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A Combined Approach for Predicting Binding Affinity of Zika Virus NS2B-NS3 Protease Inhibitors Using Semi-Empirical Methods and Molecular Docking Algorithms

de Oliveira, Maycon Vinicius ; Almeida, Leonardo ; da Rocha, João ; Wanzeller, Ana Lucia ; Lima, Anderson

Journal of the Brazilian Chemical Society, 2024, Vol.35 (3) [Periódico revisado por pares]

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Título:
A Combined Approach for Predicting Binding Affinity of Zika Virus NS2B-NS3 Protease Inhibitors Using Semi-Empirical Methods and Molecular Docking Algorithms
Autor: de Oliveira, Maycon Vinicius ; Almeida, Leonardo ; da Rocha, João ; Wanzeller, Ana Lucia ; Lima, Anderson
Assuntos: CHEMISTRY, MULTIDISCIPLINARY
É parte de: Journal of the Brazilian Chemical Society, 2024, Vol.35 (3)
Descrição: Zika virus (ZIKV) is a mosquito-borne virus that has emerged as a major public health concern due to its association with severe neurological disorders. In recent years, there has been increasing interest in exploring natural products as potential therapeutics for ZIKV infection. This study aimed to predict the binding affinity of natural compounds to the ZIKV NS2B-NS3 protease (NS2B-NS3pro) using multiple molecular docking algorithms and semiempirical quantum mechanical methods. Our results demonstrate that semiempirical methods can improve the accuracy of molecular docking studies for natural compounds. In this particular case, the PM7 (Parametric Method Number 7) method showed a significant improvement in the coefficient of determination (R2 = 0.85). We expect this combined approach to aid in the development of natural product-based therapies for ZIKV infection and to highlight the importance of continued research in this field.
Editor: Sociedade Brasileira de Química
Idioma: Inglês;Português

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