Benzothiazole derivatives as p53-MDM2 inhibitors: in-silico design, ADMET predictions, molecular docking, MM-GBSA Assay, MD simulations studies

Shridhar Deshpande, N.Naik, S.Udayakumar, U.Ghate, S.D.Dixit, S.R.Awasthi, A.Revanasiddappa, B.C.2026-02-032025Journal of Biomolecular Structure and Dynamics, 2025, 43, 6, pp. 2993-30047391102https://doi.org/10.1080/07391102.2023.2294836https://idr.nitk.ac.in/handle/123456789/20557Breast cancer stands as the most prevalent malignancy among the female populace. One of the pivotal domains in the therapeutic landscape of breast cancer revolves around the precise targeting of the p53-MDM2 inhibitory pathway. The advent of p53-MDM2 inhibition in the context of developing treatments for breast cancer marks a significant stride. In the quest for enhancing the efficacy of p53-MDM2 inhibition against breast cancer, a new series of benzothiazole compounds (B1-B30) was designed through in-silico methodologies in the present work. Using Schrodinger Maestro, the compounds underwent molecular docking assessments against the p53-MDM2 target (PDB: 4OGT). Compared to reference compounds, B25 and B12 exhibited notably elevated glide scores. Extensive in-silico studies, including ADMET and toxicity evaluations, were performed to predict pharmacokinetics, drug likeness, and toxicity. All compounds adhered to Lipinski criteria, signifying favorable oral drug properties. The MM-GBSA analysis indicated consistent binding free energies. Molecular dynamics simulations for B25 over 200 ns assessed complex stability and interactions. In summary, these compounds exhibit potential for future cancer therapy medication development. © 2023 Informa UK Limited, trading as Taylor & Francis Group.benzothiazole derivativemouse double minute 2 homologprotein p53antineoplastic agentMDM2 protein, humanprotein bindingArticlebreast cancercancer therapycomputer modelcytotoxicityfemalehumanhydrogen bondhydrophobicitymolecular dockingmolecular dynamicsmolecular mechanics-generalized born surface area assaymolecular weightpredictionprotein expressionprotein structureprotocolroot mean squared errortoxicitytoxicity testingbinding sitechemistrydrug designmetabolismstructure activity relationAntineoplastic AgentsBenzothiazolesBinding SitesDrug DesignFemaleHumansMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingProto-Oncogene Proteins c-mdm2Structure-Activity RelationshipTumor Suppressor Protein p53Benzothiazole derivatives as p53-MDM2 inhibitors: in-silico design, ADMET predictions, molecular docking, MM-GBSA Assay, MD simulations studies