| Literature DB >> 36158548 |
Ying-Ying Nie1,2, Long-Jian Zhou1,2, Yan-Mei Li1, Wen-Cong Yang1, Ya-Yue Liu1,2, Zhi-You Yang1, Xiao-Xiang Ma1, Yong-Ping Zhang1, Peng-Zhi Hong1,2, Yi Zhang1,2.
Abstract
Background: Oxidative stress, cholinergic deficiency, and neuroinflammation are hallmarks of most neurodegenerative disorders (NDs). Lipids play an important role in brain development and proper functioning. Marine-derived lipids have shown good memory-improving potentials, especially those from fish and microalgae. The cultivated macroalga Hizikia fusiforme is healthy food and shows benefits to memory, but the study is rare on the brain healthy value of its oil. Previously, we had reported that the Hizikia fusiforme functional oil (HFFO) contains arachidonic acid, 11,14,17-eicosatrienoic acid, phytol, and other molecules displaying in vitro acetylcholinesterase inhibitory and nitroxide scavenging activity; however, the in vivo effect remains unclear. In this study, we further investigated its potential effects against lipopolysaccharides (LPS)- or aluminum trichloride (AlCl3)-induced memory deficiency in zebrafish and its drug-related properties in silica.Entities:
Keywords: ADMET; HFFO; memory impairment; neuroinflammation; oxidative stress
Year: 2022 PMID: 36158548 PMCID: PMC9500236 DOI: 10.3389/fnagi.2022.941994
Source DB: PubMed Journal: Front Aging Neurosci ISSN: 1663-4365 Impact factor: 5.702
Figure 1The latency (s) of first entry into the enriched chamber (EC) zone of the T-maze test. LPS model (A), AlCl3 model (B). n = 10, *p < 0.05, **p < 0.01, ***p < 0.005, ****p < 0.001, vs. the control group; #p < 0.05, ##p < 0.01, ###p < 0.005, ####p < 0.001, vs. the model group.
Figure 2Heatmaps of zebrafish activity in the T-maze on the fifth day. The X-axis and Y-axis in the figure represent the motion trajectory of zebrafish, while the Z-axis represents the residence time of zebrafish. The higher the Z-axis, the longer the residence time of zebrafish at a certain point.
Figure 3IL-1β (A–D) and TNF-α (E–H) content in zebrafish brain and peripheral tissue, and ACh (I,J) and MDA (K,L) levels in zebrafish brain tissue. n = 3, *p < 0.05, **p < 0.01, ***p < 0.005, ****p < 0.001, vs. the control group; #p < 0.05, ##p < 0.01, ###p < 0.005, ####p < 0.001, vs. the model group.
Molecular docking affinity (kcal/mol) of phytol and eicosatrienoic acid with NF-κB and COX-2, respectively.
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| Phytol | NF-κB | 1VKX | −6.1 |
| Phytol | COX-2 | 5IKT | −7.2 |
| Eicosatrienoic acid | NF-κB | 1VKX | −6.1 |
| Eicosatrienoic acid | COX-2 | 5IKT | −6.8 |
Figure 4Molecular docking of ligands with their potential targets. Docking interaction 3D view of phytol with NF-κB (A) and COX-2 (B), and eicosatrienoic acid with NF-κB (C) and COX-2 (D). Residues are within the distance of 4Å, and the yellow dotted lines indicate hydrogen bonds.
ADMET and drug-likeness properties of HFFO main ingredient through online prediction tool of ADMETlab 2.0.
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| Caco-2 permeability (log cm/s) | −5.263 |
| −5.168 |
| −5.027 |
| −4.960 |
| −4.513 |
| −5.059 |
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| MDCK permeability (cm/s) | 7.8e−05 |
| 9.3e−05 |
| 2.5e−05 |
| 2.8e−05 |
| 1.3e−05 |
| 3.3e−05 |
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| Pgp–inhibitor | 0.000 |
| 0.000 |
| 0.009 |
| 0.0280 |
| 0.049 |
| 0.009 |
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| Pgp–substrate | 0.000 |
| 0.000 |
| 0.000 |
| 0.000 |
| 0.002 |
| 0.000 |
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| HIA | 0.033 |
| 0.027 |
| 0.005 |
| 0.005 |
| 0.003 |
| 0.015 |
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| F20% | 1.000 |
| 1.000 |
| 0.644 |
| 0.754 |
| 0.848 |
| 0.828 |
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| PPB | 0.999 |
| 0.993 |
| 0.990 |
| 0.982 |
| 0.989 |
| 0.997 |
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| VD (L/kg) | 0.735 |
| 0.912 |
| 0.608 |
| 0.416 |
| 2.298 |
| 0.503 |
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| BBB penetration | 0.002 |
| 0.005 |
| 0.060 |
| 0.163 |
| 0.2 |
| 0.0310 |
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| Fu | 0.001 |
| 0.000 |
| 0.001 |
| 0.001 |
| 0.002 |
| 0.0006 |
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| CYP1A2–inhibitor | 0.205 | – | 0.241 | – | 0.300 | – | 0.256 | – | 0.387 | – | 0.251 | – |
| CYP1A2–substrate | 0.857 | + | 0.638 | + | 0.194 | – | 0.202 | – | 0.192 | – | 0.196 | – |
| CYP2C19–inhibitor | 0.114 | – | 0.168 | – | 0.203 | – | 0.099 | – | 0.437 | – | 0.101 | – |
| CYP2C19–substrate | 0.166 | – | 0.118 | – | 0.110 | – | 0.213 | – | 0.072 | – | 0.090 | – |
| CYP2C9–inhibitor | 0.272 | – | 0.299 | – | 0.174 | – | 0.249 | – | 0.383 | – | 0.296 | – |
| CYP2C9–substrate | 0.991 | + | 0.991 | + | 0.989 | + | 0.986 | + | 0.863 | + | 0.991 | + |
| CYP2D6–inhibitor | 0.149 | – | 0.110 | – | 0.008 | – | 0.007 | – | 0.197 | – | 0.018 | – |
| CYP2D6–substrate | 0.939 | + | 0.921 | + | 0.054 | – | 0.069 | – | 0.037 | – | 0.129 | – |
| CYP3A4–inhibitor | 0.100 | – | 0.130 | – | 0.024 | – | 0.017 | – | 0.262 | – | 0.036 | – |
| CYP3A4–substrate | 0.070 | – | 0.048 | – | 0.019 | – | 0.024 | – | 0.116 | – | 0.022 | – |
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| CL (mL/min/kg) | 3.007 |
| 3.084 |
| 2.377 |
| 2.303 |
| 5.653 |
| 2.373 |
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| T1/2 | 0.916 | – | 0.887 | – | 0.610 | – | 0.718 | – | 0.210 | – | 0.827 | – |
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| hERG blockers | 0.026 |
| 0.027 |
| 0.056 |
| 0.040 |
| 0.010 |
| 0.036 |
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| H–HT | 0.251 |
| 0.281 |
| 0.026 |
| 0.030 |
| 0.046 |
| 0.039 |
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| DILI | 0.006 |
| 0.014 |
| 0.043 |
| 0.042 |
| 0.064 |
| 0.018 |
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| Ames toxicity | 0.945 |
| 0.604 |
| 0.005 |
| 0.006 |
| 0.001 |
| 0.002 |
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| Rat oral acute toxicity | 0.003 |
| 0.012 |
| 0.029 |
| 0.037 |
| 0.012 |
| 0.018 |
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| FDAMDD | 0.349 |
| 0.206 |
| 0.015 |
| 0.015 |
| 0.666 |
| 0.023 |
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| Skin sensitization | 0.959 |
| 0.953 |
| 0.899 |
| 0.807 |
| 0.970 |
| 0.912 |
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| Carcinogenicity | 0.783 |
| 0.557 |
| 0.064 |
| 0.078 |
| 0.021 |
| 0.050 |
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| Eye corrosion | 0.147 |
| 0.414 |
| 0.977 |
| 0.979 |
| 0.851 |
| 0.966 |
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| Respiratory toxicity | 0.855 |
| 0.845 |
| 0.891 |
| 0.848 |
| 0.042 |
| 0.805 |
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| MCE-18 (Ivanenkov et al., | 0.000 |
| 0.000 |
| 0.000 |
| 0.000 |
| 4.000 |
| 0.000 |
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| Lipinski rule (Lipinski et al., | accepted |
| accepted |
| accepted |
| accepted |
| accepted |
| accepted |
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| Pfizer rule (Hughes et al., | accepted |
| rejected |
| rejected |
| rejected |
| rejected |
| rejected |
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| Golden triangle (Johnson et al., | accepted |
| accepted |
| accepted |
| rejected |
| rejected |
| rejected |
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| GSK rule (Guo et al., | accepted |
| rejected |
| rejected |
| accepted |
| rejected |
| accepted |
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•: Excellent, •: medium, •: bad.