Computer-aided ligand identification of capsaicinoids and their potential functions in metabolic diseases
Ana Alondra Sobrevilla-Navarro1,2, Omar Ramos-Lopez1, Bertha Landeros-Sánchez3
1Facultad de Medicina y Psicología, Universidad Autónoma de Baja California, 22390, Tijuana, México.
Abstract:
Obesity, diabetes, and cardiovascular diseases are major health concerns worldwide. In recent times, research has focused on identifying food-derived molecules and their relationship with metabolic diseases. A study was conducted to establish a process for characterizing the biological targets of capsaicinoids found in chili peppers. Capsaicinoids are a group of compounds including Capsaicin, Dihydrocapsaicin, Nordihydrocapsaicin, Homodihydrocapsaicin, Homocapsaicin, and Nonivamide. The study aimed to use bioinformatics tools to analyze these compounds and their effect on metabolic targets. To achieve this, a search was conducted for SMILES sequences of chili pepper capsaicinoids. The 2D and 3D similarity analyses were performed with compounds known to be experimentally active on their protein targets. These ligands were then analyzed, and predictions were made about enriched biological terms and bio-pathways. A protein-protein interaction analysis was performed on metabolic targets. Additionally, pharmacokinetics and CYP450 interaction prediction were analyzed using capsaicinoids. The molecular activity of the identified ligands for the six capsaicinoids were classified as G-protein-coupled receptors, proteases, membrane receptors, oxidoreductases, erasers, electrochemical transporters, cytochrome P450s, and hydrolases. There are several signaling pathways modulated by capsaicinoids, including insulin signaling, insulin resistance, AGE-RAGE signaling in diabetic complications, endocrine resistance, lipid metabolism, and atherosclerosis. The study found that capsaicin interacts more strongly with pathways that are important in metabolic diseases, such as obesity, cancer, diabetes mellitus, and their complications. These findings could be useful in developing strategies to mitigate the impact of metabolic diseases.
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