Estudos de QSAR 2D e 3D para derivados de aminoimidazóis, aminohidantoínas e aminipiridinas com atividade inibitória sobre a enzima beta-secretase humana

Detalhes bibliográficos
Ano de defesa: 2012
Autor(a) principal: Cruz, Daniela Santos lattes
Orientador(a): Castilho, Marcelo Santos
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual de Feira de Santana
Programa de Pós-Graduação: Mestrado Acadêmico em Biotecnologia
Departamento: DEPARTAMENTO DE CIÊNCIAS BIOLÓGICAS
País: Brasil
Palavras-chave em Português:
Área do conhecimento CNPq:
Link de acesso: http://tede2.uefs.br:8080/handle/tede/1009
Resumo: Alzheimer's disease (AD) is a neurodegenerative and progressive disorder, physiologically characterized by degeneration of cholinergic neurons and formation of senile plaques containing β-amyloid peptide, which leads to cognitive and memory loss as well as dementia. The main pathophysiological event in AD is the deposition of extracellular β-amyloid peptide (βA), which originates from proteolytic action of human beta-secretase (BACE-1) over the amyloid precursor protein (APP). Therefore, inhibitors of BACE-1 may have greater therapeutic efficacy on controlling pathological process of AD, once the mechanism of action of currently available drugs provides only temporary relief from AD symptoms, without altering its progression. Recent efforts to design BACE-1 inhibitors have focused on non-peptide molecules that might overcome pharmacokinetic limitations found in transition-state mimetic inhibitors. However, the potency of these compounds has yet to be optimized. In order to contribute for this purpose QSAR models based on 2D and topological descriptors molecular fragments (hologram QSAR) and 3D models QSAR (CoMFA) have been developed for 102 derivatives aminohydantoins, aminoimidazoles and aminopyridines as inhibitors of BACE-1. HQSAR models exhibit good statistical values (r2 = 0.85/ q2 = 0.84 and r2pred = 0.70) and suggest that amine moieties bound to aminohydantoins or aminoimidazoles rings, as well as nitrogen from the pyridine ring increase potency. However, only the additional information provided by QSAR models built with topological descriptors (r2 = 0.87/ q2 = 0.85 and r2pred = 0.84) indicated that electronic features (GGI5 and GGI6) are the major underlining factors to this result. The best CoMFA model (r2 = 0.91/ q2 = 0.73 and r2pred = 0.86) was built on the basis of the maximum substructure aligment using conformation obtained by structural similarity comparison among all inhibitors and the ligands bound to 3INF or 3L38 crystallographic structures (alignment IV). Analysis of contour maps suggests, for instance, that steric hindrance near the aminoimidazol ring prevents the further addition of substituents at this point, whereas the presence of bulky moieties in the para position in the o-chloro pyridine ring would increase potency. Guided by such analysis, structural modification were proposed to develop inhibitors with increased potency.