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.

Background/Objectives: Colombia harbors exceptional plant diversity, comprising over 31,000 formally identified species, of which approximately 6000 are classified as useful plants. Among these, 2567 species possess documented food and medicinal applications, with several traditionally utilized for managing febrile illnesses. Despite the global burden of dengue virus infection affecting millions annually, no specific antiviral therapy has been established. This study aimed to identify potential anti-dengue compounds from Colombian medicinal flora through machine learning-based quantitative structure–activity relationship (QSAR) modeling. Methods: An optimized XGBoost algorithm was developed through Bayesian hyperparameter optimization (Optuna, 50 trials) and trained on 2034 ChEMBL-derived activity records with experimentally validated anti-dengue activity (IC₅₀/EC₅₀). The model incorporated 887 molecular features comprising 43 physicochemical descriptors and 844 ECFP4 fingerprint bits selected via variance-based filtering. IC₅₀ and EC₅₀ endpoints were modeled independently based on their pharmacological distinction and negligible correlation (r = −0.04, p = 0.77). Through a systematic literature review, 2567 Colombian plant species from the Humboldt Institute’s official checklist were evaluated (2501 after removing duplicates and infraspecific taxa), identifying 358 with documented antiviral properties. Phytochemical analysis of 184 characterized species yielded 3267 unique compounds for virtual screening. A dual-endpoint classification strategy categorized compounds into nine activity classes based on combined potency thresholds (Low: pActivity ≤ 5.0, Medium: 5.0 < pActivity ≤ 6.0, High: pActivity > 6.0). Results: The optimized model achieved robust performance (Matthews correlation coefficient: 0.583; ROC-AUC: 0.896), validated through hold-out testing (MCC: 0.576) and Y-randomization (p < 0.01). Virtual screening identified 276 compounds (8.4%) with high predicted potency for both endpoints (“High-High”). Structural novelty analysis revealed that all 276 compounds exhibited Tanimoto similarity < 0.5 to the training set (median: 0.214), representing 145 unique Murcko scaffolds of which 144 (99.3%) were absent from the training data. Application of drug-likeness filtering (QED ≥ 0.5) and applicability domain assessment identified 15 priority candidates. In silico ADMET profiling revealed favorable pharmaceutical properties, with Incartine (pIC₅₀: 6.84, pEC₅₀: 6.13, QED: 0.83), Bilobalide (pIC₅₀: 6.78, pEC₅₀: 6.07, QED: 0.56), and Indican (pIC₅₀: 6.73, pEC₅₀: 6.11, QED: 0.51) exhibiting the highest predicted potencies. Conclusions: This systematic computational screening of Colombian medicinal flora demonstrates the untapped potential of regional biodiversity for anti-dengue drug discovery. The identified candidates, representing structurally novel chemotypes, are prioritized for experimental validation.

Background/Objectives: Colombia harbors exceptional plant diversity, comprising over 31,000 formally identified species, of which approximately 6,000 are classified as useful plants. Among these, 2,567 species possess documented food and medicinal applications, with several traditionally utilized for managing febrile illnesses. Despite the global burden of dengue virus infection affecting millions annually, no specific antiviral therapy has been established. This study aimed to identify potential anti-dengue compounds from Colombian medicinal flora through machine learning-based quantitative struc-ture-activity relationship (QSAR) modeling. Methods: An optimized XGBoost algorithm was implemented through Bayesian hyperparameter optimization (Optuna, 50 trials) to develop a QSAR model trained on 2,034 ChEMBL-derived activity records with experi-mentally validated anti-dengue activity (IC₅₀/EC₅₀). The model incorporated 887 molecular descriptors, comprising 43 physicochemical properties and 844 ECFP4 fingerprint bits, selected via variance-based feature selection. Bayesian hyperparameter optimization us-ing Optuna (50 trials) was performed to maximize model performance. Through system-atic literature review, 2,567 Colombian plant species were evaluated, identifying 358 with documented antiviral properties. Phytochemical analysis of 184 species generated 3,267 unique compounds for subsequent virtual screening. Compounds were prioritized based on predicted activity, drug-likeness, and applicability domain assessment for future ex-perimental validation. A dual-endpoint classification strategy was employed to simulta-neously evaluate both IC50 and EC50 activities, with compounds categorized into nine activity classes based on combined potency thresholds (Low: pActivity ≤ 5.0, Medium: 5.0 < pActivity ≤ 6.0, High: pActivity > 6.0). Results: The optimized XGBoost model achieved robust performance with a Matthews correlation coefficient of 0.583 and area under the receiver operating characteristic curve of 0.896. Virtual screening of 3,267 Colombian phytochemicals identified 276 compounds (8.4%) with high predicted potency (pActivity > 6) for both IC₅₀ and EC₅₀ endpoints (classified as "High-High"). Comprehensive struc-ture-activity relationship (SAR) analysis revealed that 239 of these compounds (86.6%) represented structurally novel chemotypes with low similarity (Tanimoto < 0.5) to the training dataset. Application of drug-likeness filters (QED ≥ 0.5) identified 20 priority can-didates (7.2% of high-potency hits), with 12 compounds showing exceptional profiles. In-cartine (pIC50: 6.84, pEC50: 6.13, QED: 0.83), Bilobalide (pIC50: 6.78, pEC50: 6.07, QED: 0.56), and Indican (pIC50: 6.73, pEC50: 6.11, QED: 0.51) exhibited the highest predicted potencies. Descriptor-activity correlation analysis identified QED (ρ = 0.14 with EC50), TPSA (ρ = -0.15), and aromatic rings as key modulators of antiviral activity. Conclusions: This pioneering systematic computational screening of Colombian flora for anti-dengue activity demonstrates the untapped potential of regional biodiversity in pharmaceutical discovery. The identified lead compounds represent prioritized candidates for experi-mental validation and subsequent development of dengue therapeutics, with all compu-tational resources made publicly available to facilitate future research.

Introducción: El uso de plantas medicinales en el tratamiento de enfermedades crónicas no transmisibles como la diabetes mellitus tipo 2, la hipertensión arterial y la dislipidemia ha venido en aumento. Según cifras de la Organización Mundial de la Salud, el 80 % de las personas ha utilizado en algún momento de su vida plantas medicinales. A pesar de la rica biodiversidad de plantas medicinales en Colombia, solo un pequeño porcentaje ha sido aprobado para uso médico y la falta de comprensión sobre la complejidad de estas plantas puede conllevar un uso irracional, toxicidad, efectos adversos o interacciones farmacológicas. Objetivo: Describir los conocimientos y saberes populares que los vendedores de plantas medicinales tienen y utilizan con respecto a las plantas medicinales para tratar el síndrome metabólico y sus patologías asociadas. Métodos: Estudio de corte transversal mediante la aplicación de una encuesta semiestructurada a comerciantes y distribuidores de plantas medicinales de las tres principales plazas de mercado de Cali, Colombia. Se realizó una identificación taxonómica de las especies vegetales más citadas, las cuales no estaban reportadas en el Vademécum colombiano de plantas medicinales –VCPM–. Además, se comparó la información disponible en el VCPM con la literatura científica extraída de diversas fuentes como ScienceDirect, PubMed y Google Scholar. Resultados: Las plantas más recomendadas por los vendedores de plantas medicinales para tratar las patologías asociadas al síndrome metabólico son el nogal, insulina, chaparro rojo, papunga, chicharrón de loma, moringa, mastranto, cáscara de mandarina, diente de león, ortiga, zarzaparrilla, cofrei y alcachofa. Los entrevistados demostraron poco conocimiento de contraindicaciones y los efectos adversos y algunas de las plantas no se encuentran listadas y/o descritas en el VCPM. Conclusión: Este estudio destaca la importancia del conocimiento y uso de plantas medicinales en el tratamiento de enfermedades crónicas no transmisibles asociadas al síndrome metabólico. Los vendedores de plantas medicinales en Cali, Colombia, ofrecen una amplia gama de opciones para abordar estas patologías, aunque también se observa una falta de comprensión sobre contraindicaciones y posibles efectos adversos. Es crucial mejorar la educación y la información disponible sobre el uso racional de plantas medicinales, especialmente aquellas no incluidas en las guías oficiales, para garantizar la seguridad y eficacia en su aplicación terapéutica.

The teaching of human anatomy in medical education faces challenges, necessitating effective alternatives for students to practically explore anatomical complexity. Porcine biomodels, with their anatomical similarities to humans, offer a promising solution. This article presents a detailed protocol for preserving porcine biomodels, addressing the need for accessible and efficient methods in comparative anatomy studies. This protocol proposes the use of a modified Chilean solution for biomodel preservation, employing formalinization techniques through repletion and immersion. Subsequently, deformalization is achieved using the modified Chilean solution without formaldehyde, followed by a glycerin softening process. Given the scarcity of literature on preservation techniques and the absence of a standardized procedure or test to evaluate tissue conservation, we suggest assessing tissue quality based on measures of resistance and elasticity. Our findings indicate a qualitatively high level of tissue preservation in our specimens. Furthermore, these biomodels are currently utilized successfully for morphology studies and in teaching human comparative anatomy to medical students.

The teaching of human anatomy in medical education faces challenges, necessitating effective alternatives for students to practically explore anatomical complexity. Porcine biomodels, with their anatomical similarities to humans, offer a promising solution. This article presents a detailed protocol for preserving porcine biomodels, addressing the need for accessible and efficient methods in comparative anatomy studies. This protocol proposes the use of a modified Chilean solution for biomodel preservation, employing formalinization techniques through repletion and immersion. Subsequently, deformalization is achieved using the modified Chilean solution without formaldehyde, followed by a glycerin softening process. Given the scarcity of literature on preservation techniques and the absence of a standardized procedure or test to evaluate tissue conservation, we suggest assessing tissue quality based on measures of resistance and elasticity. Our findings indicate a qualitatively high level of tissue preservation in our specimens. Furthermore, these biomodels are currently utilized successfully for morphology studies and in teaching human comparative anatomy to medical students.