Exploring traditional Chinese medicine as a potential treatment for sarcopenia: A network pharmacology and data mining analysis of drug selection and efficacy.

Sarcopenia, as an increasingly pressing clinical issue, can be ameliorated through employment of traditional Chinese medicines. However, the current lack of specific pharmacological interventions for Sarcopenia necessitates further exploration of novel possibilities in traditional Chinese medicine for the treatment of this condition, utilizing advanced methodologies such as web pharmacology and data mining. Screening the essential targets of Sarcopenia, conducting matching between target and active molecules, as well as active molecules and herbs. Employing data mining techniques to analyze the screening outcomes, and molecular docking to compare the binding activities of active molecules with target proteins. The approach of using herbs for the treatment of Sarcopenia involves 13 targets, with 414 active compounds and 367 types of herbs. Data mining reveals that the herbs used in treating Sarcopenia are primarily characterized by their bitter taste, exerting their effects through dispelling dampness and promoting blood circulation. Moreover, 2 new formulas are postulated. Furthermore, molecular docking analysis indicates that the main active components of the herbs can be observed to tightly bind with the targets. Through network pharmacology and molecular docking, our findings reveal that herbs contain 15 key active components and 5 key targets, which correspond to 7 major herbs and 2 new formulas. Academically, these findings hold significant reference value for the development of novel drugs targeting Sarcopenia.