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DFT-based reactivity and combined QSAR, molecular docking of 1,2,4,5-Tetrazine derivatives as inhibitors of Pim-1 kinase
In the present work we have calculated several DFT reactivity descriptors for 1,2,4,5-Tetrazine at the B3LYP/6–311++G(d,p) level of theory in order to analyze its reactivity in vacuum and solvent phases. Whereas, the influence of the solvent was taken into account employing the PCM model. DFT-based...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6819827/ https://www.ncbi.nlm.nih.gov/pubmed/31687555 http://dx.doi.org/10.1016/j.heliyon.2019.e02451 |
Sumario: | In the present work we have calculated several DFT reactivity descriptors for 1,2,4,5-Tetrazine at the B3LYP/6–311++G(d,p) level of theory in order to analyze its reactivity in vacuum and solvent phases. Whereas, the influence of the solvent was taken into account employing the PCM model. DFT-based descriptors such as (electronic chemical potential, electrophilicity, condensed Fukui function….) have been determined to predict the reactivity of 1,2,4,5-Tetrazine. A series of eighteen 1,2,4,5-Tetrazine derivatives was studied by using two computational techniques, namely, quantitative structure activity relationship (QSAR) and molecular docking. QSAR models of the antitumor activity of some 1,2,4,5-Tetrazine derivatives were established in gas and solvent phases which exhibited good statistical values for both cases. Whereas, multiple linear regression (MLR) procedure was used to obtain the best QSAR models and the leave-one-out (LOO) method to estimate the predictivity of our models. The most and the least active compounds were docked with the protein (3C4E) to confirm those obtained results from QSAR models and elucidate the binding mode between this type of compounds and corresponding protein. |
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