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<p>Chikungunya fever is an arboviral disease characterized by high fever, rash, and intense polyarthralgia, which may persist and evolve into a chronic condition, significantly impairing quality of life. The etiological agent, Chikungunya virus (CHIKV), is an alphavirus transmitted by Aedes aegypti mosquitoes and represents an increasing global public health concern due to its epidemic potential, economic burden, and the lack of specific antiviral therapies. In this context, in silico methodologies have become valuable tools in drug discovery and repurposing. This study aimed to predict natural compounds capable of inhibiting CHIKV non-structural protein 3 (nsP3). A total of 84,215 natural compounds from the ZINC20 database were screened through molecular docking using AutoDock Vina, with nsP3 as the target receptor. Ligand-protein interactions were visualized and analyzed with LigPlot+ and PyMOL. The top candidates were further refined through bioisosteric modifications using MolOpt, and their pharmacokinetic properties were predicted via the pkCSM platform. Among the optimized molecules, three bioisosteres, Chikv_bio1, Chikv_bio2, and Chikv_bio3, demonstrated favorable docking scores, interaction profiles, and ADMET properties, suggesting promising inhibitory activity against nsP3. These findings support the potential of natural compound-based drug design and highlight the importance of advancing to in vitro and in vivo validation to confirm the therapeutic relevance of these candidates and contribute to the development of specific treatments for Chikungunya fever.</p>

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Bioisosteric and Virtual Screening Approach to Identify Natural Inhibitors of Chikunguya alphavirus nsP3

  • 期刊论文

  • 发表日期：

    2025年8月26日

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  • Cássia Milene Ribeiro Lopes,
  • Leonardo Pereira de Araújo,
  • Caio Pacífico Mariano,
  • Lorena Falleiros,
  • Walter Filgueira de Azevedo Junior,
  • Luiz Felipe Leomil Coelho,
  • Nelson José Freitas da Silveira

摘要

Chikungunya fever is an arboviral disease characterized by high fever, rash, and intense polyarthralgia, which may persist and evolve into a chronic condition, significantly impairing quality of life. The etiological agent, Chikungunya virus (CHIKV), is an alphavirus transmitted by Aedes aegypti mosquitoes and represents an increasing global public health concern due to its epidemic potential, economic burden, and the lack of specific antiviral therapies. In this context, in silico methodologies have become valuable tools in drug discovery and repurposing. This study aimed to predict natural compounds capable of inhibiting CHIKV non-structural protein 3 (nsP3). A total of 84,215 natural compounds from the ZINC20 database were screened through molecular docking using AutoDock Vina, with nsP3 as the target receptor. Ligand-protein interactions were visualized and analyzed with LigPlot+ and PyMOL. The top candidates were further refined through bioisosteric modifications using MolOpt, and their pharmacokinetic properties were predicted via the pkCSM platform. Among the optimized molecules, three bioisosteres, Chikv_bio1, Chikv_bio2, and Chikv_bio3, demonstrated favorable docking scores, interaction profiles, and ADMET properties, suggesting promising inhibitory activity against nsP3. These findings support the potential of natural compound-based drug design and highlight the importance of advancing to in vitro and in vivo validation to confirm the therapeutic relevance of these candidates and contribute to the development of specific treatments for Chikungunya fever.