Resveratrol is a polyphenolic compound found in certain plants, including grapes, berries, and peanuts. It has been the subject of numerous studies due to its potential health benefits. Some studies suggest that resveratrol may help to protect against a range of health issues, including heart disease, cancer, and neurological disorders.

One of the earliest studies on resveratrol was conducted in 2003 and published in the journal Nature. The study found that resveratrol could extend the lifespan of yeast cells by up to 80%. The researchers also found that resveratrol could activate a gene called SIRT1, which is thought to play a role in aging.

In a 2006 study published in the Journal of Agricultural and Food Chemistry, researchers found that resveratrol could inhibit the growth of cancer cells. The study also found that resveratrol could induce apoptosis, or programmed cell death, in cancer cells.

Overall, the research on resveratrol suggests that it may have a wide range of health benefits.

Now, thanks to a recent study published in Nature, we can add one more potential benefit to the use of resveratrol supplements - endurance.

Using network pharmacology and molecular docking, researchers at Ningxia Medical University in China investigated the potential mechanism of resveratrol in anti-fatigue. They found that resveratrol targets multiple fatigue-related genes and pathways, including the AGE-RAGE signaling pathway in diabetic complications and pathways in cancer. Molecular docking also confirmed that key target genes had good binding activity to resveratrol.

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In this study, the anti-fatigue effects of resveratrol were investigated by screening for the compound's targets using various databases. The fatigue targets were obtained by merging data from GeneCard, DisGeNET, OMIM, and DrugBank databases. The intersection of the resveratrol action target and fatigue target was then used to identify the resveratrol anti-fatigue target. The resveratrol anti-fatigue target Protein-protein interaction (PPI) network was constructed and analyzed to identify the top 10 core target proteins. Enrichment analysis of resveratrol anti-fatigue target genes was also conducted. Additionally, animal experiments were carried out to investigate the effects of resveratrol on exercise endurance in mice.

The study aimed to identify the anti-fatigue targets of resveratrol and their effects on exercise performance in mice. Resveratrol, a polyphenolic compound found in red grapes and various other plants, has been shown to have numerous beneficial effects on human health, including anti-cancer, anti-inflammatory, and antioxidant properties. 

To achieve the study's objectives, a series of methods were employed. Firstly, several databases, including CTD, DGIdb, DrugBank, Swiss Target Prediction, and TCMSP, were searched for potential targets of resveratrol. These targets were merged, deduplicated, and non-human targets were eliminated. The study also screened for targets of fatigue from various databases, including GeneCard, DisGeNET, OMIM, and DrugBank, and eliminated duplicate targets.

To identify the anti-fatigue targets of resveratrol, the study used the Venn diagram to determine the intersection of resveratrol action targets and fatigue targets. The study then constructed the resveratrol anti-fatigue target Protein-protein interaction (PPI) network and identified the core target proteins. To do this, the resveratrol anti-fatigue target proteins were uploaded to the String database, and protein interactions with a confidence score > 0.4 were selected. The obtained data were imported into Cytoscape 3.7.1, and the topological parameters moderate centrality, compact centrality, and betweenness centrality were analyzed to screen the top 10 proteins as core target proteins.

The study also conducted enrichment analysis of resveratrol anti-fatigue target genes using the DAVID database. This analysis included Gene ontology (GO) and Kyoto encyclopedia of gene and genome (KEGG) pathway analysis. GO analysis includes analysis of three aspects: cellular component (CC), molecular function (MF), and biological process (BP).

Molecular docking was used to determine the binding affinity of resveratrol to the core target proteins. The PDB database was searched and downloaded for the PDB file of the core target protein, and Autodock Tools were used to dehydrate and hydrogenate it. The mol2 file of resveratrol was downloaded from PubChem, and molecular docking of resveratrol to core target proteins was performed using Autodock Vina. The docking results were visualized using Pymol software.

The study then conducted animal experiments on healthy male mice to investigate the anti-fatigue effects of resveratrol. The mice were divided into four groups, including a quiet control group (NC), an endurance training control group (EC), an endurance training control + Resveratrol group (EC + RES), and an endurance training control group + Glucose group (EC + GLU). After six weeks of treatment, exhaustive swimming was performed, and relevant indicators of anti-exercise fatigue were measured.

The study was conducted by researchers from Ningxia Medical University in China, including Peipei Ma, Zhizhong Wang, Jinlei Li, Qing Huang, Shijie Wei, and Hurong Ge. Ma was responsible for writing the experimental plan and carrying out the analysis of data, while Li was responsible for data collection and Huang was responsible for preparing the animal experimental drugs. Wei conducted the swimming training for mice, and Ge provided overall direction for the experiments. All authors contributed to the study's concepts and design, and the manuscript was written by Ma with input and approval from all authors.

The authors of this study made significant contributions to the research, including the development of concepts and design. J.L. was responsible for collecting data for network pharmacology and feeding the experimental mice, while Q.H. prepared the animal experimental drugs. S.W. conducted swimming training for the mice. P.M. created the entire experimental plan, performed the analysis of network pharmacological data, conducted the molecular docking operation and analysis, and analyzed the results of the animal experiment gavage. H.G. and Z.W. supervised all the experiments in this study. The initial draft of the manuscript was written by P.M., and all authors provided feedback on previous versions of the manuscript. All authors have reviewed and approved the final manuscript.

The study found that resveratrol can effectively improve exercise performance and reduce fatigue in mice. The core target proteins identified through the PPI network were involved in various biological processes, such as energy metabolism, immune response, and cell cycle regulation.

The study's methodology also provides a useful framework for the identification and validation of other potential anti-fatigue agents.

In today's fast-paced world, many people are facing sub-health states due to unreasonable diet, lack of exercise, irregular work and rest, mental stress, high psychological pressure, and long-term negative emotions. If the treatment for recurrent fatigue is inappropriate, it may turn into chronic fatigue, affecting physical and psychological health.

Experts have been researching effective prevention and treatment of fatigue, but there are still many uncertainties. Resveratrol, a compound with various biological functions and medicinal values, has been found to have a high scavenging ability to various free radicals and can effectively inhibit lipid peroxidation, making it a potential anti-fatigue candidate. This study used network pharmacology to predict targets and analyze drug pathways to explore the mechanism of resveratrol in anti-fatigue. 

The results showed that resveratrol can improve exercise capacity and delay fatigue by acting on core target genes such as TP53, PIK3R1, AKT1, PIK3CA, and MAPK1, affecting various pathways. Animal experiments confirmed the anti-fatigue efficacy of resveratrol, providing a theoretical basis for the development of anti-fatigue preparations or health products.

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