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DOI 10.1021/acs.jcim.6c01372

Медицинская библиотека · Journal of chemical information and modeling · 2026

Identification of Noncovalent Small-Molecules from Virtual Screening Toward the Development of Potential KRAS Inhibitors.

Addis Amanuel G, Jakubec Jacob, Sanchez John, Pagba Cynthia V, Sianoya Abraham C, Gorfe Alemayehu A

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Аннотация

Kirsten rat sarcoma (KRAS) is an oncoprotein responsible for ∼ 20% of all human cancers. So far, only two covalent drugs are approved by the U.S. Food and Drug Administration (FDA) for the treatment of KRAS (G12C)-driven non-small cell lung cancer. However, their reliance on a covalent bond with cysteine at position 12 limits their effectiveness for treating other cancers driven by non-G12C KRAS mutations, and the emergence of resistance against allele-specific inhibitors means that considerable effort is being directed toward developing noncovalent KRAS inhibitors. Currently, multiple noncovalent inhibitors are in various stages of clinical trials. While some of these may eventually come to fruition, none has so far been approved for market use, underscoring the need for new inhibitors. Here, we report a set of small molecules obtained from virtual screening of a physiochemically tailored ligand library against multiple KRAS mutants. Initial binding and cell proliferation experiments show that some of the predicted hits exhibit high affinity (single digit nM) binding to KRAS and sub-to-low micromolar inhibitory activity in pancreatic cancer cell lines harboring G12D, G12V, or G12C KRAS mutations. Predicted to bind to the p2 (also called switch II) pocket of KRAS, these ligands harbor unique scaffolds compared to existing drugs or leads and may serve as useful starting points for the development of allele-specific or pan-KRAS inhibitors.

Для цитирования: Addis Amanuel G, Jakubec Jacob, Sanchez John, Pagba Cynthia V, Sianoya Abraham C, Gorfe Alemayehu A. Identification of Noncovalent Small-Molecules from Virtual Screening Toward the Development of Potential KRAS Inhibitors.. Journal of chemical information and modeling. 2026. DOI: 10.1021/acs.jcim.6c01372.

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