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Isolation and Structural Characterization of Bioactive Molecules on Prostate Cancer from Mayan Traditional Medicinal Plants.

ABSTRACT: Prostate cancer is the most common cancer in men around the world. It is a complex and heterogeneous disease in which androgens and their receptors play a crucial role in the progression and development. The current treatment for prostate cancer is a combination of surgery, hormone therapy, radiation and chemotherapy. Therapeutic agents commonly used in the clinic include steroidal and non-steroidal anti-androgens, such as cyproterone acetate, bicalutamide and enzalutamide. These few agents have multiple adverse effects and are not 100% effective. Several plant compounds and mixtures, including grape seed polyphenol extracts, lycopene and tomato preparations, soy isoflavones, and green tea extracts, have been shown to be effective against prostate cancer cell growth. In vivo activity of some isolated compounds like capsaicin and curcumin was reported in prostate cancer murine models. We prepared a library of plant extracts from traditional Mayan medicine. These plants were selected for their use in the contemporaneous Mayan communities for the treatment of different diseases. The extracts were assessed in a phenotypic screening using LNCaP prostate cancer androgen sensitive cell line, with a fixed dose of 25 μg/mL. MTT assay identified seven out of ten plants with interesting anti-neoplastic activity. Extracts from these plants were subjected to a bioguided fractionation to study their major components. We identified three compounds with anti-neoplastic effects against LNCaP cells, one of which shows selectivity for neoplastic compared to benign cells.

SUBMITTER: Fort RS

PROVIDER: S-EPMC6160984 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundNeorautanenia mitis, Hydnora abyssinica, and Senna surattensis are medicinal plants with a variety of traditional uses. In this study, we sought to isolate the bioactive compounds responsible for some of these activities, and to uncover their other potential medicinal properties.MethodsThe DCM and ethanol extracts of the roots of N. mitis and H. abyssinica, and the leaves of S. surattensis were prepared and their phytochemical components were isolated and purified using chromatographic methods. These extracts and their pure phytochemical components were evaluated in in-vitro models for their inhibitory activities against Plasmodium falciparum, Trypanosoma brucei rhodesiense, Mycobacterium tuberculosis, α-amylase (AA), and α-glucosidase (AG).ResultsRautandiol B had significant inhibitory activities against two strains of Plasmodium falciparum showing a high safety ratio (SR) and IC50 values of 0.40 ± 0.07 μM (SR - 108) and 0.74 ± 0.29 μM (SR - 133) against TM4/8.2 and K1CB1, respectively. While (-)-2-isopentenyl-3-hydroxy-8-9-methylenedioxypterocarpan showed the highest inhibitory activity against T. brucei rhodesiense with an IC50 value of 4.87 ± 0.49 μM (SR > 5.83). All crude extracts showed inhibitory activities against AA and AG, with three of the most active phytochemical components; rautandiol A, catechin, and dolineon, having only modest activities against AG with IC50 values of 0.28 mM, 0.36 mM and 0.66 mM, respectively.ConclusionThese studies have led to the identification of lead compounds with potential for future drug development, including Rautandiol B, as a potential lead compound against Plasmodium falciparum. The relatively higher inhibitory activities of the crude extracts against AG and AA over their isolated components could be due to the synergistic effects between their phytochemical components. These crude extracts could potentially serve as alternative inhibitors of AG and AA and as therapeutics for diabetes.

Project description:BackgroundThere are handful hypothesis-driven ethnobotanical studies in Nepal. In this study, we tested the non-random medicinal plant selection hypothesis using national- and community-level datasets through three different types of regression: linear model with raw data, linear model with log-transformed data and negative binomial model.MethodsFor each of these model, we identified over-utilized families as those with highest positive Studentized residuals and underutilized families with highest negative Studentized residuals. The national-level data were collected from online databases and available literature while the community-level data were collected from Baitadi and Darchula districts.ResultsBoth dataset showed larger variance (national dataset mean 6.51 < variance 156.31, community dataset mean 1.16 < variance 2.38). All three types of regression were important to determine the medicinal plant species selection and use differences among the total plant families, although negative binomial regression was most useful. The negative binomial showed a positive nonlinear relationship between total plant family size and number of medicinal species per family for the national dataset (β1 = 0.0160 ± 0.0009, Z1 = 16.59, p < 0.00001, AIC1 = 1181), and with similar slope and stronger performance for the community dataset (β2 = 0.1747 ± 0.0199, Z2 = 8.76, p < 0.00001, AIC2 = 270.78). Moraceae and Euphorbiaceae were found over-utilized while Rosaceae, Cyperaceae and Caryophyllaceae were recorded as underutilized.ConclusionsAs our datasets showed larger variance, negative binomial regression was found the most useful for testing non-random medicinal plant selection hypothesis. The predictions made by non-random selection of medicinal plants hypothesis holds true for community-level studies. The identification of over-utilized families is the first step toward sustainable conservation of plant resources and it provides a baseline for pharmacological research that might be leading to drug discovery.

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Isolation and Structural Characterization of Bioactive Molecules on Prostate Cancer from Mayan Traditional Medicinal Plants.

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