Breast Cancer Therapy: Network Pharmacology of Several New Dithiocarbamate Complexes to Reveal Significant Target Proteins

Abstract

PURPOSE: This study aims to identify key molecular targets and pathways of newly designed metal-dithiocarbamate peptide complexes in breast cancer using a network pharmacology approach, addressing the limited understanding of their systems-level mechanisms of action. METHODS: Fifteen essential metal dithiocarbamate complexes were evaluated using ADMET profiling and network pharmacology analysis. Potential protein targets were predicted using the SwissTargetPrediction and SuperPred databases, followed by protein-protein interaction (PPI) analysis via STRING and topological analysis using Cytoscape. RESULTS: A total of 502 potential targets were identified, of which 21 hub proteins were extracted through network clustering. Topological analysis revealed CDK1, CCNA2, CCNB1, and CCNB2 as key hub genes with the highest degree (≥20), betweenness, and closeness centrality values. KEGG enrichment analysis indicated that these targets were primarily involved in cell cycle regulation, cellular senescence, and p53 signaling pathway. CONCLUSION: This study provides a system-level perspective on the potential anticancer mechanisms of metal-dithiocarbamate complexes in breast cancer. Although the findings are predictive and computational, they highlight promising molecular targets that warrant further experimental validation.

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