Caracterização molecular e investigação de mecanismos de ação anticâncer de quinona contendo dois centros redox (ENSJ-1135) através de abordagens in silico

• Ano de defesa: 2024
• Autor(a) principal: Souza, Gabriel Caetano de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Neoplasias; Simulação por Computador; Técnicas In Vitro; Preparações Farmacêuticas; Simulação de Acoplamento Molecular; Neoplasms; Computer Simulation; In Vitro Techniques; Pharmaceutical Preparations; Molecular Docking Simulation; CNPQ::CIENCIAS DA SAUDE::FARMACIA
• Link de acesso: http://repositorio.ufc.br/handle/riufc/78432

Cancer, characterized by uncontrolled proliferation of neoplastic cells, represents one of the greatest global health challenges. Tumor heterogeneity and the side effects associated with conventional treatments drive the search for new, more effective, and less toxic therapies. The identification of specific molecular targets is fundamental for the development of drugs with greater selectivity and efficacy. In this way, computational approaches have proven to be valuable tools to accelerate the drug discovery process, offering faster and more cost-effective alternatives to traditional experimental methods. Virtual screening and target fishing are examples of computational techniques that allow for the screening of large libraries of chemical compounds in search of molecules with therapeutic potential. In this study, computational tools were used to characterize and predict the pharmacokinetic and pharmacodynamic properties of the molecule ENSJ-1135 (20b). Through prediction platforms such as SwissADME and ProTox-3, the molecule's pharmacokinetic parameters, such as absorption, distribution, metabolism, excretion, and toxicity, were evaluated. Subsequently, the target fishing technique was employed to identify potential therapeutic targets, which consists of analyzing different protein-ligand interaction databases, followed by the establishment of a set of criteria to filter the most promising targets for this study. The selected targets were then subjected to molecular docking experiments to evaluate the interaction between the molecule and its protein targets. The results obtained in this study demonstrate the applicability of the computational approach employed for the identification of potential therapeutic targets for anticancer drugs under development. However, it is important to emphasize that in silico results must be validated experimentally through in vitro and in vivo assays, as experimental validation is essential to confirm the molecule's interaction with the predicted targets and to evaluate its biological activity and toxicity.