Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study

Alzheimer's disease (AD) leads to gradual memory loss including other compromised cognitive abilities. Acetylcholinesterase (AChE), an important biochemical enzyme from the cholinesterase (ChE) family, is recognized as primary pharmacological target for treating AD. Currently marketed drugs for...

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Main Authors: Bikram Saha, Agnidipta Das, Kailash Jangid, Amit Kumar, Vinod Kumar, Vikas Jaitak
Format: Article
Language:English
Published: Elsevier 2024-01-01
Series:Current Research in Structural Biology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2665928X24000011
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author Bikram Saha
Agnidipta Das
Kailash Jangid
Amit Kumar
Vinod Kumar
Vikas Jaitak
author_facet Bikram Saha
Agnidipta Das
Kailash Jangid
Amit Kumar
Vinod Kumar
Vikas Jaitak
author_sort Bikram Saha
collection DOAJ
description Alzheimer's disease (AD) leads to gradual memory loss including other compromised cognitive abilities. Acetylcholinesterase (AChE), an important biochemical enzyme from the cholinesterase (ChE) family, is recognized as primary pharmacological target for treating AD. Currently marketed drugs for AD treatment are primarily AChE inhibitors and coumarin derivatives comprising a wide variety of pharmacological activities have proved their efficacy towards AChE inhibition. Ensaculin (KA-672 HCl), a compound that belong to the coumarin family, is a clinical trial candidate for AD treatment. Therefore, a ligand library was prepared with 60 reported coumarin derivatives for field-based 3D-QSAR and pharmacophore modelling. The field-based 3D-QSAR model obtained at partial least square (PLS) factor 7, was the best validated model that predicted activity closer to original activity for each ligand introduced. The contour maps demonstrated spatial distribution of favourable and unfavorable steric, hydrophobic, electrostatic and H-bond donor and acceptor contours around coumarin nucleus. The best pharmacophore model, ADHRR_1 exhibited five essential pharmacophoric features of four different traits for optimum AChE inhibition. Virtual screening through ADHRR_1 accompanied with molecular docking and MM/GBSA identified 10 HITs from a 4,00,000 coumarin derivatives from PubChem database. HITs comprised docking scores ranging from −12.096 kcal/mol to −8.271 kcal/mol and compared with the reference drug Donepezil (-8.271 kcal/mol). ADME properties analysis led into detecting two leads (HIT 1 and HIT 2) among these 10 HITs. Molecular Dynamics Simulation indicated thermodynamic stability of the complex of lead compounds with AChE protein. Finally, thorough survey of the experimental results from 3D-QSAR modelling, pharmacophore modelling and molecular docking interactions led us to develop the lead formula I for future advancements in treating AD through AChE inhibitors.
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spelling doaj.art-1f36d7e3d3fd4a38971f8d58fc09fe832024-01-14T05:40:01ZengElsevierCurrent Research in Structural Biology2665-928X2024-01-017100124Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation studyBikram Saha0Agnidipta Das1Kailash Jangid2Amit Kumar3Vinod Kumar4Vikas Jaitak5Department of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Ghudda, Bathinda, 151401, IndiaDepartment of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Ghudda, Bathinda, 151401, IndiaDepartment of Chemistry, Central University of Punjab, Ghudda, Bathinda, 151401, IndiaDepartment of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Ghudda, Bathinda, 151401, IndiaDepartment of Chemistry, Central University of Punjab, Ghudda, Bathinda, 151401, IndiaDepartment of Pharmaceutical Sciences and Natural Products, Central University of Punjab, Ghudda, Bathinda, 151401, India; Corresponding author.Alzheimer's disease (AD) leads to gradual memory loss including other compromised cognitive abilities. Acetylcholinesterase (AChE), an important biochemical enzyme from the cholinesterase (ChE) family, is recognized as primary pharmacological target for treating AD. Currently marketed drugs for AD treatment are primarily AChE inhibitors and coumarin derivatives comprising a wide variety of pharmacological activities have proved their efficacy towards AChE inhibition. Ensaculin (KA-672 HCl), a compound that belong to the coumarin family, is a clinical trial candidate for AD treatment. Therefore, a ligand library was prepared with 60 reported coumarin derivatives for field-based 3D-QSAR and pharmacophore modelling. The field-based 3D-QSAR model obtained at partial least square (PLS) factor 7, was the best validated model that predicted activity closer to original activity for each ligand introduced. The contour maps demonstrated spatial distribution of favourable and unfavorable steric, hydrophobic, electrostatic and H-bond donor and acceptor contours around coumarin nucleus. The best pharmacophore model, ADHRR_1 exhibited five essential pharmacophoric features of four different traits for optimum AChE inhibition. Virtual screening through ADHRR_1 accompanied with molecular docking and MM/GBSA identified 10 HITs from a 4,00,000 coumarin derivatives from PubChem database. HITs comprised docking scores ranging from −12.096 kcal/mol to −8.271 kcal/mol and compared with the reference drug Donepezil (-8.271 kcal/mol). ADME properties analysis led into detecting two leads (HIT 1 and HIT 2) among these 10 HITs. Molecular Dynamics Simulation indicated thermodynamic stability of the complex of lead compounds with AChE protein. Finally, thorough survey of the experimental results from 3D-QSAR modelling, pharmacophore modelling and molecular docking interactions led us to develop the lead formula I for future advancements in treating AD through AChE inhibitors.http://www.sciencedirect.com/science/article/pii/S2665928X24000011Alzheimer's diseaseCoumarinAcetylcholine esterasePharmacophore3D-QSAR
spellingShingle Bikram Saha
Agnidipta Das
Kailash Jangid
Amit Kumar
Vinod Kumar
Vikas Jaitak
Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study
Current Research in Structural Biology
Alzheimer's disease
Coumarin
Acetylcholine esterase
Pharmacophore
3D-QSAR
title Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study
title_full Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study
title_fullStr Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study
title_full_unstemmed Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study
title_short Identification of coumarin derivatives targeting acetylcholinesterase for Alzheimer's disease by field-based 3D-QSAR, pharmacophore model-based virtual screening, molecular docking, MM/GBSA, ADME and MD Simulation study
title_sort identification of coumarin derivatives targeting acetylcholinesterase for alzheimer s disease by field based 3d qsar pharmacophore model based virtual screening molecular docking mm gbsa adme and md simulation study
topic Alzheimer's disease
Coumarin
Acetylcholine esterase
Pharmacophore
3D-QSAR
url http://www.sciencedirect.com/science/article/pii/S2665928X24000011
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