A systems approach to pigmentation control by ascorbic acid esterified with coconut oil-derived medium-chain fatty acids: Investigated via network pharmacology, molecular dynamics, elastic network and Markov state models
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引用次数: 0
Abstract
Tyrosinase family enzymes (TYR, TRP1, TRP2) play pivotal roles in melanogenesis, making them targets for pigmentation modulation. Ascorbic acid (ASC) and coconut oil have shown promise in skin whitening. Inspired by these ASC esterified with coconut oil-derived medium-chain fatty acids (MCFAs) such as capric acid (ASC-CAP), caproic acid (ASC-CAPRO), caprylic acid (ASC-CAPRY) and lauric acid (ASC-LAU) are investigated via in silico analysis such as network pharmacology (NP), molecular docking and molecular dynamics (MD) simulation to understand their interaction with tyrosinase family enzymes. This study introduces a novel approach to skin depigmentation by examining the combined effects of ascorbic acid and coconut oil derivatives on the regulation of tyrosinase family enzymes involved in melanogenesis. NP analysis identified a key hub of enzymes-LRRC8A (cell regulation), MITF (melanogenesis), and CD8A (immune signalling)-emphasizing MITF's central role in activating tyrosinase-mediated pathways. Toxicity predictions revealed minimal risk with low LD50 values of the compounds studied. MD simulations showed strong ligand stability at enzyme active sites, supported by RMSD, RMSF, DCCM, RTA, ENM, PCA, FEL, MSM and MM-GBSA binding free energy analyses. Energy landscape analyses identified metastable low-energy states, identifying stable ligand-enzyme interactions. These findings highlight the potential of ASC esterified with MCFAs as safe, and effective agents for pigmentation regulation. The present study reveals that ASC-CAPRO for TRP1 and TRP2; and ASC-LAU for TYR are the most promising candidates, offering insights into therapeutic approaches for hyperpigmentation treatment.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
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