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Identification of potential oral cancer drugs as Bcl-2 inhibitors from known anti-neoplastic agents through docking studies

Raychaudhury, C and Srinivasan, S and Pal, D (2023) Identification of potential oral cancer drugs as Bcl-2 inhibitors from known anti-neoplastic agents through docking studies. In: Journal of Mathematical Chemistry .

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Official URL: https://doi.org/10.1007/s10910-023-01537-w


Oral Cancer is one of the major killers in India and of global concern. An attempt has been made here to identify small molecule inhibitors of Bcl-2 (B-cell lymphoma 2) protein through docking studies in search of new oral cancer drugs from a curated set of 276 known anti-neoplastic agents obtained from PubChem. The Bcl-2 protein (PDB id:6QGH), being complexed with ligand ABT-263, has been detached from the complex. The ligand-free protein and 276 compounds have been prepared for docking studies using corresponding tools available in Discovery Studio (DS), ver.4.1. The 276 compounds have been docked on the first site of the protein using LibDock docking program available in DS. By considering Methotrexate as the reference compound (LibDock score: 114.76), we have identified 25 compounds as the most potential oral cancer drugs having LibDock scores greater than 100. Another set of 114 compounds with LibDock scores between 80 and 100 have also been identified as the next set of potential drug candidates and some of them show anti-apoptosis properties. Two other compounds with LibDock scores below 80 have been identified for comparative analyses with some high-scoring compounds. The docking results have been given in tables and pictures (screenshots) of the docked poses of selected compounds have been shown to illustrate the findings. Finally, the most suitable potential compounds have been identified by applying Lipinski�s Rule of 5. The present approach using known anti-neoplastic agents is believed to help discover potential anti-oral cancer drug candidates. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

Item Type: Journal Article
Publication: Journal of Mathematical Chemistry
Publisher: Springer Science and Business Media Deutschland GmbH
Additional Information: The copyright for this article belongs to Springer Science and Business Media Deutschland GmbH.
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 04 Mar 2024 09:23
Last Modified: 04 Mar 2024 09:23
URI: https://eprints.iisc.ac.in/id/eprint/84330

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