Using bioinformatic technique to discovery Huangqin and Lianqiao combination as a potential new drus for treatment acne

Abstract

Acne is the most common chronic inflammatory skin disease in adolescents and young adults. Many Chinese herbal medicines (CHMs) have been used in the treatment of acne and were proved to be effective and safe. There is growing need to investigate which CHMs are the most frequently prescribed herbs used to treatment acne and what were the molecular mechanisms of therapeutic effects of these CHMs. So the most frequently prescribed CHMs were mined out by a novel text mining method based on a comprehensive collection of 2,136 records of literatures in SinoMed database. The target proteins of these CHMs were retrieved from PubChem database and the genes of acne were searched in Gene database. Ingenuity pathways analysis (IPA) online platform was used for the analysis of the target proteins and the genes. The molecular mechanisms of these CHMs treating acne could be deciphered by building and comparing the related networks and canonical pathways. Results showed that scutellaria baicalensis (Huangqin) and fructus forsythiae (Lianqiao) are the most frequently prescribed CHMs for treatment acne. The network analysis indicated that the associated network functions related with both acne and two CHMs were involved in dermatological diseases, infectious disease and inflammatory disease. The canonical pathway comparison showed that the molecular mechanisms of therapeutic effects of two CHMs were focused on apoptosis signaling and p70s6k signaling. In conclusion, Huangqin and Lianqiao combination might be regarded as a potential new drug for treatment acne and the molecular mechanisms of therapeutic effects could be at least partly due to regulating apoptosis signaling and p70s6k signaling. Integrative text mining and bioinformatics analysis is a promising method to find new drug and decipher their molecular mechanism intuitively.