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Identification of potential human beta-secretase 1 inhibitors by hierarchical virtual screening and molecular dynamics.
do Bomfim, Mayra Ramos; Barbosa, Deyse Brito; de Carvalho, Paulo Batista; da Silva, Alisson Marques; de Oliveira, Tiago Alves; Taranto, Alex Gutterres; Leite, Franco Henrique Andrade.
Afiliação
  • do Bomfim MR; Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Estadual de Feira de Santana, Feira de Santana, Brazil.
  • Barbosa DB; Programa de Pós-Graduação em Ciências Farmacêuticas, Universidade Estadual de Feira de Santana, Feira de Santana, Brazil.
  • de Carvalho PB; Feik School of Pharmacy, University of the Incarnate Word, San Antonio, TX, USA.
  • da Silva AM; Departamento de Informática, Gestão e Design, Centro Federal de Educação Tecnológica de Minas Gerais, Divinópolis, Brazil.
  • de Oliveira TA; Departamento de Informática, Gestão e Design, Centro Federal de Educação Tecnológica de Minas Gerais, Divinópolis, Brazil.
  • Taranto AG; Departamento de Bioengenharia, Universidade Federal de São João del-Rei, São João del-Rei, Brazil.
  • Leite FHA; Departamento de Bioengenharia, Universidade Federal de São João del-Rei, São João del-Rei, Brazil.
J Biomol Struct Dyn ; 41(10): 4560-4574, 2023 Jul.
Article em En | MEDLINE | ID: mdl-35491692
Alzheimer's disease (AD) is a neurodegenerative pathology responsible for 70% of dementia cases worldwide. Despite its relevance, the few drugs available for the treatment of this disease offer only symptomatic relief, with limited efficacy and serious adverse effects. The most accepted hypothesis about the pathogenesis involves the aggregation and deposition of ß-amyloid peptides, mainly in the cerebral cortex and hippocampus, through the catalytic action of beta-secretase 1 (BACE-1), making this enzyme a promising target for the development of new drugs. In order to prioritize candidates for BACE-1 inhibitors, a hierarchical virtual screening by pharmacophore model and molecular docking was performed against the 216,833 molecules contained in several databases. Our previously built pharmacophore model was used for the first filtering step, which resulted in the selection of 399 molecules. The remaining molecules were filtered through molecular docking with GOLD 5.4.0. In this step, molecules with scoring values ​​greater than the mean plus standard deviation were evaluated for commercial availability and absence of asymmetric centers. Four molecules were selected and evaluated for mutagenic potential by the AMES test with the help of the pkCSM server. Finally, they were tested against the descriptors on Lipinski and Veber rules, and ZINC01589617 (QFIT = 56.52/Score = 44.95) satisfied all requirements, being subjected to molecular dynamics simulations (t = 100 ns) in order to obtain robust data on the mode of bonding and profile of intermolecular interactions. Those in silico strategies demonstrated that ZINC01589617 is a potential candidate for biological tests.Communicated by Ramaswamy H. Sarma.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação de Dinâmica Molecular / Doença de Alzheimer Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação de Dinâmica Molecular / Doença de Alzheimer Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article