Estudio de la actividad bactericida de los ácidos húmicos extraídos del carbón - una revisión computacional.

Abstract

This work presents a literature review on the application of technological tools in the identification and classification of humic acids (HA), with a particular focus on their potential medicinal use. The study highlights computational molecular dynamics as an advanced tool successfully applied to analyze the molecular complexity and chemical structure of HA at the molecular scale. The study covers various application areas of humic acids, emphasizing their relevance in medicine. Despite the interest in developing drugs from HA, the limited amount of research in this area is acknowledged, though the potential of these compounds as functional agents in the prevention and treatment of various diseases is noted. The review identifies computational simulators, such as molecular dynamics (MD) simulations, which allow for the presentation of the structure and properties of HA related to drug development. These computational models facilitate the estimation of the macroscopic properties of humic substances and their contrast with chemical composition. Additionally, artificial neural network models have been developed, trained on infrared and visible spectra, to estimate the biological activity of HA. Regarding the action pathways of HA on bacterial inhibition, molecular dynamics simulations have provided valuable insights into the molecular structure and properties of humic substances at the atomic scale. This is crucial for understanding the mechanisms of interaction between HA and bacteria, suggesting that their antimicrobial activity may be related to the chemical structure and functional groups present. The study also explores the importance of molecular dynamics as an essential tool in research, allowing the study of a system's evolution over time. In the field of drug discovery, the crucial role of molecular docking is highlighted, facilitating the exploration and prediction of interactions between candidate molecules and their biological targets. Specific studies employing molecular dynamics simulations and humic substance models to explore macroscopic properties and estimate the biological activity of peat-derived HA through artificial neural networks are mentioned. In the final discussion, it is acknowledged that despite advances in computational simulations, challenges remain, especially the need for more sophisticated models and greater computational capacity. Additionally, the importance of experimental validation is emphasized to ensure the accuracy of simulated results.