Abstract BACKGROUND Methods & Results Conclusion Acknowledgements References Pharmacophore modeling has become an integrated part of drug discovery. The work described herein focuses on the use of ligand- based pharmacophore modeling to identify novel acetylcholinesterase inhibitors against Alzheimer’s disease. From a small training set of known dual inhibitors of the Torpedo californica acetylcholinesterase (TcAChE), we generated a series of ligand-based pharmacophore models using the Molecular Operating Environment (MOE) software 1 . The models were further used to screen a lead-like subset of the ZINC database 2 . The top 25 molecules were virtually screened against the TcAChE three-dimensional structure using Molegro Virtual Docker 3 in order to prioritize hits for experimental testing. Using a combination of ligand based and structure based drug design approaches we have identified structurally diverse dual inhibitor candidates for TcAChE. The national BBSI program (http://bbsi.eeicom.com) is a joint initiative of the NIH-NIBIB and NSF- EEC, and the BBSI @ Pitt is supported by the National Science Foundation under Grant EEC- 0234002. 1. Lin A. Overview of pharmacophore Application in MOE. Chemica Computing group. http://www.chemcomp.com/journal /ph4.htm 2. Irwin and Stoichet. J. Chem. Info. Model. (2005); 45(1): 177-182 3. Molegro Virtual Docker. www.molegro.com 4. Xu. et al. induced fit or preexisting equilibrium dynamics? Protein Science (2008), 17: 601-5 A caption, centered. • Dr Jeffry Madura • Kennesaw State University Pharmacophore Model Development for the Identification of Novel Acetylcholinesterase Inhibitors Edwin Kamau 1,2 and Gabriela Mustata 3 1 Bioengineering & Bioinformatics Summer Institute, Department Computational Biology, University of Pittsburgh, Pittsburgh, PA 15260 2 Department of Chemistry & Biochemistry, Kennesaw State University, Kennesaw, GA, 30144 3 Department Computational Biology, University of Pittsburgh, Pittsburgh, PA 15260 Acetylcholinesterase Multifunctional enzyme Function: Termination of nerve impulses of acetylcholine origin Promotes production of β-Amyloid protein Associated with pathogenesis of Alzheimer's Disease (AD) Impairs the cholinergic system Promotes formation of plaques Alzheimer's Disease Available drugs only able to treat certain stages only Structure 4 Peripheral Anionic Site (PAS) Trp 279 Catalytic Anionic Site (CAS) Trp 84 Lining of aromatic residues 55 X-ray structures with bound ligands Xu. et al. 2008,17:601-5 Drug-like Molecule Rule Ligand-Based Drug Design (MOE) Start Training set Pharmacophore Model Development Pharmacophore Model Validation 3D Database Screening Top 25 Hits Structure-Based Drug Design (Molegro) (TcAChE) Top 5 Hits Experimental Assay(TBD) SAR Data Set of AChE Dual Inhibitors Green borders: test set Red border: training set; Pharmacophore Queries 3 Queries Generated: 1.4 HYD| ARO| 3 VOLS 1.4 Donepezil HYD| ARO Ref_No _Vol HYD| ACC|DON| ARO 1.74 Consensus Features a Donepezil All training set molecules Molecule(s) Tolerance Radius Query ReF_Vol a ACC,hydrogen-bond acceptor; DON, hydrogen-bond donor; HYD, hydrophobic, ARO, ring aromatic, Vols, excluded volumes Reference queries with and without excluded volumes generated using Donepezil. Meshed spheres represent pharmacophoric features volumes in both queries. Solid spheres (red, blue and cyan represent excluded volumes Consensus query generated from flexible aligned training set. Meshed spheres are the pharmacophore features (Aro, Acc, Hyd, Don) . Molecules matching the features satisfied the query and were therefore hits Bis5 tacrine Bis10 Hupyridone Aminoquinoline28 Bw284c51 Donepezil Decamethonium Search Results and Sorting Query Ref:Vol ef:No Vol Consensus Number of hits 211 378 329 Sort top 100 100 100 100 Common hits 68 Selection based on Lowest rmsd value 25 Sorted Hits (2D Structures) 3D Database Search Docking Results (Top 5 solutions are highlighted) Virtual Screening Binding mode of E2020 (Donepezil) and ZINC3785268. Future Work Virtually screen the remaining lead-like compounds of the ZINC database Prioritize hits for experimental testing (i.e. binding free energy; types of interactions in the active site)
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Abstract
BACKGROUND
Methods & Results Conclusion
Acknowledgements
References
Pharmacophore modeling has become anintegrated part of drug discovery. The workdescribed herein focuses on the use of ligand-based pharmacophore modeling to identifynovel acetylcholinesterase inhibitors againstAlzheimer’s disease. From a small training setof known dual inhibitors of the Torpedocalifornica acetylcholinesterase (TcAChE), wegenerated a series of ligand-basedpharmacophore models using the MolecularOperating Environment (MOE) software1. Themodels were further used to screen a lead-likesubset of the ZINC database2. The top 25molecules were virtually screened against theTcAChE three-dimensional structure usingMolegro Virtual Docker3 in order to prioritizehits for experimental testing.
Using a combination of ligand based andstructure based drug design approacheswe have identified structurally diversedual inhibitor candidates for TcAChE.
The national BBSI program(http://bbsi.eeicom.com) is a jointinitiative of the NIH-NIBIB and NSF-EEC, and the BBSI @ Pitt issupported by the National ScienceFoundation under Grant EEC-0234002.
1. Lin A. Overview of pharmacophoreApplication in MOE. Chemica Computinggroup. http://www.chemcomp.com/journal/ph4.htm
2. Irwin and Stoichet. J. Chem. Info. Model.(2005); 45(1): 177-182
3. Molegro Virtual Docker. www.molegro.com
4. Xu. et al. induced fit or preexistingequilibrium dynamics? Protein Science(2008), 17: 601-5
A caption, centered.
• Dr Jeffry Madura
• Kennesaw State University
Pharmacophore Model Development for the Identification of Novel Acetylcholinesterase Inhibitors
Edwin Kamau1,2 and Gabriela Mustata3
1Bioengineering & Bioinformatics Summer Institute, Department Computational Biology, University of Pittsburgh, Pittsburgh, PA 152602Department of Chemistry & Biochemistry, Kennesaw State University, Kennesaw, GA, 301443 Department Computational Biology, University of Pittsburgh, Pittsburgh, PA 15260
Acetylcholinesterase
Multifunctional enzyme
Function: Termination of nerve
impulses of acetylcholine
origin
Promotes production of
β-Amyloid protein
Associated with pathogenesis of
Alzheimer's Disease (AD)
Impairs the cholinergic system
Promotes formation of plaques
Alzheimer's Disease Available drugs only able to treat certain stages only
Structure4
Peripheral Anionic Site (PAS)
Trp 279
Catalytic Anionic Site (CAS)
Trp 84
Lining of aromatic residues
55 X-ray structures with
bound ligands Xu. et al. 2008,17:601-5
Drug-like Molecule Rule
Ligand-Based Drug
Design (MOE)
Start
Training set
Pharmacophore Model Development
Pharmacophore Model Validation
3D Database Screening
Top 25 Hits
Structure-Based Drug
Design (Molegro)
(TcAChE)
Top 5 Hits
Experimental
Assay(TBD)
SAR Data Set of AChE Dual Inhibitors
Green borders: test setRed border: training set;
Pharmacophore Queries
3 Queries Generated:
1.4
HYD| ARO| 3 VOLS
1.4
Donepezil
HYD| ARORef_No _Vol
HYD| ACC|DON| ARO
1.74
Consensus
Features a
Donepezil
All training set
molecules
Molecule(s)Tolerance
RadiusQuery
ReF_Vol
a ACC,hydrogen-bond acceptor; DON, hydrogen-bond donor; HYD,hydrophobic, ARO, ring aromatic, Vols, excluded volumes
Reference queries with and without excluded volumes generated using Donepezil. Meshed spheres represent pharmacophoric features volumes in both queries. Solid spheres (red, blueand cyan represent excluded volumes
Consensus query generated from flexible aligned training set. Meshed spheres are the pharmacophore features (Aro, Acc, Hyd, Don) . Molecules matching the features satisfied the query and were therefore hits
Bis5 tacrineBis10 HupyridoneAminoquinoline28Bw284c51 DonepezilDecamethonium
Search Results and Sorting
Query Ref:Vol ef:No Vol Consensus
Number of hits 211 378 329
Sort top 100 100 100 100
Common hits 68
Selection based on Lowest rmsd value
25
Sorted Hits (2D Structures)
3D Database Search
Docking Results (Top 5 solutions are highlighted)
Virtual Screening
Binding mode of E2020 (Donepezil) and ZINC3785268.
Future Work Virtually screen the remaining lead-like
compounds of the ZINC database
Prioritize hits for experimental testing (i.e. binding free energy; types of interactions in the active site)
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