Discovery of a 4-Hydroxy-3'-Trifluoromethoxy-Substituted Resveratrol Derivative as an Anti-Aging Agent

Abstract

With the intensification of population aging, aging-related diseases are attracting more and more attention, thus, the study of aging mechanisms and anti-aging drugs is becoming increasingly urgent. Resveratrol is a potential candidate as an anti-aging agent, but its low bioavailability limits its application in vivo. In this work, a 4-hydroxy-3'-trifluoromethoxy-substituted resveratrol derivative (4-6), owing to its superior cell accumulation, could inhibit NO production in an inflammatory cell model, inhibit oxidative cytotoxicity, and reduce ROS accumulation and the population of apoptotic cells in an oxidative stress cell model. In D-galactose (D-gal)-stimulated aging mice, 4-6 could reverse liver and kidney damage; protect the serum, brain, and liver against oxidative stress; and increase the body's immunity in the spleen. Further D-gal-induced brain aging studies showed that 4-6 could improve the pathological changes in the hippocampus and the dysfunction of the cholinergic system. Moreover, protein expression related to aging, oxidative stress, and apoptosis in the brain tissue homogenate measured via Western blotting also showed that 4-6 could ameliorate brain aging by protecting against oxidative stress and reducing apoptosis. This work revealed that meta-trifluoromethoxy substituted 4-6 deserved to be further investigated as an effective anti-aging candidate drug.

Keywords: D-galactose; anti-aging; apoptosis; inflammation; oxidative stress; resveratrol derivatives.

Figure 1

Structures of resveratrol and its derivatives.

Figure 2

Effects of resveratrol derivatives on oxidative stress in Raw264.7 cells stimulated with t-BHP. (A) Cells were incubated with drugs for 24 h, then induced with 2 mM t-BHP for 3 h. (B) Cells were treated with 4–6 for 24 h, then induced with 0.5, 1, 2, or 3 mM t-BHP for 3 h. The MTT method was used to measure cytotoxicity. (A) *** p < 0.001 vs. the control group; ^# p < 0.05, ^## p < 0.01, ^### p < 0.001 vs. the 2 mM t-BHP group. (B) ** p < 0.01, *** p < 0.001 vs. the control group; ^### p < 0.001 vs. the 0.5 mM group; ^● p < 0.05, ^●● p < 0.01, ^●●● p < 0.001 vs. the 1 mM group; ^★★★ p < 0.001 vs. the 2 mM group; ^▲▲▲ p < 0.001 vs. the 3 mM group.

Figure 3

Cellular uptake of resveratrol and its active derivatives. Cells were pre-treated with compounds for 0.5, 1, 2, 3, or 4 h. Measurement of the intracellular compound concentrations was performed using HPLC.

Figure 4

Effect of 1–1 or 4–6 on the excessive accumulation of ROS in Raw264.7 cells induced by t-BHP. (A) ROS levels induced by 2 mM t-BHP for different times. (B) ROS levels induced by 2 mM t-BHP for 10 min after cells were treated with 2.5, 5, and 10 μM of 1–1 or 4–6 for 1 h. Measurement of the ROS levels was carried out using flow cytometry. * p < 0.05, ** p < 0.01, *** p < 0.001 vs. the control group. ^### p < 0.001 vs. the t-BHP group.

Figure 5

Flow cytometric analysis of apoptosis in Raw264.7 cells induced by t-BHP. Apoptosis induced by 1 mM t-BHP for 1 h after cells were pre-treated with 5 or 10 μM 1–1 or 4–6 for 1 h. Measurement of apoptosis was carried out using flow cytometry. The percentages of normal, early apoptosis, late apoptosis, and necrosis are indicated in each quadrant; sequentially lower-left, lower-right, upper-right, and upper-left.

Figure 6

Molecular docking of resveratrol 1–1 and its derivative 4–6 with the SIRT1 protein structure (PDB ID 5BTR). (A,B) SIRT1-1–1 interactions on 3D and 2D diagrams. (C,D) SIRT1-4–6 interactions on 3D and 2D diagrams.

Figure 7

Serum AST (A), ALT (B), BUN (C), and CRE (D) levels for liver and kidney function. These biomarkers were assessed using the corresponding detection reagent kits. *** p < 0.001 vs. the control group. ^# p < 0.05, ^## p < 0.01, ^### p < 0.001 vs. the model group.

Figure 8

Effects of 4–6 on serum oxidative stress biomarkers in aging mice stimulated with D-gal. (A) T-AOC. (B) CAT. (C) GPx. (D) SOD. These oxidative stress biomarkers were assessed using their detection reagent kits. * p < 0.05, ** p < 0.01, *** p < 0.001 vs. the control group. ^# p < 0.05, ^## p < 0.01, ^### p < 0.001 vs. the model group.

Figure 9

Effects of 4–6 on oxidative stress biomarkers in the brain. (A) MDA. (B) CAT. (C) GPx. (D) SOD. These oxidative stress biomarkers were assessed using their detection reagent kits. ** p < 0.01,*** p < 0.001 vs. the control group. ^# p < 0.05, ^## p < 0.01, ^### p < 0.001 vs. the model group.

Figure 10

Effects of 4–6 on oxidative stress biomarkers in the liver. (A) MDA. (B) CAT. (C) GPx. (D) SOD. These oxidative stress biomarkers were assessed using their detection reagent kits. ** p < 0.01, *** p < 0.001 vs. the control group. ^## p < 0.01, ^### p < 0.001 vs. the model group.

Figure 11

Effects of 4–6 on MDA (A), iNOS, IL-6, TNF-α, and SA-β-gal in the spleen of D-gal-stimulated aging mice (B). The MDA level was assessed using its detection reagent kit. The expressions of iNOS, IL-6, TNF-α, and SA-β-gal were analyzed using Western blotting. ImageJ 1.53e software was used to analyze the densitometric quantifications. * p < 0.05, ** p < 0.01, *** p < 0.001 vs. the control group. ^## p < 0.01, ^### p < 0.001 vs. the model group (C).

Figure 12

Effects on the histopathology of the hippocampus, liver, and spleen. HE staining was used for the paraffin sections. (Scale bar: hippocampus: CA1, 50 μM; CA3, 50 μM; DG, 200 μM. liver, 50 μM. spleen, 200 μM).

Figure 13

Effects on the histopathology of the subfields of the hippocampus (CA1, CA3, and DG). Nissl staining was used for the paraffin sections. (Scale bar: CA1, 50 μM; CA3, 50 μM; DG, 200 μM).

Figure 14

Effects of 4–6 on (A) Ach and (B) AchE in brain tissue. The Ach level and AchE activity were assessed using their corresponding detection reagent kits. ** p < 0.01, *** p < 0.001 vs. the control group. ^## p < 0.01, ^### p < 0.001 vs. the model group.

Figure 15

Effects on aging, oxidative stress, and apoptosis in brain tissue. (A) The expression levels of the corresponding proteins were analyzed with Western blotting. (B–D) Quantitative analysis of the corresponding proteins. ImageJ software was used to analyze the densitometric quantification. ** p < 0.01, *** p < 0.001 vs. the control group. ^## p < 0.01, ^### p < 0.001 vs. the model group.