ESTUDIO FITOQUÍMICO DE Echinopsis peruviana

Baldera-Aguayo, Pedro A; Pinedo, Víctor M. Reyna

doi:10.37761/rsqp.v80i3.229

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Natural products sourced from the biodiversity in Peru were gathered from the literature up to 2019, encompassing 48 articles [ 3 , 4 , 5 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 ]. The collected data encompassed the SMILES codes, chemical names, organism nam...…”

Section: Methodsmentioning

confidence: 99%

A Machine Learning Approach for Predicting Caco-2 Cell Permeability in Natural Products from the Biodiversity in Peru

Acuña-Guzman,

Montoya-Alfaro,

Negrón-Ballarte

et al. 2024

Pharmaceuticals

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Background: Peru is one of the most biodiverse countries in the world, which is reflected in its wealth of knowledge about medicinal plants. However, there is a lack of information regarding intestinal absorption and the permeability of natural products. The human colon adenocarcinoma cell line (Caco-2) is an in vitro assay used to measure apparent permeability. This study aims to develop a quantitative structure–property relationship (QSPR) model using machine learning algorithms to predict the apparent permeability of the Caco-2 cell in natural products from Peru. Methods: A dataset of 1817 compounds, including experimental log Papp values and molecular descriptors, was utilized. Six QSPR models were constructed: a multiple linear regression (MLR) model, a partial least squares regression (PLS) model, a support vector machine regression (SVM) model, a random forest (RF) model, a gradient boosting machine (GBM) model, and an SVM–RF–GBM model. Results: An evaluation of the testing set revealed that the MLR and PLS models exhibited an RMSE = 0.47 and R2 = 0.63. In contrast, the SVM, RF, and GBM models showcased an RMSE = 0.39–0.40 and R2 = 0.73–0.74. Notably, the SVM–RF–GBM model demonstrated superior performance, with an RMSE = 0.38 and R2 = 0.76. The model predicted log Papp values for 502 natural products falling within the applicability domain, with 68.9% (n = 346) showing high permeability, suggesting the potential for intestinal absorption. Additionally, we categorized the natural products into six metabolic pathways and assessed their drug-likeness. Conclusions: Our results provide insights into the potential intestinal absorption of natural products in Peru, thus facilitating drug development and pharmaceutical discovery efforts.

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Section: Methodsmentioning

confidence: 99%

A Machine Learning Approach for Predicting Caco-2 Cell Permeability in Natural Products from the Biodiversity in Peru

Acuña-Guzman,

Montoya-Alfaro,

Negrón-Ballarte

et al. 2024

Pharmaceuticals

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“…(cactus de San Pedro) [19], which contains mescaline. In this regard, it has been proposed that mescaline is one of the main active compounds in Echinopsis spp., and that the highest concentration is mainly found in the chlorenchymatic layer [19,20]. Furthermore, it has been proposed that the mescaline content in different Echinopsis species varies from 0.053 to 4.7% of dry-weight biomass [19], directly correlating with the most used plants in traditional medicine and their alkaloid content.…”

Section: Introductionmentioning

confidence: 99%

Alkaloid and Nitrogenated Compounds from Different Sections of Coryphantha macromeris Plants and Callus Cultures

Viera-Escareño,

Perez-Molphe Balch,

Gómez-Aguirre

et al. 2023

Applied Sciences

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One of the distinctive characteristics of cacti species is the presence of alkaloids. Alkaloids are nitrogenated molecules with hallucinogenic and pharmacological properties in humans and other animals. Plant cell, tissue, and organ culture have emerged as an effective tool for investigating the biosynthesis of a variety of functional metabolites and for studying the preservation of endangered plant species. In this study, we examined the alkaloid and nitrogenated compound profiles of the aerial and radicular sections of Coryphantha macromeris plants that were cultivated in both greenhouse and in vitro conditions. Additionally, we analyzed the callus cultures generated from stem discs. To perform these analyses, Ultra-High-Performance Liquid Chromatography coupled with High-Resolution Mass Spectrometry (UHPLC-PDA-HESI-Orbitrap-MS/MS) was utilized. Under the working parameters, 78 compounds were detected, and 61 of them were identified. Among the identified compounds, the in vitro plants presented 24 compounds, greenhouse plants a total of 21 compounds, and callus tissue 16 compounds. On the other hand, 7 compounds (laurydiethanolamine, toluic acids, and their derivatives) were detected in all systems, suggesting that these metabolites may serve as markers to help find the authenticity of C. macromeris preparations, and that, plant and cell-tissue cultures with this plant species are suitable for the biosynthesis of the selected compounds. In addition, our research suggests that no alkaloids with reported psychotropic properties are present in C. macromeris.

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ESTUDIO FITOQUÍMICO DE Echinopsis peruviana

Cited by 2 publications

References 7 publications

A Machine Learning Approach for Predicting Caco-2 Cell Permeability in Natural Products from the Biodiversity in Peru

A Machine Learning Approach for Predicting Caco-2 Cell Permeability in Natural Products from the Biodiversity in Peru

Alkaloid and Nitrogenated Compounds from Different Sections of Coryphantha macromeris Plants and Callus Cultures

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