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

• N. Wasim

  Department of Microbiology, College of Education for Pure Science, Basrah University, Iraq ,RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• R.A. Talha

  RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• V.V. Luga

  Department of Pharmaceutical Technology, Faculty of pharmacy, University of Medical Sciences and Technology,RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom Khartoum, Sudan ,

  Author

• EL.G. Hamed

  Faculty of Science, Department of Biotechnology, Mansoura University, Mansoura, Egypt, RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• M. Ramdan

  National Center for Clinic and Environmental Toxicology (NCCET), Cairo University, Egypt , RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• S.A. Elhosany

  Department of Biotechnology, Faculty of Agriculture, Cairo University, Cairo, Egypt , RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• A. Attallah

  RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• A. Helmy

  RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• Nour El-Houda A. Reyad

  9 Plant Pathology Department, Faculty of Agriculture, Cairo University, Giza, Egypt , RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

• Israa M Shamkh

  Chief Computational Chemistry Department EBO Bio Solution Company, London, EC1V2NX, United Kingdom

  Author

• Shrouq Rashad

  Department of Agricultural Microbiology, Faculty of Agriculture, Cairo University, Giza, Egypt, RM-G1002 Lab, Department Of Cheminformatics, EBO Bio Solution, London United Kingdom

  Author

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.

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• Computational Science Section

Copyright (c) 2025 N. Wasim, R.A. Talha, V.V. Luga, EL.G. Hamed, M. Ramdan, S.A. Elhosany, A. Attallah, A. Helmy, Nour El-Houda A. Reyad , Israa M Shamkh, Shrouq Rashad (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.

This work is licensed under a Creative Commons Attribution 4.0 International License.