Marrero Ponce, Yovani
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Marrero Ponce, Yovani
Official Name
Marrero Ponce, Yovani
Alternative Name
ymarrero
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Scopus Author ID
55665599200
Researcher ID
H-5724-2011

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Biological Implications of the Intrinsic Deformability of Human Acetylcholinesterase Induced by Diverse Compounds: A Computational Study

2024 , Ysaías J. Alvarado , Lenin González-Paz , José L. Paz , Marcos A. Loroño-González , Julio Santiago Contreras , Carla Lossada , Alejandro Vivas , Marrero Ponce, Yovani , Felix Martinez-Rios , Patricia Rodriguez-Lugo , Yanpiero Balladores , Joan Vera-Villalobos

The enzyme acetylcholinesterase (AChE) plays a crucial role in the termination of nerve impulses by hydrolyzing the neurotransmitter acetylcholine (ACh). The inhibition of AChE has emerged as a promising therapeutic approach for the management of neurological disorders such as Lewy body dementia and Alzheimer’s disease. The potential of various compounds as AChE inhibitors was investigated. In this study, we evaluated the impact of natural compounds of interest on the intrinsic deformability of human AChE using computational biophysical analysis. Our approach incorporates classical dynamics, elastic networks (ENM and NMA), statistical potentials (CUPSAT and SWOTein), energy frustration (Frustratometer), and volumetric cavity analyses (MOLE and PockDrug). The results revealed that cyanidin induced significant changes in the flexibility and rigidity of AChE, especially in the distribution and volume of internal cavities, compared to model inhibitors such as TZ2PA6, and through a distinct biophysical-molecular mechanism from the other inhibitors considered. These findings suggest that cyanidin could offer potential mechanistic pathways for future research and applications in the development of new treatments for neurodegenerative diseases.

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Molecular Modeling of Vasodilatory Activity: Unveiling Novel Candidates Through Density Functional Theory, QSAR, and Molecular Dynamics

2024 , Anthony Bernal , Edgar A. Márquez , Máryury Flores-Sumoza , Sebastián A. Cuesta , José Ramón Mora , José L. Paz , Adel Mendoza-Mendoza , Juan Rodríguez-Macías , Franklin Salazar , Daniel Insuasty , Marrero Ponce, Yovani , Guillermin Agüero-Chapin , Virginia Flores-Morales , Domingo César Carrascal-Hernández

Cardiovascular diseases (CVD) pose a significant global health challenge, requiring innovative therapeutic strategies. Vasodilators, which are central to vasodilation and blood pressure reduction, play a crucial role in cardiovascular treatment. This study integrates quantitative structure– (QSAR) modeling and molecular dynamics (MD) simulations to predict the biological activity and interactions of vasodilatory compounds with the aim to repurpose drugs already known and estimateing their potential use as vasodilators. By exploring molecular descriptors, such as electronegativity, softness, and highest occupied molecular orbital (HOMO) energy, this study identifies key structural features influencing vasodilatory effects, as it seems molecules with the same mechanism of actions present similar frontier orbitals pattern. The QSAR model was built using fifty-four Food Drugs Administration-approved (FDA-approved) compounds used in cardiovascular treatment and their activities in rat thoracic aortic rings; several molecular descriptors, such as electronic, thermodynamics, and topographic were used. The best QSAR model was validated through robust training and test dataset split, demonstrating high predictive accuracy in drug design. The validated model was applied on the FDA dataset and molecules in the application domain with high predicted activity were retrieved and filtered. Thirty molecules with the best-predicted pKI50 were further analyzed employing molecular orbital frontiers and classified as angiotensin-I or β1-adrenergic inhibitors; then, the best scoring values obtained from molecular docking were used to perform a molecular dynamics simulation, providing insight into the dynamic interactions between vasodilatory compounds and their targets, elucidating the strength and stability of these interactions over time. According to the binding energies results, this study identifies novel vasodilatory candidates where Dasabuvir and Sertindole seem to have potent and selective activity, offering promising avenues for the development of next-generation cardiovascular therapies. Finally, this research bridges computational modelling with experimental validation, providing valuable insight for the design of optimized vasodilatory agents to address critical unmet needs in cardiovascular medicine.

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