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QSAR, molecular docking, and molecular dynamics simulation–based design of novel anti-cancer drugs targeting thioredoxin reductase enzyme

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Abstract

Thioredoxin reductase (TrxR) plays an important role in the reduction of thioredoxin (Trx), which is found to be involved in the upregulation of a diversity of tumors, including those related to chemo-resistant tumors. In recent years, thioredoxin reductase (TrxR) has been identified as a very important regulator of tumor development, and therefore, targeting TrxR is a promising strategy for cancer therapy. The 3/2D-QSAR models were established in this study, such as HQSAR, and the study was based on CoMFA and CoMSIA analyses. The established optimal 2D-QSAR (HQSAR) model gave Q2 = 0.756, R2 = 0.959, and = 0.90, the established optimal CoMFA model gave Q2 = 0.671, R2 = 0.925, and = 0.853, and the CoMSIA/SEA model gave Q2 = 0.627, R2 = 0.962, and = 0.927. The predictive ability of the three proposed models was successfully evaluated using the criteria validation method of Golbraikh et al. [1] and Kunal Roy [2]. The visualization of the CoMFA contour map, the CoMSIA/SEA contour map, the HQSAR contribution map analysis, and the molecular docking results revealed that the R3 surrogate is important in enhancing or decreasing anti-cancer biological activity. Molecular dynamics (MD) simulation results revealed that both inhibitors remained stable in the active sites of the 3EAO protein for 100 ns. To propose new molecules based on a change in the R3 substituent, the three proposed models predicted the TrxR inhibitory activities of the four proposed new molecules, which were then evaluated using Lipinski’s rule, synthetic accessibility, and ADMET properties of each molecule. The obtained results have revealed that the compound C3 will be of great value as a new anti-cancer drug candidate.

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Authors and Affiliations

  1. LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Mohammed Er-rajy, Mohamed El Fadili, Sara Zarougui & Menana Elhallaoui

  2. Chitkara College of Pharmacy, Chitkara University, Rajpura-140401, Punjab, India

    Somdutt Mujwar

  3. Department of Chemistry, Faculty of Science, University Ibn Zohr, Agadir, Morocco

    Fatima Zohra Lenda

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  1. Mohammed Er-rajy
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Mohammed Er-rajy: data curation, formal analysis, methodology, resources, software, writing — original draft, writing — review editing. Mohamed el Fadili: investigation and methodology. Somdutt Mujwar: MD simulation, docking analysis, manuscript review, and editing. Fatima Zohra Lenda: conceptualization, supervision, writing — review and editing. Sara Zarougui: supervision and visualization. Menana Elhallaoui: conceptualization, methodology, project administration, supervision, validation, visualization, writing — review and editing.

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Er-rajy, M., Fadili, M.E., Mujwar, S. et al. QSAR, molecular docking, and molecular dynamics simulation–based design of novel anti-cancer drugs targeting thioredoxin reductase enzyme. Struct Chem 34, 1527–1543 (2023). https://doi.org/10.1007/s11224-022-02111-x

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