Selection of Mexican Medicinal Plants by Identification of Potential Phytochemicals with Anti-Aging, Anti-Inflammatory, and Anti-Oxidant Properties through Network Analysis and Chemoinformatic Screening

Abstract

Many natural products have been acquired from plants for their helpful properties. Medicinal plants are used for treating a variety of pathologies or symptoms. The axes of many pathological processes are inflammation, oxidative stress, and senescence. This work is focused on identifying Mexican medicinal plants with potential anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects through network analysis and chemoinformatic screening of their phytochemicals. We used computational methods to analyze drug-like phytochemicals in Mexican medicinal plants, multi-target compounds, and signaling pathways related to anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence mechanisms. A total of 1373 phytochemicals are found in 1025 Mexican medicinal plants, and 148 compounds showed no harmful functionalities. These compounds displayed comparable structures with reference molecules. Based on their capacity to interact with pharmacological targets, three clusters of Mexican medicinal plants have been established. Curatella americana, Ximenia americana, Malvastrum coromandelianum, and Manilkara zapota all have anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects. Plumeria rubra, Lonchocarpus yucatanensis, and Salvia polystachya contained phytochemicals with anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence reported activity. Lonchocarpus guatemalensis, Vallesia glabra, Erythrina oaxacana, and Erythrina sousae have drug-like phytochemicals with potential anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects. Between the drug-like phytochemicals, lonchocarpin, vallesine, and erysotrine exhibit potential anti-oxidant, anti-inflammatory, anti-aging, and anti-senescence effects. For the first time, we conducted an initial virtual screening of selected Mexican medicinal plants, which was subsequently confirmed in vivo, evaluating the anti-inflammatory activity of Lonchocarpus guatemalensis Benth in mice.

Keywords: Mexican; anti-aging; anti-inflammatory; anti-oxidants; database; medicinal; native; network; phytochemicals; plants; senolytic.

Figure 1

Workflow for identifying MMPs and drug-like phytochemicals related to AOX-AINF-AAG-ASEN activities. (1) Relevant MMPs by multi-effect reported. (2) Relevant MMPs without reported effect but with phytochemicals with reported activity. (3) Determination of drug-like phytochemicals from MMPs without AOX-AINF-AAG-ASEN background. (4) Structural comparison between drug-like phytochemicals and reference AOX-AINF-AAG-ASEN compounds. (5) MMPs that have potential drug-like phytochemicals can network with pharmacological targets. (6) Enrichment analysis of the pharmacological targets from the most relevant MMPs.

Figure 2

Graphical representation of the MMP dataset into a network. (A) The taxonomic characteristics of the MMPs are integrated into the structural network, which also includes information on the availability or lack of scientific support for AOX-AINF-AAG-ASEN properties. (B) Network with the most relevant node. The table summarizes the ten most connected nodes.

Figure 3

Structural network of MMPs that may have AOX-AINF-AAG-ASEN properties based on their chemical content. (A) MMP network lacks scientific evidence of AOX-AINF-AAG-ASEN activity but has proven phytochemicals. (B) The most relevant nodes of families, genera, and species of MMPs with potential AOX-AINF-AAG-ASEN activity and phytochemicals with reported studied activities. Table 3 shows the top 10 of the most interconnected nodes.

Figure 4

Hierarchical structural clustering of the AOX−AINF-AAG−ASEN compounds. The top cluster with the most similar compounds is shown and highlighted in a red rectangle. The cluster comprises the reference compounds paromomycin, magnesium ascorbate, calcium ascorbate, rapamycin, digoxin, geldanamycin, alvespimycin, oleuropein, strophanthin k, natamycin, streptomycin, ouabain, tunicamycin, ginsenoside Rb1, rapamycin, roxithromycin, timosaponin a-III, and azithromycin. It showed a similarity among molecular descriptors, such as cLogP, symmetric atoms, aromatic atoms, ring atoms, and log.kp.cm.

Figure 5

Steps of the process of selecting some AOX−AINF−AAG−ASEN potential compounds involved comparing 149 drug-like phytochemicals with the reference paromomycin based on their structural similarity. (A) The dashed line represents the suitable number of clusters determined by the Elbow method. (B) Cluster analysis of Ward’s method; the senolytic cluster is shaped in red and the senolytic molecule as 1. (C) Cluster plot using K-means showed the same molecules in the senolytic cluster marked in blue. (D) Silhouette cluster representation to corroborate the previously described cluster analysis methods. * Means matrix of distances used in clustering by Ward’s method in (B).

Figure 6

MMP network lacking AOX-AINF-AAG-ASEN properties with their phytochemicals and biological targets. (A) The network was constructed using MMPs, their putative AOX-AINF-AAG-ASEN compounds, and their biological targets reported in PubChem. The signaling pathways involved in these processes were many (see Methods). The network was designed and analyzed using Cytoscape software. (B) The structural network was built with the Cytohubba plugin for the top 10 most connected nodes.

Figure 7

Effects of Lonchocarpus guatemalensis (10, 31, and 100 mg/kg) and indomethacin (10 mg/kg) on carrageenan-induced paw edema in mice. A statistically significant reduction in the percentage of edema can be observed from 1 to 6 h during treatment with L. guatemalensis at 30 and 100 mg/kg, which are similar to anti-inflammatory positive control indomethacin. Values are expressed as mean ± standard error of the mean (n = 6). Different symbols show significant (p < 0.05) differences between treatments according to ANOVA) post hoc Dunnett’s test. # carrageenan vs. indomethacin. $ carrageenan vs. HE (10 mg/kg). ∞ carrageenan vs. HE (31 mg/kg). * carrageenan vs. HE (100 mg/kg).