Docking-Based Virtual Screening Method for Selecting Natural Compounds with Synergistic Inhibitory Effects Against Cancer Signalling Pathways Using a Multi-Target Approach

This study aims to introduce a methodology for identifying medicinal plants that contain effective natural compounds with the most possible synergistic effects to inhibit cancer survival and proliferation in a multi-targeted manner.

To select targets, the signaling pathways involved in cancer development were defined from the KEGG database, and the protein-protein interactions (PPIs) of genes within these pathways were investigated using the STRING software. Then 14 proteins with the highest degree were identified as targets. Using the NPASS database, natural compounds were initially filtered based on their IC₅₀ against 50 cancer cell lines. Finally, a total of 1,107 natural compounds were docked to the 14 selected targets involved in cancer and 5 targets involved in general drug side effects.

The targets with the highest protein interactions, as identified by PPI analysis on cancer signaling pathways, were selected as hub proteins. Natural compounds with IC₅₀ less than 20000 nM against cancer cell lines were then docked to these selected targets using the NPASS database. Natural compounds with low binding energy to the selected targets were identified as potential synergistic inhibitors of cancer progression if used together. Additionally, plants reported with the widest range of identified natural compounds were introduced as potential sources of synergistic effects against cancer development.

We have proposed a methodology for pre-screening the natural compounds database to identify potential compounds with a high likelihood of producing a synergistic response against multiple molecular mechanisms in cancer. However, further validation methods are necessary to confirm their effectiveness.