Affiliations 

  • 1 Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan
  • 2 Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Shaqra University, Al- Quwayiyah, Riyadh, Saudi Arabia
  • 3 Chemistry Department, College of Science, King Khalid University, Abha, 61421, Saudi Arabia
  • 4 Division of Pharmacology, School of Medical and Life Sciences, Sunway University No. 5, Jalan Universiti, Bandar Sunway, Selangor Darul Ehsan, 47500, Malaysia
  • 5 Health Research Center, Jazan University, 114, Jazan, 45142, Saudi Arabia
  • 6 Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, Pakistan. awadood@awkum.edu.pk
Cancer Chemother Pharmacol, 2025 Apr 07;95(1):52.
PMID: 40195161 DOI: 10.1007/s00280-025-04767-8

Abstract

KRAS was (Kirsten rat sarcoma viral oncogene homolog) revealed as an important target in current therapeutic cancer research because alteration of RAS (rat sarcoma viral oncogene homolog) protein has a critical role in malignant modification, tumor angiogenesis, and metastasis. For cancer treatment, designing competitive inhibitors for this attractive target was difficult. Nevertheless, computational investigations of the protein's dynamic behavior displayed the existence of temporary pockets that could be used to design allosteric inhibitors. The last decade witnessed intensive efforts to discover KRAS inhibitors. In 2021, the first KRAS G12C covalent inhibitor, AMG 510, received FDA (Food and drug administration) approval as an anticancer medication that paved the path for future treatment strategies against this target. Computer-aided drug designing discovery has long been used in drug development research targeting different KRAS mutants. In this review, the major breakthroughs in computational methods adapted to discover novel compounds for different mutations have been discussed. Undoubtedly, virtual screening and molecular dynamic (MD) simulation and molecular docking are the most considered approach, producing hits that can be employed in subsequent refinements. After comprehensive analysis, Afatinib and Quercetin were computationally identified as hits in different publications. Several authors conducted covalent docking studies with acryl amide warheads groups containing inhibitors. Future studies are needed to demonstrate their true potential. In-depth studies focusing on various allosteric pockets demonstrate that the switch I/II pocket is a suitable site for drug designing. In addition, machine learning and deep learning based approaches provide new insights for developing anti-KRAS drugs. We believe that this review provides extensive information to researchers globally and encourages further development in this particular area of research.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.