Medicinal Chemistry/ CHEM 458/658 Chapter 4- Computer-Aided Drug Design

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Transcription:

Medicinal Chemistry/ CHEM 458/658 Chapter 4- Computer-Aided Drug Design Bela Torok Department of Chemistry University of Massachusetts Boston Boston, MA 1

Computer Aided Drug Design - Introduction Development of computers - hardware - algorithms softwares - computation chemists - representation 2

Computer Aided Drug Design - Introduction Models Molecular modelling methods - Molecular or quantum mechanics - Semiempirical vs ab initio methods - Cartesian and polar coordinates 3

Computer Aided Drug Design - Introduction Computer graphics - space fill, CPK (Corey-Pauling-Koulton), stick, stick and ball, mesh, ribbon, surface, molecular dinamics etc. 4

Molecular Mechanics Basis: E total = Σ attractive + repulsive forces - mechanical method atoms are balls with respective atomic masses 5

Molecular Mechanics E total = Σ E stretching +Σ E bend +ΣE torsion +ΣE vdw +ΣE coulombic 6

Molecular Mechanics Creating a molecular model using molecular mechanics - Joining fragments from program database - Prepare 2D structure and convert it to 3D structure - Converting an existing model from the database 7

Molecular Dynamics Creating a dynamic molecular model - atomic coordinates (twist, bend, stretch etc.) - conformational analysis 8

Quantum Mechanics Schrodinger equation, Born-Oppenheimer approximation - simplification Hartree-Fock approximation Density Funtional Theory Practice Gaussian 03 (or 98) ab initio methods Gamess The Nobel Prize in Chemistry 1998 Walter Kohn "for his development of the density-functional theory" John A. Pople "for his development of computational methods in quantum chemistry" 9

Docking Produce and investigate the complex of large biomolecule (host) and the drug (or candidate) (ligand) E binding = E target + E ligand E target-ligand Global E min Bioactive conformer 10

Docking De novo design Using docking programs to design new lead structures The template method The component fragment method 11

Docking A case study Inhibition of FBPase (Kimberly Stieglitz) Start: - build and optimize the drug candidate ChemDraw and import to Gaussian or get crystal structure (CCD) - get protein (enzyme or receptor) structure PDB 12

Docking A case study Inhibition of FBPase - list of compounds 13

Docking A case study Inhibition of FBPase - protein structure 14

Docking A case study Inhibition of FBPase - docking 15

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Docking A case study Inhibition of FBPase - visualization 17

Docking 18

Docking 19

Docking 20

Comparing 3D Structure by Overlays 21

Comparing 3D Structure by Overlays 22

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Pharmacophores A case study Inhibition of AChE - Marianna Torok, Seema Bag 24

Pharmacophores Typical pharmacophore features are: - Hydrophobic - Aromatic - Hydrogen bond donor/acceptor - Cation/anion The features need to match different chemical groups with similar properties, in order to identify novel ligands. Ligands receptor interactions are typically polar positive, polar negative or hydrophobic. A well-defined pharmacophore model includes both hydrophobic volumes and hydrogen bond vectors. 25

Pharmacophores Select molecules: 50 100 highly active molecules Training set + test set Prepare Ligands PHASE Version 3.0 Find common pharmacophore using binary decision tree Create pharmacophoric sites Alignment Build QSAR model r 2 & q2 value Screen/design for more potent analogs 26

Pharmacophores Pharmacophoric points on active molecules 27

Interpretation Pharmacophores H-donor Hydrophobic 28

Pharmacophores 29

Pharmacophores galanthamine dihydrocodein morphine 30

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Modeling Protein Structures Solvent Mapping (Sandor Vajda, BU) 16 solvents: ethanol, acetaldehyde, acetonitrile, benzaldehyde, isopropanol, methanol, dimethyl ether, urea, benzene, t-butanol, isobutanol, cyclohexane, methanamine, acetamide, phenol, acetone, dimethylformamide and ethane) will be used in rigid-body fragment docking 32

Modeling Protein Structures 33

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