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Central Nervous System Agents in Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1871-5249
ISSN (Online): 1875-6166

Research Article

In silico Screening of Pyridoxine Carbamates for Anti-Alzheimer’s Activities

Author(s): Dnyaneshwar Baswar, Abha Sharma and Awanish Mishra*

Volume 21, Issue 1, 2021

Published on: 19 November, 2020

Page: [39 - 52] Pages: 14

DOI: 10.2174/1871524920666201119144535

Price: $65

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
[1]
Auti ST, Kulkarni YA. Neuroprotective effect of cardamom oil against aluminum induced neurotoxicity in rats. Front Neurol 2019; 10: 399.
[http://dx.doi.org/10.3389/fneur.2019.00399] [PMID: 31114535]
[2]
Mishra CB, Kumari S, Manral A, et al. Design, synthesis, in silico and biological evaluation of novel donepezil derivatives as multi-target-directed ligands for the treatment of Alzheimer’s disease. Eur J Med Chem 2017; 125: 736-50.
[http://dx.doi.org/10.1016/j.ejmech.2016.09.057] [PMID: 27721157]
[3]
Ibrahim MM, Gabr MT. Multitarget therapeutic strategies for Alzheimer’s disease. Neural Regen Res 2019; 14(3): 437-40.
[http://dx.doi.org/10.4103/1673-5374.245463] [PMID: 30539809]
[4]
Cavdar H, Senturk M, Guney M, et al. Inhibition of acetylcholinesterase and butyrylcholinesterase with uracil derivatives: Kinetic and computational studies. J Enzyme Inhib Med Chem 2019; 34(1): 429-37.
[http://dx.doi.org/10.1080/14756366.2018.1543288] [PMID: 30734597]
[5]
Hampel H, Mesulam MM, Cuello AC, et al. The cholinergic system in the pathophysiology and treatment of Alzheimer’s disease. Brain 2018; 141(7): 1917-33.
[http://dx.doi.org/10.1093/brain/awy132] [PMID: 29850777]
[6]
Nikl K, Castillo S, Hoie E, O’Brien KK. Alzheimer’s disease: Current treatments and potential new agents. US Pharm 2019; 44: 20-3.
[7]
Cai R, Wang LN, Fan JJ, Geng SQ, Liu YM. New 4-N-phenylaminoquinoline derivatives as antioxidant, metal chelating and cholinesterase inhibitors for Alzheimer’s disease. Bioorg Chem 2019; 2019: 93103328.
[http://dx.doi.org/10.1016/j.bioorg.2019.103328] [PMID: 31600664]
[8]
Colović MB, Krstić DZ, Lazarević-Pašti TD, Bondžić AM, Vasić VM. Acetylcholinesterase inhibitors: Pharmacology and toxicology. Curr Neuropharmacol 2013; 11(3): 315-35.
[http://dx.doi.org/10.2174/1570159X11311030006] [PMID: 24179466]
[9]
Jana S, Ganeshpurkar A, Singh SK. Multiple 3D-QSAR modeling, e-pharmacophore, molecular docking, and in vitro study to explore novel AChE inhibitors. RSC Advances 2018; 8: 39477-95.
[http://dx.doi.org/10.1039/C8RA08198K]
[10]
Chaudhary A, Das P, Mishra A, Kaur P, Singh B, Goel RK. Naturally occurring himachalenes to benzocycloheptene amino vinyl bromide derivatives: As antidepressant molecules. Mol Divers 2012; 16(2): 357-66.
[http://dx.doi.org/10.1007/s11030-012-9372-3] [PMID: 22584731]
[11]
Mishra SS, Kumar N, Singh HP, Ranjan S. Sharma. In silico pharmacokinetic, bioactivity and toxicity study of some selected anti-asthmatic agents. Int J Pharm Sci Drug Res 2018; 10: 278-82.
[http://dx.doi.org/10.25004/IJPSDR.2018.100411]
[12]
Alam A, Tamkeen N, Imam N, et al. Pharmacokinetic and molecular docking studies of plant-derived natural compounds to exploring potential anti-Alzheimer activity In Silico Approach Sustain Agric. 2018; 2018: pp. 217-38.
[http://dx.doi.org/10.1007/978-981-13-0347-0_13]
[13]
Daina A, Michielin O, Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 2017; 7: 42717.
[http://dx.doi.org/10.1038/srep42717] [PMID: 28256516]
[14]
Han Y, Zhang J, Hu CQ, Zhang X, Ma B, Zhang P. In silico ADME and toxicity prediction of ceftazidime and its impurities. Front Pharmacol 2019; 10: 434.
[PMID: 31068821]
[15]
Banerjee P, Eckert AO, Schrey AK, Preissner R. ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic Acids Res 2018; 46(W1): W257-63.
[http://dx.doi.org/10.1093/nar/gky318] [PMID: 29718510]
[16]
Goel RK, Gawande D, Lagunin A, Randhawa P, Mishra A, Poroikov V. Revealing medicinal plants that are useful for the comprehensive management of epilepsy and associated comorbidities through in silico mining of their phytochemical diversity. Planta Med 2015; 81(6): 495-506.
[http://dx.doi.org/10.1055/s-0035-1545884] [PMID: 25856437]
[17]
Mishra A, Punia JK, Bladen C, Zamponi GW, Goel RK. Anticonvulsant mechanisms of piperine, a piperidine alkaloid. Channels (Austin) 2015; 9(5): 317-23.
[http://dx.doi.org/10.1080/19336950.2015.1092836] [PMID: 26542628]
[18]
Anand A, Sharma N, Khurana N. Prediction of activity spectra of substances assisted prediction of biological activity spectra of potential anti-alzheimer’s phytoconstituents. Asian J Pharm Clin Res 2017; 10: 13-21.
[http://dx.doi.org/10.22159/ajpcr.2017.v10s4.21330]
[19]
Mandal M, Jaiswal P, Mishra A. Role of curcumin and its nano formulations in neurotherapeutics: A comprehensive review. J Biochem Mol Toxicol 2020; 34(6): e22478.
[20]
Maan G, Sikdar B, Kumar A, Shukla R, Mishra A. Role of flavonoids in neurodegenerative diseases: Limitations and future perspectives. Curr Top Med Chem 2020; 20(13): 1169-94.
[21]
Pizova H, Havelkova M, Stepankova S, et al. Proline-based carbamates as cholinesterase inhibitors. Molecules 2017; 22(11): 1969.
[http://dx.doi.org/10.3390/molecules22111969] [PMID: 29135926]
[22]
Bak A, Kozik V, Kozakiewicz D, et al. Novel benzene-based carbamates for ache/bche inhibition: Synthesis and ligand/structure-oriented sar study. Int J Mol Sci 2019; 20(7): 1524.
[http://dx.doi.org/10.3390/ijms20071524] [PMID: 30934674]
[23]
Horáková E, Drabina P, Brož B, et al. Synthesis, characterization and in vitro evaluation of substituted N-(2-phenylcyclopropyl) carbamates as acetyl- and butyrylcholinesterase inhibitors. J Enzyme Inhib Med Chem 2016; 31(sup3): 173-9.
[http://dx.doi.org/10.1080/14756366.2016.1212193] [PMID: 27476673]
[24]
Agatonovic-Kustrin S, Kettle C, Morton DW. A molecular approach in drug development for Alzheimer’s disease. Biomed Pharmacother 2018; 106: 553-65.
[http://dx.doi.org/10.1016/j.biopha.2018.06.147] [PMID: 29990843]

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