Evaluation of the Possible Pathways Involved in the Protective Effects of Quercetin, Naringenin, and Rutin at the Gene, Protein and miRNA Levels Using In-Silico Multidimensional Data Analysis

Abstract

Flavonoids are secondary metabolites that are non-essential for plant growth or survival, and they also provide numerous health benefits to humans. They are antioxidants that shield plants from the ill effects of ultraviolet light, pests, and diseases. They are beneficial to health for several reasons, including lowering inflammation, boosting cardiovascular health, and lowering cancer risk. This study looked into the physicochemical features of these substances to determine the potential pharmacological pathways involved in their protective actions. Potential targets responsible for the protective effects of quercetin, naringenin, and rutin were identified with SwissADME. The associated biological processes and protein-protein networks were analyzed by using the GeneMANIA, Metascape, and STRING servers. All the flavonoids were predicted to be orally bioavailable, with more than 90% targets as enzymes, including kinases and lyases, and with common targets such as NOS2, CASP3, CASP9, CAT, BCL2, TNF, and HMOX1. TNF was shown to be a major target in over 250 interactions. To extract the "biological meanings" from the MCODE networks' constituent parts, a GO enrichment analysis was performed on each one. The most important transcription factors in gene regulation were RELA, NFKB1, PPARG, and SP1. Treatment with quercetin, naringenin, or rutin increased the expression and interaction of the microRNAs' hsa-miR-34a-5p, hsa-miR-30b-5p, hsa-let-7a-5p, and hsa-miR-26a-1-3p. The anticancer effects of hsa-miR-34a-5p have been experimentally confirmed. It also plays a critical role in controlling other cancer-related processes such as cell proliferation, apoptosis, EMT, and metastasis. This study's findings might lead to a deeper comprehension of the mechanisms responsible for flavonoids' protective effects and could present new avenues for exploration.

Keywords: computational analysis; flavonoids; gene interactions; miRNAs; pathways.

Figure 1

Illustrations of the structures of flavonoids and radar charts that represent their pharmacokinetic and physicochemical properties. The structures of (A) quercetin, (B) naringenin, and (C) rutin were adapted from SwissADME’s Marvin J S tool for visualization purposes in our study.

Figure 2

Boiled egg demonstration of quercetin, naringenin, and rutin.

Figure 3

Target classes binding to quercetin, naringenin, and rutin using SwissADME’s target prediction tool. (A) Quercetin targets; (B) naringenin targets, and (C) rutin targets.

Figure 4

The top significantly interacting proteins with flavonoids. (A) quercetin protein interactions; (B) naringenin protein interactions; and (C) rutin protein interactions (D) The GeneMANIA predicted interaction of targeted genes with the quercetin, rutin and naringenin.

Figure 5

The statistically significant enriched terms, hierarchically clustered for the three flavonoids. (A) Biological processes or pathways and diseases that may be treated by the three flavonoids; and (B) the network clusters converted into a network layout that showed a similarity score greater than 0.3. The darker the color, the more statistically significant the node (C) Transcription factors involved in gene regulation.

Figure 6

A network of the miRNA target interactions that were targeted by the three flavonoids via MIENTURNET. (A) Networks with microRNA and genes; (B) a bar illustrates the degree of involvement of each gene in protective mechanisms; (C) the number of interactions of each miRNA, (FDR means false discovery rate); and (D) the degree of involvement of each miRNA in protective mechanisms.

Figure 7

The major contributor genes involved in flavonoid interaction.