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. 2022 Feb 11:13:813772.
doi: 10.3389/fendo.2022.813772. eCollection 2022.

Systematic Understanding of Anti-Aging Effect of Coenzyme Q10 on Oocyte Through a Network Pharmacology Approach

Liuqing Yang  1 , Heng Wang  1   2 , SuJie Song  1   2 , Hongbin Xu  3 , Yun Chen  1 , Saisai Tian  4 , Yiqun Zhang  1 , Qin Zhang  1
Affiliations

Systematic Understanding of Anti-Aging Effect of Coenzyme Q10 on Oocyte Through a Network Pharmacology Approach

Liuqing Yang et al. Front Endocrinol (Lausanne). .

Abstract

Background: Maternal oocyte aging is strongly contributing to age-related decline in female fertility. Coenzyme Q10 (CoQ10) exerts positive effects in improving aging-related deterioration of oocyte quality, but the exact mechanism is unclear.

Objective: To reveal the system-level mechanism of CoQ10's anti-aging effect on oocytes based on network pharmacology.

Methods: This study adopted a systems network pharmacology approach, including target identification, data integration, network and module construction, bioinformatics analysis, molecular docking, and molecular dynamics simulation.

Result: A total of 27 potential therapeutic targets were screened out. Seven hub targets (PPARA, CAT, MAPK14, SQSTM1, HMOX1, GRB2, and GSR) were identified. Functional and pathway enrichment analysis indicated that these 27 putative targets exerted therapeutic effects on oocyte aging by regulating signaling pathways (e.g., PPAR, TNF, apoptosis, necroptosisn, prolactin, and MAPK signaling pathway), and are involved oxidation-reduction process, mitochondrion, enzyme binding, reactive oxygen species metabolic process, ATP binding, among others. In addition, five densely linked functional modules revealed the potential mechanisms of CoQ10 in improving aging-related deterioration of oocyte quality are closely related to antioxidant, mitochondrial function enhancement, autophagy, anti-apoptosis, and immune and endocrine system regulation. The molecular docking study reveals that seven hub targets have a good binding affinity towards CoQ10, and molecular dynamics simulation confirms the stability of the interaction between the hub targets and the CoQ10 ligand.

Conclusion: This network pharmacology study revealed the multiple mechanisms involved in the anti-aging effect of CoQ10 on oocytes. The molecular docking and molecular dynamics simulation provide evidence that CoQ10 may act on these hub targets to fight against oocytes aging.

Keywords: aging; coenzyme Q10; mechanism; molecular docking; molecular dynamic simulation; oocyte.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Workflow diagram of this research.
Figure 2
Figure 2
Venn diagram and PPI network of potential therapeutic targets. (A) Venn diagram of intersected targets of oocyte aging and CoQ10. (B) PPI network of potential therapeutic targets. The nodes’ colors are illustrated from yellow to red in descending order of degree values.
Figure 3
Figure 3
GO enrichment analysis. (A) The top 10 significantly enriched terms of each part. BP, biological process, CC, cell component, MF, molecular function. (B) The first lap indicates top 10 GO term, and the number of the genes corresponds to the outer lap. The second lap indicates the number of the genes in the genome background and -lg (p-value). The third lap indicates the DEGS. The fourth lap indicates the enrichment factor of each GO term.
Figure 4
Figure 4
The KEGG pathway analysis of the 27 potential therapeutic targets. (A) The 15 significant pathways. The bubbles’ sizes are indicated from big to small in descending order of the count of the potential targets enriched in the pathways. The bubbles’ colors are indicated from red to blue in descending order of -lg (p-value). (B) CoQ10-targets-pathways network. The width of the line is proportional to the number of connected points. (C) Module analysis of the target-pathway network. The diamond nodes represent the pathways, and the ellipse nodes represent the targets. The red nodes represent the hub genes obtained from the PPI network of potential therapeutic targets.
Figure 5
Figure 5
Molecular docking of 7 hub targets with CoQ10. (A) The binding poses of CAT complexed with CoQ10. (B) The binding poses of PPARA complexed with CoQ10. (C) The binding poses of MAPK14 complexed with CoQ10. (D) The binding poses of SQSTM1 complexed with CoQ10. (E) The binding poses of HMOX1 complexed with CoQ10. (F) The binding poses of GRB2 complexed with CoQ10. (G) The binding poses of GSR complexed with CoQ10.
Figure 6
Figure 6
RMSD change of targets backbone atoms in MD simulation. (A) RMSD of CAT-CoQ10 complex, RMSD of GRB2-CoQ10 complex, RMSD of MAPK14-CoQ10 complex (B) RMSD of HMOX1-CoQ10 complex, RMSD of PPARA-CoQ10 complex, RMSD of SQSTM1-CoQ10 complex, RMSD of GSR-CoQ10 complex.
Figure 7
Figure 7
RMSF of residues. (A) RMSF of GRB2-CoQ10 complex. (B) RMSF of HMOX1-CoQ10 complex. (C) RMSF of PPARA-CoQ10 complex. (D) RMSF of SQSTM1-CoQ10 complex. (E) RMSF of CAT-CoQ10 complex. (F) RMSF of GSR-CoQ10 complex. (G) RMSF of MAPK14-CoQ10 complex.
Figure 8
Figure 8
The two-dimensional FEL as a function of Rg and RMSD (defined in the text) for the complexes along 30 ns MD simulations. Snapshots from minimum energy wells were extracted. (A) CAT-CoQ10 complex. (B) PPARA-CoQ10 complex. (C) MAPK14-CoQ10 complex. (D) SQSTM1-CoQ10 complex. (E) HMOX1-CoQ10 complex. (F) GRB2-CoQ10 complex. (G) GSR-CoQ10 complex.
Figure 9
Figure 9
(A) The process of oxidative phosphorylation in the mitochondria. This figure shows the central role of CoQ10 as an electron and proton transporter in the mitochondrial respiratory chain. (B) This “ROS vicious cycle” depicts the production of mitochondrial ROS causing oxidative damage that leads to mitochondrial DNA damage, mitochondrial dysfunction, and further increasing the production of ROS.
Figure 10
Figure 10
The multiple roles of CoQ10 in oocyte.
See this image and copyright information in PMC

References

    1. Amanvermez R, Tosun M. An Update on Ovarian Aging and Ovarian Reserve Tests. Int J Fertil Steril (2016) 9(4):411–5. doi: 10.22074/ijfs.2015.4591 - DOI - PMC - PubMed
    1. Wang J, Chen L, Zhou C, Wang L, Xie H, Xiao Y, et al. . Prospective Chromosome Analysis of 3429 Amniocentesis Samples in China Using Copy Number Variation Sequencing. Am J Obstet Gynecol (2018) 219(3):287.e281–287.e218. doi: 10.1016/j.ajog.2018.05.030 - DOI - PubMed
    1. Zhu Q, Chen Q, Wang L, Lu X, Lyu Q, Wang Y, et al. . Live Birth Rates in the First Complete IVF Cycle Among 20 687 Women Using a Freeze-All Strategy. Hum Reprod (2018) 33(5):924–9. doi: 10.1093/humrep/dey044 - DOI - PubMed
    1. Chen Y, Wang X, Li L, Lu S, Zhang Z. New Cut-Off Values for Screening of Trisomy 21, 18 and Open Neural Tube Defects (ONTD) During the Second Trimester in Pregnant Women With Advanced Maternal Age. BMC Pregnancy Childbirth (2020) 20(1):776. doi: 10.1186/s12884-020-03464-z - DOI - PMC - PubMed
    1. Sunderam S, Kissin DM, Crawford SB, Folger SG, Jamieson DJ, Barfield WD. Assisted Reproductive Technology Surveillance–United State. MMWR Surveill Summ (2014) 63(10):1–28. doi: 10.15585/mmwr.ss6606a1 - DOI - PubMed

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