Network pharmacology identifies AMG-900 as a multi-targeted anticancer candidate for breast, ovarian, and colorectal cancers

Cancer remains a significant global health challenge, characterized by complex genetic and molecular mechanisms that often converge across different tissue types. While traditional approaches focused on specific drivers for individual cancer types, there's a growing need for therapies that can target common molecular patterns across multiple cancers simultaneously. This shift towards multi-targeted therapeutics aims to overcome resistance and improve efficacy by addressing shared oncogenic pathways. Understanding these common mechanisms, such as dysregulated cell cycle progression and proliferation, is crucial for developing broad-spectrum agents.

Researchers conducted a multi-omics and network pharmacology analysis to identify common oncogenic pathways and potential multi-targeted drug molecules for breast, ovarian, and colorectal (BOC) cancers. They analyzed three transcriptomic datasets to identify common differentially expressed genes (DEGs), totaling 128 genes. A protein-protein interaction (PPI) network study was performed to pinpoint top-ranked hub targets. Enrichment analysis using GO and KEGG pathways, alongside regulatory network (TFs and mRNAs) analysis, elucidated common pathogenetic processes. Finally, molecular docking was used to assess the binding affinity of AMG-900 to the identified targets, followed by large-scale (500 ns) molecular dynamics and MM-GBSA analyses to validate protein-ligand complex stability. Pharmacokinetic analysis was also conducted.

The multi-omics analysis successfully identified 128 common differentially expressed genes (DEGs) across breast, ovarian, and colorectal cancers. From the protein-protein interaction (PPI) network, AURKA, CDK1, and CCNB1 were revealed as the top-ranked, most significant hub targets, indicating their central role in the common oncogenic pathways of these cancers. Enrichment analysis further confirmed common pathogenetic processes, including cell cycle regulation and proliferation pathways. Molecular docking studies demonstrated that AMG-900 exhibited high binding affinity scores:

-10.8 kcal/mol with AURKA, -9.40 kcal/mol with CCNB1, and -9.7 kcal/mol with CDK1. Large-scale molecular dynamics and MM-GBSA analyses validated the stability and structural flexibility of these protein-ligand complexes, showing stable interactions for AURKA and CCNB1, while CDK1 displayed comparatively reduced stability. Furthermore, pharmacokinetic analysis indicated favorable drug-likeness and a manageable toxicity profile, typical of anticancer agents.