scholarly journals Acetylcholinesterase inhibition, molecular docking and ADME prediction studies of new dihydrofuran-piperazine hybrid compounds

Author(s):  
Sait SARI ◽  
Mehmet YILMAZ
PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2322 ◽  
Author(s):  
Saw Simeon ◽  
Nuttapat Anuwongcharoen ◽  
Watshara Shoombuatong ◽  
Aijaz Ahmad Malik ◽  
Virapong Prachayasittikul ◽  
...  

Alzheimer’s disease (AD) is a chronic neurodegenerative disease which leads to the gradual loss of neuronal cells. Several hypotheses for AD exists (e.g., cholinergic, amyloid, tau hypotheses, etc.). As per the cholinergic hypothesis, the deficiency of choline is responsible for AD; therefore, the inhibition of AChE is a lucrative therapeutic strategy for the treatment of AD. Acetylcholinesterase (AChE) is an enzyme that catalyzes the breakdown of the neurotransmitter acetylcholine that is essential for cognition and memory. A large non-redundant data set of 2,570 compounds with reported IC50values against AChE was obtained from ChEMBL and employed in quantitative structure-activity relationship (QSAR) study so as to gain insights on their origin of bioactivity. AChE inhibitors were described by a set of 12 fingerprint descriptors and predictive models were constructed from 100 different data splits using random forest. Generated models affordedR2, ${Q}_{\mathrm{CV }}^{2}$ and ${Q}_{\mathrm{Ext}}^{2}$ values in ranges of 0.66–0.93, 0.55–0.79 and 0.56–0.81 for the training set, 10-fold cross-validated set and external set, respectively. The best model built using the substructure count was selected according to the OECD guidelines and it affordedR2, ${Q}_{\mathrm{CV }}^{2}$ and ${Q}_{\mathrm{Ext}}^{2}$ values of 0.92 ± 0.01, 0.78 ± 0.06 and 0.78 ± 0.05, respectively. Furthermore, Y-scrambling was applied to evaluate the possibility of chance correlation of the predictive model. Subsequently, a thorough analysis of the substructure fingerprint count was conducted to provide informative insights on the inhibitory activity of AChE inhibitors. Moreover, Kennard–Stone sampling of the actives were applied to select 30 diverse compounds for further molecular docking studies in order to gain structural insights on the origin of AChE inhibition. Site-moiety mapping of compounds from the diversity set revealed three binding anchors encompassing both hydrogen bonding and van der Waals interaction. Molecular docking revealed that compounds13,5and28exhibited the lowest binding energies of −12.2, −12.0 and −12.0 kcal/mol, respectively, against human AChE, which is modulated by hydrogen bonding,π–πstacking and hydrophobic interaction inside the binding pocket. These information may be used as guidelines for the design of novel and robust AChE inhibitors.


2020 ◽  
Vol 32 (6) ◽  
pp. 1482-1490
Author(s):  
Manju Mathew ◽  
Raja Chinnamanayakar ◽  
Ezhilarasi Muthuvel Ramanathan

A series of 1-(5-(5-(4-chlorophenyl)furan-2-yl)-4,5-dihyropyrazol-1-yl ethanone (5a-h) was synthesized through E-(3-(5-(4-chloro-phenyl)furan-2-yl)-1-phenylprop-2-en-1-one (3a-h) with hydrazine monohydrate and sodium acetate. Totally, eight compounds were synthesized and their structures were elucidated by infrared, 1H & 13C NMR, elemental analysis, antimicrobial studies, in silico molecular docking studies and also in silico ADME prediction. Antimicrobial studies of the synthesized compounds showed good to moderate activity against the all the stains compared with standard drugs. in silico Molecular docking study was carried out using bacterial protein and BC protein. Synthesized compounds (5a-h) showed good docking score compared with ciprofloxacin. Antimicrobial study was carried out for 4-chlorophenyl furfuran pyrazole derivatives (5a-h). The results of assessment of toxicities, drug likeness and drug score profiles of compounds (5a-j) are promising


2012 ◽  
Vol 21 (12) ◽  
pp. 4239-4251 ◽  
Author(s):  
Sunil Kumar Tripathi ◽  
Chandrabose Selvaraj ◽  
Sanjeev Kumar Singh ◽  
Karnati Konda Reddy

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Lilly Aswathy ◽  
Radhakrishnan S. Jisha ◽  
Vijay H. Masand ◽  
Jayant M. Gajbhiye ◽  
Indira G. Shibi

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