Planejamento in silico de inibidores da enzima dihidrofolato redutase

Detalhes bibliográficos
Ano de defesa: 2016
Autor(a) principal: Matos, Isaac de Araujo lattes
Orientador(a): Costa Júnior, Nivan Bezerra da
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Sergipe
Programa de Pós-Graduação: Pós-Graduação em Química
Departamento: Não Informado pela instituição
País: Brasil
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: https://ri.ufs.br/handle/riufs/5358
Resumo: Inhibition of the folate metabolism is an important strategy in the treatment of infectious diseases. In the folate metabolism, the dihydrofolate reductase (DHFR) catalyses the reduction of dihydrofolate to tetrahydrofolate. This metabolite is essential for the synthesis of DNA and proteins. Therefore, developing new dihydrofolate reductase antagonist has been considered as a good strategy to improve infectious diseases treatment. In this work, a quantitative study of structure-activity relationship of 17 diaminonazolines inhibitors of the Staphylococcus aureus DHFR (SaDHFR), were performed by using multiple linear regression. Seven inhibitors, not included in the training group, were used to validate the QSAR model. In addition, molecular docking was used to study molecular recognition between SaDHFR and diaminoquinazolines derivatives. Moreover, theoretical pharmacokinetics and toxicological profile was determined for the most potent ligands. The molecular docking study suggest that hydrophobic interactions between the ligand and the residues Ile51, Phe93, Leu55, Val32 and Leu29, are important for potency. The model of QSAR generated values of R2 training, Q2 and R2 pred equal to 0.90, 0.90 and 0.65, respectively. The descriptors included in the model, indicate the importance of pKa and molar refractivity biological activity. The analogs 28A-12, 28A-13 e 28A- 21 exhibit a favorable theoretical pharmacodynamics, pharmacokinetics and toxicological profile. The results obtained for different computational approaches, may be useful in design of new antimicrobial drugs more potent and with few side effects.