| Autor: |
Mascarenhas AMS; Laboratório de Modelagem Molecular, Departamento de Saúde, Universidade Estadual de Feira de Santana, Bahia, Brasil., de Almeida RBM; Laboratório de Toxicologia, Departamento de Saúde, Universidade Estadual de Feira de Santana, Bahia, Brasil., de Araujo Neto MF; Laboratório de Modelagem Molecular, Departamento de Saúde, Universidade Estadual de Feira de Santana, Bahia, Brasil., Mendes GO; Laboratório de Modelagem Molecular, Departamento de Saúde, Universidade Estadual de Feira de Santana, Bahia, Brasil., da Cruz JN; Laboratório de Modelagem e Química Computacional, Departamento de Ciências Biológicas e da Saúde, Universidade Federal do Amapá, Macapá, Brasil., Dos Santos CBR; Laboratório de Modelagem e Química Computacional, Departamento de Ciências Biológicas e da Saúde, Universidade Federal do Amapá, Macapá, Brasil., Botura MB; Laboratório de Toxicologia, Departamento de Saúde, Universidade Estadual de Feira de Santana, Bahia, Brasil., Leite FHA; Laboratório de Modelagem Molecular, Departamento de Saúde, Universidade Estadual de Feira de Santana, Bahia, Brasil. |
| Abstrakt: |
The dual inhibition of human acetylcholinesterase (hAChE) and butyrylcholinesterase (hBuChE) plays an important role in Alzheimer's disease treatment. Thus, this study aims identify promising dual inhibitors against hAChE and hBuChE by in silico approaches (pharmacophore-based virtual screening and molecular docking). Ten 3 D pharmacophore models for dual inhibitors using default genetic parameters were built by GALAHAD™ available on SYBYL-X 2.0. Validation steps were carried out according to Energy (<100.0 kcal/mol), Pareto = 0, Area under the ROC Curve (>0.70), Boltzmann-Enhanced Discrimination of ROC curve (BEDROC >0.50) and structure-activity relationship (SAR) for known inhibitors. The best dual pharmacophore model based on internal/external statistical parameters and SAR data (one hydrogen bond acceptor, two hydrogen bond donors and four hydrophobic centers) was employed in virtual screening at Sigma-Aldrich® subset ( n = 214,446) of ZINC database by UNITY module of SYBYL-X 2.0. According to superposition values (QFIT), the best ranked compounds were prioritized for molecular docking and partition coefficient analysis (clog p < 5.0). 37 top-ranked compounds (QFIT > 64.22) from pharmacophore model showed affinity in hAChE (-10.2 < Affinity energy < -6.3 kcal/mol) and hBuChE (-10.9 < Affinity energy < -2.3 kcal/mol) binding sites. Next, liposolubity prediction and commercially available showed that ZINC43198636, ZINC43198637 and ZINC00390718 can be potential dual inhibitors against hAChE and hBuChE.Communicated by Ramaswamy H. Sarma. |
