class="html-italic">n</span> = 3). (<b>C</b>) Representative flow cytometry peak diagrams showing the proliferation rate of gated EdU labeling granulocytes in total granulocytes. (<b>D</b>) The bar graph shows the proliferation rate of granulocytes (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05, determined by a two-tailed Student’s <span class="html-italic">t</span> test. (<b>E</b>) Schematic of granulocyte isolation for cell cycle and Western blotting analyses. (<b>F</b>) The percentage changes of granulocytes in different cell cycle phases. (<b>G</b>) The bar graph shows the percentage of agranulocytes in different cell cycle phases (<span class="html-italic">n</span> = 3). Error bars show mean ± standard deviation (<span class="html-italic">n</span> = 3). <span class="html-italic">p</span>-values, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, were calculated using a one-way ANOVA with Dunnett’s correction for multiple comparisons. (<b>H</b>,<b>I</b>) Protein expression levels of proliferative genes <span class="html-italic">Cg</span>Cyclin B1 and <span class="html-italic">Cg</span>CDK2 in granulocytes. β-Tubulin was used as an internal control. Error bars show mean ± standard deviation (<span class="html-italic">n</span> = 3). The data shown are representative of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, determined by a two-tailed Student’s <span class="html-italic">t</span> test.</p>
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<p><span class="html-italic">Cg</span>CHIP attenuates phagocytosis in a <span class="html-italic">Cg</span>Runx-dependent manner. (<b>A</b>,<b>B</b>) Representative flow cytometry peak diagrams show the gated phagocytic haemocytes that are defined according to the red positive signal of latex beads. Phagocytic rate in haemocytes was defined by the percentage of phagocytic haemocytes taking in latex beads in total haemocytes. Error bars show mean ± standard deviation (<span class="html-italic">n</span> = 3). <span class="html-italic">p</span>-values were calculated using a one-way ANOVA with Dunnett’s correction for multiple comparisons. The asterisk * and ** indicated a significant difference at <span class="html-italic">p</span> &lt; 0.05 and extremely significant difference at <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>A graphical abstract. A conceptual framework for the ubiquitination and degradation of <span class="html-italic">Cg</span>Runx mediated by <span class="html-italic">Cg</span>CHIP, which inhibits the differentiation of agranulocytes and the proliferation of granulocytes in the Pacific oyster <span class="html-italic">C</span>. <span class="html-italic">gigas</span>.</p>
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25 pages, 5506 KiB  
Article
Neurotoxicity, Neuroprotection, In Vitro MAOA/MAOB Inhibitory Activity Assessment, Molecular Docking, and Permeability Assay Studies of Newly Synthesized Hydrazones Containing a Pyrrole Ring
by Maya Georgieva, Emilio Mateev, Iva Valkova, Hristina Kuteva, Diana Tzankova, Denitsa Stefanova, Yordan Yordanov, Karolina Lybomirova, Alexander Zlatkov, Virginia Tzankova and Magdalena Kondeva-Burdina
Molecules 2024, 29(18), 4338; https://doi.org/10.3390/molecules29184338 - 12 Sep 2024
Viewed by 253
Abstract
Neurodegenerative diseases such as Parkinson’s and Alzheimer’s continue to be some of the most significant challenges in modern medicine. Recent research related to the molecular mechanisms of parkinsonism has opened up new approaches to antiparkinsonian therapy. In response to this, we present the [...] Read more.
Neurodegenerative diseases such as Parkinson’s and Alzheimer’s continue to be some of the most significant challenges in modern medicine. Recent research related to the molecular mechanisms of parkinsonism has opened up new approaches to antiparkinsonian therapy. In response to this, we present the evaluation of the potential neuroprotective and MAOA/MAOB inhibitory effects of newly synthesized hydrazones, containing a pyrrole moiety in the carboxyl fragment of the structure. The substances were studied on different brain subcellular fractions, including rat brain synaptosomes, mitochondria, and microsomes. The single application of 50 µM of each compound to the subcellular fractions showed that all substances exhibit a weak neurotoxic effect, with 7b, 7d, and 8d being the least neurotoxic representatives. The corresponding neuroprotective and antioxidant effects were also evaluated in different injury models on subcellular fractions, single out 7b, 7d, and 8d as the most prominent derivatives. A 1 µM concentration of each molecule from the series was also studied for potential hMAOA/hMAOB inhibitory effects. The results revealed a lack of hMAOA activity for all evaluated structures and the appearance of hMAOB effects, with compounds 7b, 7d, and 8d showing effects similar to those of selegiline. The best hMAOB selectivity index (>204) was determined for 7d and 8d, distinguishing these two representatives as the most promising molecules for further studies as potential selective MAOB inhibitors. The performed molecular docking simulations defined the appearance of selective MAOB inhibitory effects based on the interaction of the tested molecules with Tyr398, which is one of the components of the aromatic cage of MAOB and participated in π–π stabilization with the aromatic pyrrole ring. The preliminary PAMPA testing indicated that in relation to the blood–brain barrier (BBB) permeability, the tested pyrrole-based hydrazones may be considered as high permeable, except for 8a and 8e, which were established to be permeable in the medium range with −logP of 5.268 and 5.714, respectively, compared to the applied references. Full article
(This article belongs to the Section Medicinal Chemistry)
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Figure 1

Figure 1
<p>Structures of some MAO inhibitors.</p>
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<p>Structures of the most active molecule <b>12a</b> and its analogues containing a benzaldehyde residue from a previously synthesized series [<a href="#B28-molecules-29-04338" class="html-bibr">28</a>].</p>
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<p>Structures and IDs of the evaluated hydrazones.</p>
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<p>Effect of the test substances applied alone at a concentration of 50 µM on synaptosomal viability. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01 vs. control (non-treated synaptosomes).</p>
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<p>Effect of the test substances applied alone at a concentration of 50 µM on the level of glutathione (GSH). * <span class="html-italic">p</span> &lt; 0.05 vs. control (non-treated synaptosomes).</p>
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<p>Effect of test substances applied alone at a concentration of 50 µM on MDA production. ** <span class="html-italic">p</span> &lt; 0.01 vs. control (non-treated mitochondria).</p>
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<p>Effect of test substances applied alone at a concentration of 50 µM on GSH level. * <span class="html-italic">p</span> &lt; 0.05 vs. control (non-treated mitochondria).</p>
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<p>Effect of test substances applied alone, at a concentration of 50 µM, on MDA production. ** <span class="html-italic">p</span> &lt; 0.01 vs. control (non-treated microsomes).</p>
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<p>Effect of substances in combination with 6-OHDA on synaptosomal viability. *** <span class="html-italic">p</span> &lt; 0.001 vs. control (non-treated synaptosomes); + <span class="html-italic">p</span> &lt; 0.05; ++ <span class="html-italic">p</span> &lt; 0.01 vs. 6-OHDA. The green color indicates the most active derivatives.</p>
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<p>Effect of substances, in combination with 6-OHDA, on the level of reduced glutathione (GSH). ** <span class="html-italic">p</span> &lt; 0.001 vs. control (non-treated synaptosomes); + <span class="html-italic">p</span> &lt; 0.05 vs. 6-OHDA. The green color indicates the most active derivatives.</p>
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<p>Effect of substances in combination with <span class="html-italic">t</span>-BuOOH on MDA production. *** <span class="html-italic">p</span> &lt; 0.001 vs. control (non-treated mitochondria); + <span class="html-italic">p</span> &lt; 0.05; ++ <span class="html-italic">p</span> &lt; 0.01 vs. <span class="html-italic">t</span>-BuOOH. The green color indicates the most active derivatives.</p>
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<p>Effect of substances in combination with <span class="html-italic">t</span>-BuOOH on GSH level. ** <span class="html-italic">p</span> &lt; 0.01 vs. control (non-treated mitochondria); + <span class="html-italic">p</span> &lt; 0.05; ++ <span class="html-italic">p</span> &lt; 0.01 vs. <span class="html-italic">t</span>-BuOOH. The green color indicates the most active derivatives.</p>
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<p>Effect of substances under conditions of non-enzyme-induced lipid peroxidation (Fe<sup>2+</sup>/AA). *** <span class="html-italic">p</span> &lt; 0.001 vs. control (non-treated microsomes); ++ <span class="html-italic">p</span> &lt; 0.01; +++ <span class="html-italic">p</span> &lt; 0.001 vs. Fe<sup>2+</sup>/AA. The green color indicates the most active derivatives.</p>
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<p>Effect of newly synthetized hydrazones containing a pyrrole cycle in the carboxyl fragment of the structure (at 1 µM concentration) on the activity of human recombinant MAOA enzyme (<span class="html-italic">h</span>MAOA). *** <span class="html-italic">p</span> &lt; 0.001 vs. control (pure <span class="html-italic">h</span>MAOA).</p>
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<p>Effect of newly synthetized hydrazones containing a pyrrole cycle in the carboxyl fragment of the structure (at 1 µM concentration) on the activity of the human recombinant MAOB enzyme (<span class="html-italic">h</span>MAOB). * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001 vs. control (pure <span class="html-italic">h</span>MAOB). The green color indicates the most active derivatives.</p>
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<p>Major intermolecular interactions between the active site of MAOB and <b>8d</b>: (<b>a</b>) 3D model; (<b>b</b>) 2D model.</p>
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19 pages, 3230 KiB  
Article
The Phylogenomic Characterization of Planotetraspora Species and Their Cellulases for Biotechnological Applications
by Noureddine Bouras, Mahfoud Bakli, Guendouz Dif, Slim Smaoui, Laura Șmuleac, Raul Paşcalău, Esther Menendez and Imen Nouioui
Genes 2024, 15(9), 1202; https://doi.org/10.3390/genes15091202 - 12 Sep 2024
Viewed by 259
Abstract
This study aims to evaluate the in silico genomic characteristics of five species of the genus Planotetraspora: P. kaengkrachanensis, P. mira, P. phitsanulokensis, P. silvatica, and P. thailandica, with a view to their application in therapeutic research. [...] Read more.
This study aims to evaluate the in silico genomic characteristics of five species of the genus Planotetraspora: P. kaengkrachanensis, P. mira, P. phitsanulokensis, P. silvatica, and P. thailandica, with a view to their application in therapeutic research. The 16S rRNA comparison indicated that these species were phylogenetically distinct. Pairwise comparisons of digital DNA-DNA hybridization (dDDH) and OrthoANI values between these studied type strains indicated that dDDH values were below 62.5%, while OrthoANI values were lower than 95.3%, suggesting that the five species represent distinct genomospecies. These results were consistent with the phylogenomic study based on core genes and the pangenome analysis of these five species within the genus Planotetraspora. However, the genome annotation showed some differences between these species, such as variations in the number of subsystem category distributions across whole genomes (ranging between 1979 and 2024). Additionally, the number of CAZYme (Carbohydrate-Active enZYme) genes ranged between 298 and 325, highlighting the potential of these bacteria for therapeutic research applications. The in silico physico-chemical characteristics of cellulases from Planotetraspora species were analyzed. Their 3D structure was modeled, refined, and validated. A molecular docking analysis of this cellulase protein structural model was conducted with cellobiose, cellotetraose, laminaribiose, carboxymethyl cellulose, glucose, and xylose ligand. Our study revealed significant interaction between the Planotetraspora cellulase and cellotetraose substrate, evidenced by stable binding energies. This suggests that this bacterial enzyme holds great potential for utilizing cellotetraose as a substrate in various applications. This study enriches our understanding of the potential applications of Planotetraspora species in therapeutic research. Full article
(This article belongs to the Section Microbial Genetics and Genomics)
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Figure 1
<p>Phylogenomic tree based on genome sequences in the TYGS tree inferred with FastME 2.1.6.1 [<a href="#B16-genes-15-01202" class="html-bibr">16</a>] from the Genome BLAST Distance Phylogeny approach (GBDP); distances calculated from genome sequences. The branch lengths are scaled in terms of GBDP distance formula d5. The numbers above branches are GBDP pseudo-bootstrap support values &gt;70% from 100 replications. The tree was rooted at the midpoint [<a href="#B13-genes-15-01202" class="html-bibr">13</a>]. The different color indicates the different species cluster.</p>
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<p>Maximum likelihood core gene phylogenomic tree. The core genes were identified using the Roary program [<a href="#B20-genes-15-01202" class="html-bibr">20</a>] and MEGA software version 11 [<a href="#B21-genes-15-01202" class="html-bibr">21</a>] with 1000 bootstrap replications to assess statistical support. This illustrates the evolutionary relationship between the species of <span class="html-italic">Planotetraspora</span>. <span class="html-italic">Nocardiopsis algeriensis</span> CECT 8712<sup>T</sup> was used as an outgroup. Bar 0.02 nucleotide substitution per site.</p>
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<p>Pangenome analysis of five species of genomes of <span class="html-italic">Planotetraspora</span> was conducted using Roary [<a href="#B20-genes-15-01202" class="html-bibr">20</a>]. Matrix destitution of genes across the pangenome of all <span class="html-italic">Planotetraspora</span> species (from Rotary), and <span class="html-italic">Nocardiopsis algeriensis</span> CECT 8712<sup>T</sup> was used as an outgroup. Pangenome visualization is displayed as presence (blue) and absence (white) output using Phandango [<a href="#B24-genes-15-01202" class="html-bibr">24</a>].</p>
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<p>The SWISS−MODEL generated the 3D and refined structure of <span class="html-italic">Planotetraspora</span> cellulase enzymes and its validation. (<b>A</b>) This structural model was refined by ModRefiner and visualized by PyMOL. α-helix (chocolate), β-sheet (cyan), and loop (yellow). (<b>B</b>) Ramachandran plot for the refined cellulase obtained by PROCHECK. The residues found in favored (A, B, and L), additional allowed (a, b, l, and p), generously allowed (~a, ~b, ~l, and ~p), and disallowed regions are delineated with red, yellow, beige, and white color coding, respectively. All non-glycine and non-proline residues are depicted as filled black squares, while glycines (non−terminal) are represented as filled black triangles.</p>
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<p>Molecular docking analysis of the cellotetraose ligand with the <span class="html-italic">Planotetraspora</span> cellulase enzyme receptor. (<b>A</b>) The cartoon representation of the protein receptor and its ligand. (<b>B</b>) Cavity illustration showed the region on the protein receptor surface where bonding occurs with the ligand. (<b>C</b>) Vina score and cavity size models table displayed the Vina score of this receptor and the ligand docking with the best highlighted score. The enzyme–ligand interactions were visualized, employing the ball and stick style for the ligand and the surface style for the receptor. Ligand and receptor colors were configured based on elements and B-factor, respectively. (<b>D</b>) Interaction residues depicted the interacting residues of the receptor with the ligand as visualized in BIOVIA Discovery Studio Visualizer. (<b>E</b>) 2D diagram of residue interaction types between ligand and receptor as visualized in BIOVIA Discovery Studio Visualizer.</p>
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23 pages, 10968 KiB  
Article
Ginkgo Biloba Bioactive Phytochemicals against Age-Related Diseases: Evidence from a Stepwise, High-Throughput Research Platform
by Yuming Yuan, Xiaoyan Xiang, Xuejun Jiang, Yingju Liu, Ming Zhang, Luyang Lu, Xinping Zhang, Xinyi Liu, Qunyou Tan and Jingqing Zhang
Antioxidants 2024, 13(9), 1104; https://doi.org/10.3390/antiox13091104 - 12 Sep 2024
Viewed by 277
Abstract
The seeds of ginkgo biloba L (GB) have been widely used worldwide. This study investigated the bioefficacies of whole GB seed powder (WGP) retaining the full nutrients of ginkgo against aging, atherosclerosis, and fatigue. The experimental results indicated that WGP lowered brain monoamine [...] Read more.
The seeds of ginkgo biloba L (GB) have been widely used worldwide. This study investigated the bioefficacies of whole GB seed powder (WGP) retaining the full nutrients of ginkgo against aging, atherosclerosis, and fatigue. The experimental results indicated that WGP lowered brain monoamine oxidase and serum malondialdehyde levels, enhanced thymus/spleen indexes, and improved learning ability, and delayed aging in senescent mice. WGP regulated lipid levels and prevented atherosclerosis by reducing triglycerides, lowering low-density lipoprotein cholesterol, increasing high-density lipoprotein cholesterol, and decreasing the atherosclerosis index. WGP improved exercise performance by reducing blood lactate accumulation and extending exhaustive swimming and climbing times, improved energy storage by increasing muscle/liver glycogen levels, and relieved physical fatigue. Network pharmacology analysis revealed 270 potential targets of WGP that play roles in cellular pathways related to inflammation inhibition, metabolism regulation, and anti-cellular senescence, etc. Protein-protein interaction analysis identified 10 hub genes, including FOS, ESR1, MAPK8, and SP1 targets. Molecular docking and molecular dynamics simulations showed that the bioactive compounds of WGP bound well to the targets. This study suggests that WGP exerts prominent health-promoting effects through multiple components, targets, and pathways. Full article
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Figure 1

Figure 1
<p>Schematic diagram depicting the experimental studies and network pharmacological analysis to assess the multifunction efficacy of whole ginkgo biloba L powder.</p>
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<p>Effects of whole ginkgo powder (WGP) on (<b>A</b>–<b>G</b>) motion map and (<b>H</b>) numbers to cross the virtual platform, (<b>I</b>) time in the first quadrant, (<b>J</b>) distance in the first quadrant in the water maze test for D-galactose (D-gal)-induced aging mice. Data are expressed means ± standard deviations (SDs) (<span class="html-italic">n</span> = 10). * and <sup>#</sup>, <span class="html-italic">p</span> &lt; 0.05 compared with the adult control (Group B) and old control (Group C), respectively; <sup>##</sup>, <span class="html-italic">p</span> &lt; 0.01 compared with e old control (Group C). Motion map of different groups A–G: Group A, young control; Group B, adult control, non-aging; Group C, old control, non-treated; Group D, vitamin E (VE) (0.1 g/kg)-treated, aging; Group E, WGP (2 g/kg)-treated, aging; Group F, WGP (4 g/kg)-treated, aging; Group G, WGP (6 g/kg)-treated, aging.</p>
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<p>Effects of WGP on (<b>A</b>) spleen index and (<b>B</b>) thymus index in different treatment groups. Data are expressed means ± SDs (<span class="html-italic">n</span> = 10).</p>
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<p>Effects of WGP of (<b>A</b>) superoxide dismutase (SOD) levels, (<b>B</b>) serum malondialdehyde (MDA), and (<b>C</b>) brain monoamine oxidase (MAO). Data are expressed means ± SDs (<span class="html-italic">n</span> = 10). * and <sup>#</sup>, <span class="html-italic">p</span> &lt; 0.05 compared with the adult control (Group B) and the old control (Group C), respectively; **, <span class="html-italic">p</span> &lt; 0.01 compared with the adult control (Group B) and the old control (Group C).</p>
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<p>Effects of WGP on the liver, lung, and kidney of D-gal-induced aging mice. The histological changes are revealed via hematoxylin and eosin (H&amp;E) staining (400×). Scale bar = 50 µm. Control 1, 60-d mice; Control 2, 300-d mice.</p>
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<p>Effects of WGP on (<b>A</b>–<b>D</b>) serum biochemical lipid parameters and (<b>E</b>) atherosclerosis index (AI) in rats. Data are expressed means ± standard deviations (SDs) (<span class="html-italic">n</span> = 10). * and <sup>#</sup>, <span class="html-italic">p</span> &lt; 0.05 compared with the negative control (Group A) and high-fat diet (HFD)-fed mice (Group B), respectively; ** and <sup>##</sup>, <span class="html-italic">p</span> &lt; 0.01 compared with the negative control (Group A) and high-fat diet (HFD)-fed mice (Group B). Group A: negative control, old; Group B: model control, HFD-fed; Group C: treatment, treated with 1 g of simvastatin (Sim); Group D: treatment, treated with 0.5 g of WGP; Group E: treatment, treated with 1 g of WGP; Group F: treatment, treated with 1.5 g of WGP.</p>
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<p>Effects of WGP on coronary artery and abdominal aorta. The histological examinations were performed via H&amp;E staining. The lipid plaque (LP) and endothelial injury (EI) were marked in different groups (400×). Scale bar = 50 μm.</p>
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<p>Effects of WGP on the (<b>A</b>) climbing time and (<b>B</b>) exhaustive swimming time of mice. Data are expressed as means ± standard deviations (SDs) (<span class="html-italic">n</span> = 10). * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared with the negative control (Group A). Group B: treatment, treated with 2 g of WGP; Group C: treatment, treated with 4 g of WGP; Group D: treatment, treated with 6 g of WGP.</p>
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<p>Effects of WGP on blood and tissue parameters. (<b>A</b>) Blood lactic acid (BLA); (<b>B</b>) blood urea nitrogen (BUN); (<b>C</b>) muscle glycogen (MG); (<b>D</b>) liver glycogen (LG) in mice. Data are expressed as means ± standard deviations (SD) (<span class="html-italic">n</span> = 10). * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared with the negative control (Group A). Group B: treatment, treated with 2 g of WGP; Group C: treatment, treated with 4 g of WGP; Group D: treatment, treated with 6 g of WGP.</p>
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<p>Relationships of active components and disease targets. The WGP compounds-targets-aging networks include the WGP compounds-targets-aging network (<b>A</b>), WGP compounds-targets-atherosclerosis network (<b>B</b>), and WGP compounds-targets-fatigue network (<b>C</b>). The green hexagon represents the disease, the round blue rectangle represents the target of the WGP compound, the red circle represents the WGP active ingredient compound, the edges represent the interactions between the nodes, and the dark pink diamond represents the WGP formula.</p>
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<p>Network pharmacological analysis of WGP. (<b>A</b>–<b>C</b>) Venn diagram of the action targets of WGP and the targets of aging (<b>A</b>), atherosclerosis (<b>B</b>), and fatigue (<b>C</b>). (<b>D</b>–<b>F</b>) Protein-protein interaction network reflected in cytohubba-MCC identified hub genes in the gene lists for WGP-aging (<b>D</b>), WGP-atherosclerosis (<b>E</b>), and WGP-fatigue (<b>F</b>). Node size and color in the network graph are positively correlated with the degree value. Redder colors and larger nodes represent larger degree value.</p>
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<p>GO enrichment analysis and KEGG pathway analysis. (<b>A</b>–<b>D</b>) GO enrichment analysis and KEGG pathway of intersection target of WGP and atherosclerosis (FDR ≤ 0.05). The biological processes (top 10, (<b>A</b>)), the cellular components (top 10, (<b>B</b>)), the molecular functions (top 10, (<b>C</b>)), and the KEGG pathways (top 10, (<b>D</b>)). (<b>E</b>–<b>H</b>) GO enrichment analysis and KEGG pathway analysis for WGP-Aging (FDR ≤ 0.05). The biological processes (top 10, (<b>E</b>)), the cellular components (top 10, (<b>F</b>)), the molecular functions (top 10, (<b>G</b>)), and the KEGG pathways (top 10, (<b>H</b>)) analysis for WGP-aging. The bubble size represents the number of targets in the pathway. The bubble color indicates the magnitude of the −log<sub>10</sub>(<span class="html-italic">p</span>) values.</p>
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<p>Molecular docking to model the interaction between FOS and three active ingredients of WGP (quercetin, EGCG, or kaempferol). (<b>A</b>–<b>C</b>) Interaction of FOS and quercetin. (<b>A</b>) Binding conformation of FOS-quercetin complex. (<b>B</b>,<b>C</b>) Electrical interactions of residue of FOS with quercetin. (<b>D</b>–<b>F</b>) Interaction of FOS and EGCG. (<b>D</b>) Binding conformation of FOS-EGCG complex. (<b>E</b>,<b>F</b>) Electrical interactions of residue on FOS with EGCG. (<b>G</b>–<b>I</b>) Interaction of FOS and kaempferol. (<b>G</b>) Binding conformation of FOS-kaempferol complex. (<b>H</b>,<b>I</b>) Electrical interactions of residue on FOS with kaempferol.</p>
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