Desenvolvimento de modelos de QSAR e planejamento de novos inibidores da enzima dUTPase de Plasmodium falciparum

• Autor(a) principal: Nascimento, Marília Nunes do
• Data de Publicação: 2015
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/001300000c5pf
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/5105
• topic: Malária; Plasmodium falciparum; Planejamento de fármacos; dUTPase; HQSAR; CoMFA; CoMSIA; Malaria; Plasmodium falciparum; Drug design; dUTPase; HQSAR; CoMFA; CoMSIA; CIENCIAS DA SAUDE::FARMACIA

Malaria is a serious endemic disease caused by parasites of the genus Plasmodium, which affects much of the population, especially in tropical and subtropical areas. Currently, drug therapy makes use of artemisinin or its derivatives associated with a second anti-malarial drug. The shortage of new treatments as well as the spread of parasite resistance to drugs currently available, makes urgent the search and discovery of new targets and new antimalarial drugs. The enzyme deoxyuridine triphosphatase (dUTPase) of Plasmodium falciparum plays an important role in maintaining balance between 2'-deoxyuridine 5'-triphosphate (dUTP) and 2'- deoxitimina 5'-triphosphate (dTTP) in order to avoid the erroneous incorporation uracil on the DNA tape. Thus, the enzyme dUTPase is a potential target for the development of new drugs, and has been validated for the organisms Escherichia coli, Saccharomyces cerevisiae and Mycobacterium smegmatis. This study aimed to carry out quantitative studies of the relationship between structure and activity (QSAR) to a series of β-branched nucleoside inhibitors PfdUTPase, in order to generate robust and predictive models to predict compounds activity untested and that may help to elucidate the important structural requirements for the affinity of this class of compounds. For this, there was the hologram QSAR analysis (HQSAR), comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). For studies of CoMFA and CoMSIA were tested two methods of calculation of partial charges, the empirical method Gasteiger-Huckel and the semi-empirical method AM1-BCC. Were also tested three structural alignment strategies based on the binder: maximum common substructure, based on the overlap of molecular volumes, and on the basis of morphological similarities; and a strategy based on the 3D coordinates of the enzymeinhibitor complex (molecular docking). The QSAR models generated showed good robustness and external predictability, showing good power correlation and prediction of affinity. The HQSAR contribution maps and contour maps of the CoMFA and CoMSIA indicated the importance of certain groups for affinity, such as the importance of the presence of at least two of trityl rings that contribute both sterically as hydrophobically to interact with the hydrophobic site of the parasite enzyme, non-existent in the human enzyme. The drug design based on information obtained from 2D and 3D QSAR, generated 121 molecules grouped into 18 clusters. Two hits with approximate power to one of the most active compounds of the series stood out by presenting appropriate physicochemical properties.