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In silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease.
CNS Neurol Disord Drug Targets. 2018 04 26; 17(1):54-68.CN

Abstract

OBJECTIVE AND BACKGROUND

Inhibition of acetylcholinesterase (AChE) has gained much importance since the discovery of the involvement of peripheral anionic site as an allosteric regulator of AChE. Characterized by the formation of β-amyloid plaques, Alzheimer's disease (AD) is currently one of the leading causes of death across the world. Progression in this neurodegenerative disorder causes deficit in the cholinergic activity that leads towards cognitive decline. Therapeutic interventions in AD are largely focused upon AChE inhibitors designed essentially to prevent the loss of cholinergic function. The multifactorial AD pathology calls for Multitarget-directed ligands (MTDLs) to follow up on various components of the disease. Considering this approach, other related AD targets were also selected. Structure-based virtual screening was relied upon for the identification of lead compounds with anti-AD effect.

METHOD

Several chemoinformatics approaches were used in this study, reporting four multi-target inhibitors: MCULE-7149246649-0-1, MCULE-6730554226-0-4, MCULE-1176268617-0-6 and MCULE-8592892575-0-1 with high binding energies that indicate better AChE inhibitory activity. Additional in-silico analysis hypothesized the abundant presence of aromatic interactions to be pivotal for interaction of selected compounds to the acetyl-cholinesterase. Additionally, we presented an alternative approach to determine protein-ligand stability by calculating the Gibbs-free energy change over time. Furthermore, this allows to rank potential hits for further in-vitro testing.

RESULTS AND CONCLUSION

With no predicted indication of adverse effects on humans, this study unravels four active multi-target inhibitors against AChE with promising affinities and good ADMET profile for the potential use in AD treatment.

Authors+Show Affiliations

Department of Biochemistry, Kinnaird College for Women, Lahore, Pakistan.Centre for Research in Molecular Medicine, The University of Lahore, Lahore, Pakistan. Department of Pharmaceutical and Pharmacological Sciences, Rega Institute for Medical Research, Medicinal Chemistry, University of Leuven, Leuven B-3000, Belgium.Department of Psychiatry and Behavioral Sciences, Services Institute of Medical Sciences (SIMS)/Services Hospital. Lahore, Pakistan.Department of Pharmaceutical and Pharmacological Sciences, Rega Institute for Medical Research, Medicinal Chemistry, University of Leuven, Leuven B-3000, Belgium.Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore, Pakistan.King Fahd Medical Research Center, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia. Enzymoics, 7 Peterlee Place, Hebersham, NSW 2770, Australia. Novel Global Community Educational Foundation, Sydney, Australia.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

29336270

Citation

Iman, Kanzal, et al. "In Silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease." CNS & Neurological Disorders Drug Targets, vol. 17, no. 1, 2018, pp. 54-68.
Iman K, Mirza MU, Mazhar N, et al. In silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease. CNS Neurol Disord Drug Targets. 2018;17(1):54-68.
Iman, K., Mirza, M. U., Mazhar, N., Vanmeert, M., Irshad, I., & Kamal, M. A. (2018). In silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease. CNS & Neurological Disorders Drug Targets, 17(1), 54-68. https://doi.org/10.2174/1871527317666180115162422
Iman K, et al. In Silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease. CNS Neurol Disord Drug Targets. 2018 04 26;17(1):54-68. PubMed PMID: 29336270.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - In silico Structure-based Identification of Novel Acetylcholinesterase Inhibitors Against Alzheimer's Disease. AU - Iman,Kanzal, AU - Mirza,Muhammad Usman, AU - Mazhar,Nauman, AU - Vanmeert,Michiel, AU - Irshad,Imran, AU - Kamal,Mohammad A, PY - 2016/08/16/received PY - 2017/04/22/revised PY - 2017/05/24/accepted PY - 2018/1/18/pubmed PY - 2019/6/1/medline PY - 2018/1/17/entrez KW - AChE KW - ADMET KW - Alzheimer's disease (AD) KW - Molecular docking KW - Pharmacoinformtics KW - Virtual screening. SP - 54 EP - 68 JF - CNS & neurological disorders drug targets JO - CNS Neurol Disord Drug Targets VL - 17 IS - 1 N2 - OBJECTIVE AND BACKGROUND: Inhibition of acetylcholinesterase (AChE) has gained much importance since the discovery of the involvement of peripheral anionic site as an allosteric regulator of AChE. Characterized by the formation of β-amyloid plaques, Alzheimer's disease (AD) is currently one of the leading causes of death across the world. Progression in this neurodegenerative disorder causes deficit in the cholinergic activity that leads towards cognitive decline. Therapeutic interventions in AD are largely focused upon AChE inhibitors designed essentially to prevent the loss of cholinergic function. The multifactorial AD pathology calls for Multitarget-directed ligands (MTDLs) to follow up on various components of the disease. Considering this approach, other related AD targets were also selected. Structure-based virtual screening was relied upon for the identification of lead compounds with anti-AD effect. METHOD: Several chemoinformatics approaches were used in this study, reporting four multi-target inhibitors: MCULE-7149246649-0-1, MCULE-6730554226-0-4, MCULE-1176268617-0-6 and MCULE-8592892575-0-1 with high binding energies that indicate better AChE inhibitory activity. Additional in-silico analysis hypothesized the abundant presence of aromatic interactions to be pivotal for interaction of selected compounds to the acetyl-cholinesterase. Additionally, we presented an alternative approach to determine protein-ligand stability by calculating the Gibbs-free energy change over time. Furthermore, this allows to rank potential hits for further in-vitro testing. RESULTS AND CONCLUSION: With no predicted indication of adverse effects on humans, this study unravels four active multi-target inhibitors against AChE with promising affinities and good ADMET profile for the potential use in AD treatment. SN - 1996-3181 UR - https://www.unboundmedicine.com/medline/citation/29336270/In_silico_Structure_based_Identification_of_Novel_Acetylcholinesterase_Inhibitors_Against_Alzheimer's_Disease_ DB - PRIME DP - Unbound Medicine ER -