Molecular Simulation-Based Insights into the Pharmacological Role of Silk Fibroin in Peripheral Nerve Repair

作者
Nasser Alotaiq,Samir Chtita,Doni Dermawan
出处
期刊:ACS Chemical Neuroscience [American Chemical Society]
卷期号:16 (20): 3993-4010
标识
DOI:10.1021/acschemneuro.5c00375
摘要

Peripheral nerve injury (PNI) remains a significant clinical challenge, often leading to impaired nerve regeneration and chronic neuropathic pain. Can Si (Silk Fibroin), a key component of traditional Chinese medicine (TCM), has long been recognized for its regenerative properties, yet its molecular mechanisms in PNI treatment remain unexplored. To elucidate the pharmacological actions of Silk Fibroin, an integrative molecular simulation approach was applied. Network pharmacology was employed to identify the most favorable target receptor for PNI, leading to the selection of the glucocorticoid receptor (GR) due to its critical role in inflammation and nerve repair. Molecular docking simulations evaluated the binding affinities of chemical and protein-based compounds from Silk Fibroin to GR, followed by molecular dynamics (MD) simulations to confirm the stability of these interactions under physiological conditions. Pharmacophore modeling identified key structural features essential for bioactivity, while in silico toxicity assessments evaluated the safety profiles of the compounds. Key bioactive compounds from Silk Fibroin, including Catechin, Hesperetin, and Menaquinone-7, demonstrated strong interactions with GR, with MM/PBSA-based binding free energy values of -35.98 -33.65, and -32.13 kcal/mol, respectively. Protein-based compounds, such as Bombyxin A-5 (-228.06 kcal/mol) and small ribosomal subunit protein uS11 (-204.98 kcal/mol), also displayed promising binding affinities, suggesting potential neuroprotective roles. In silico toxicity assessments revealed favorable safety profiles for most of the compounds. This study highlights Silk Fibroin as a promising source of therapeutic agents for PNI. Future studies should focus on the experimental validation of these computational findings through in vitro and in vivo models.
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