IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS

Autores

  • SHOLA ELIJAH ADENIJI
  • Sani Uba Department of Chemistry, Ahmadu Bello University, Zaria-Nigeria
  • Adamu Uzairu Department of Chemistry, Ahmadu Bello University, Zaria-Nigeria

DOI:

https://doi.org/10.18540/jcecvl4iss2pp0246-0254

Palavras-chave:

Tuberculosis, 1, 2, 4-Triazole, QSAR, Applicability domain, Y-Randomization.

Resumo

Abstract

In silico study was carried on a dataset of 1,2,4-Triazole derivatives to investigate their activities behaviour on mycobacterium tuberculosis by utilizing Quantitative Structure-Activity Relationship (QSAR) technique. Genetic Function Algorithm (GFA) and Multiple Linear Regression Analysis (MLRA) were used to select the optimum descriptors and to generate the correlation QSAR model that relate their activities values against mycobacterium tuberculosis with the molecular structures of the inhibitors. The model was validated and was found to have squared correlation coefficient (R2) of 0.9134, adjusted squared correlation coefficient (Radj) of 0.8753 and Leave one out (LOO) cross validation coefficient (Qcv^2) value of 0.8231. The external validation set used for confirming the predictive power of the model has R2pred of 0.7482. Stability and robustness of the model obtained by the validation test indicate that the model can be used to design and synthesis other 1,2,4-Triazole derivatives with improved anti-mycobacterium tuberculosis activities

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Referências

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Publicado

2018-07-04

Como Citar

ADENIJI, S. E., Uba, S., & Uzairu, A. (2018). IN SILICO STUDY FOR INVESTIGATING AND PREDICTING THE ACTIVITIES OF 1,2,4-TRIAZOLE DERIVATIES AS POTENT ANTI-TUBERCULAR AGENTS. The Journal of Engineering and Exact Sciences, 4(2), 0246–0254. https://doi.org/10.18540/jcecvl4iss2pp0246-0254

Edição

Seção

Physical Chemistry

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