Targeting Colorectal Cancer through Multi-Protein Modeling: A Computational Drug Discovery Approach

Colorectal cancer (CRC) is one of the most prevalent cancers globally and remains the third leading cause of cancer-related mortality, underscoring the urgent need for novel therapeutic strategies. In this study, the potential of anticancer peptides (ACPs) as ligands for key proteins in the KEGG colorectal cancer pathway was explored using a computational drug discovery approach. ACPs are short peptides designed to selectively target and kill cancer cells, offering a promising strategy with minimal toxicity to normal cells.The research utilized a computer-aided drug design (CADD) framework, which included virtual screening, molecular docking, and molecular dynamics (MD) simulations, to assess the binding interactions between ACPs and colorectal cancer-associated proteins. Virtual screening was performed to identify promising ACP candidates, followed by molecular docking to predict the binding affinity and specificity of peptide-target interactions. Additionally, MD simulations were conducted to evaluate the stability and dynamic behavior of the peptide-protein complexes over time.Although no experimental validation was carried out, the computational analysis suggests that certain ACPs exhibit strong binding affinity to key targets within the CRC signaling pathways. The results provide valuable insights into the potential of ACPs as multi-target inhibitors and lay the groundwork for further experimental studies. This computational approach offers a promising strategy to accelerate the development of novel, targeted therapeutics for colorectal cancer.