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Combinatorial Chemistry & High Throughput Screening

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ISSN (Print): 1386-2073
ISSN (Online): 1875-5402

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Research Article

Lignans and Neolignans Anti-tuberculosis Identified by QSAR and Molecular Modeling

Author(s): Mayara S. Maia, Natália F. de Sousa, Gabriela C.S. Rodrigues, Alex F.M. Monteiro, Marcus T. Scotti and Luciana Scotti*

Volume 23, Issue 6, 2020

Page: [504 - 516] Pages: 13

DOI: 10.2174/1386207323666200226094940

Price: $65

Abstract

Background: Tuberculosis is a disease with high incidence and high mortality rate, especially in Brazil. Although there are several medications available for treatment, in cases of resistance, there is a need to use more than one medication.

Objective: Therefore, cases of toxicity increase and reports of resistance have been worrying the population. In addition, some medications have a short period of effectiveness. To achieve the goal, ligand-based and structure-based approaches were used.

Methods: Thus, in an attempt to discover potent inhibitors against Mycobacterium tuberculosis enzymes, we sought to identify natural products with high therapeutic potential for the treatment of Tuberculosis through QSAR, Molecular Modeling and ADMET studies.

Results: The results showed that the models generated from two sets of molecules with known activity against M. tuberculosis enzymes InhA and PS were able to select 11 and 8 compounds, respectively, between Lignans and Neolignans with 50 to 60% activity probability. In addition, molecular docking contributed to confirm the mechanism of action of compounds and increase the accuracy of methodologies. All molecules showed higher binding energy values for the drug Isoniazid. We conclude that compounds 33, 34, 110, 114 and 133 are promising for InhA target and compounds 07, 08, 19, 21, 42, 48, 75 and 141 for target PS. In addition, most molecules did not show any toxicity according to the evaluated parameters.

Conclusion: Therefore, Lignans and Neolignans may be an alternative for the treatment of Tuberculosis.

Keywords: Lignans, neolignans, QSAR, molecular modeling, tuberculosis, molecular docking.

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