AUTHOR=Yang Jiansheng , Cheng Chunchao , Wu Zhuolin 

TITLE=Mechanisms underlying the therapeutic effects of cinobufagin in treating melanoma based on network pharmacology, single-cell RNA sequencing data, molecular docking, and molecular dynamics simulation

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 14 - 2023

YEAR=2024

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2023.1315965

DOI=10.3389/fphar.2023.1315965

ISSN=1663-9812

ABSTRACT=Malignant melanoma is one of the most aggressive cancer, if not be resected in early stage, it can metastasis rapidly. Therefore, drug therapy plays a important role in the treatment of melanoma. Cinobufagin , an active ingredient derived from Venenum Bufonis, can inhibit the growth and development of melanoma. However, the mechanism underlying its therapeutic effects is unclear. The purpose of this study was to predict the protential targets of Cinobufagin in melanoma. We gathered known and predicted targets of cinobufagin from four online databases. Subsequently, Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed. Gene expression data were downloaded from the GSE46517 dataset, and Differential gene expression analysis and Weighted gene correlation network analysis were performed to identify melanoma-related genes. Through input melanoma related genes and drug targets in STRING online database, and apply Molecular Complex Detection (MCODE) analysis, we identify key targets that may be the protential targets of cinobufagin in melanoma. Moreover, we assessed the distribution of pharmacological targets of cinobufagin in melanoma, key cluster, using single-cell data from the GSE215120 dataset obtained from the Gene Expression Omnibus database. The crucial targets of cinobufagin in melanoma were identified from the intersection of key cluster and the intersection of melanoma-related genes and drug targets. The receiver operating characteristic curve(ROC) analysis, survival analysis, molecular docking and molecular dynamics simulation were performed to gain further insights. Our findings suggest that Cinobufagin may affect melanoma by arresting cell cycle through the inhibition of three protein tyrosine/serine kinase (EGFR, ERBB2, CDK2). However, our conclusions are not supported by relevant experimental data and need to be further studied in the future.