Abstract
Background: Alzheimer’s disease (AD), an irreversible complex neurodegenerative disorder, is the most common type of dementia, with progressive loss of cholinergic neurons. Based on the multi-factorial etiology of Alzheimer’s disease, novel ligands strategy appears as an up-coming approach for the development of newer molecules against AD. This study is envisaged to investigate anti-Alzheimer’s potential of 10 synthesized compounds. The screening of compounds (1-10) was carried out using in silico techniques.
Methods: For in silico screening of physicochemical properties of compounds, Molinspiration property engine v.2018.03, Swiss ADME online web-server and pkCSM ADME were used. For pharmacodynamic prediction, PASS software was used, while the toxicity profile of compounds was analyzed through ProTox-II online software. Simultaneously, molecular docking analysis was performed on mouse AChE enzyme (PDB ID:2JGE, obtained from RSCB PDB) using Auto Dock Tools 1.5.6. Results: Based on in silico studies, compound 9 and 10 have been found to have better druglikeness, LD50 value, better anti-Alzheimer’s, and nootropic activities. However, these compounds had poor blood-brain barrier (BBB) permeability. Compounds 4 and 9 were predicted with a better docking score for the AChE enzyme. Conclusion: The outcome of in silico studies has suggested, out of various substitutions at different positions of pyridoxine-carbamate, compound 9 has shown promising drug-likeness, with better safety and efficacy profile for anti-Alzheimer’s activity. However, BBB permeability appears as one of the major limitations of all these compounds. Further studies are required to confirm its biological activities.Keywords: Carbamates, pyridoxine, AChE, in silico, PASS prediction, anti-alzheimer’s activity.
Graphical Abstract
[http://dx.doi.org/10.3389/fneur.2019.00399] [PMID: 31114535]
[http://dx.doi.org/10.1016/j.ejmech.2016.09.057] [PMID: 27721157]
[http://dx.doi.org/10.4103/1673-5374.245463] [PMID: 30539809]
[http://dx.doi.org/10.1080/14756366.2018.1543288] [PMID: 30734597]
[http://dx.doi.org/10.1093/brain/awy132] [PMID: 29850777]
[http://dx.doi.org/10.1016/j.bioorg.2019.103328] [PMID: 31600664]
[http://dx.doi.org/10.2174/1570159X11311030006] [PMID: 24179466]
[http://dx.doi.org/10.1039/C8RA08198K]
[http://dx.doi.org/10.1007/s11030-012-9372-3] [PMID: 22584731]
[http://dx.doi.org/10.25004/IJPSDR.2018.100411]
[http://dx.doi.org/10.1007/978-981-13-0347-0_13]
[http://dx.doi.org/10.1038/srep42717] [PMID: 28256516]
[PMID: 31068821]
[http://dx.doi.org/10.1093/nar/gky318] [PMID: 29718510]
[http://dx.doi.org/10.1055/s-0035-1545884] [PMID: 25856437]
[http://dx.doi.org/10.1080/19336950.2015.1092836] [PMID: 26542628]
[http://dx.doi.org/10.22159/ajpcr.2017.v10s4.21330]
[http://dx.doi.org/10.3390/molecules22111969] [PMID: 29135926]
[http://dx.doi.org/10.3390/ijms20071524] [PMID: 30934674]
[http://dx.doi.org/10.1080/14756366.2016.1212193] [PMID: 27476673]
[http://dx.doi.org/10.1016/j.biopha.2018.06.147] [PMID: 29990843]