Biomedical Engineering Reference
In-Depth Information
3
Ligand-Based Drug Design
Ingrid Pettersson, Thomas Balle,
and Tommy Liljefors
CONTENTS
3.1 Introduction ........................................................................................................................... 43
3.2 The Benzodiazepine Site of GABA
A
Receptors ...................................................................44
3.3 Pharmacophore Modeling.....................................................................................................44
3.4 A 3D-Pharmacophore Model for Flavones Binding to the BZD Site ................................... 45
3.4.1 The Initial Pharmacophore Model........................................................................... 46
3.4.2 Receptor Essential Volumes and the Use of Exclusion Spheres .............................. 47
3.4.3 Extension of the Pharmacophore Model.................................................................. 48
3.5 Database Searching Using the Pharmacophore Model......................................................... 50
3.5.1 Postprocessing of Database Hits—An Essential Requirement ............................... 51
3.6 Pharmacophore-Guided Optimization of Compound 3.14 ................................................... 52
3.7 3D-QSAR Analysis—The GRID/GOLPE Approach ........................................................... 53
3.7.1 GRID Molecular Interaction Fields ......................................................................... 53
3.7.2 Development of a 3D-QSAR Model for Substituted Flavones ................................ 55
Further Readings .............................................................................................................................. 57
3.1 INTRODUCTION
The use of computational methods to facilitate the drug discovery process is today well established
and plays an important role in modern multidisciplinary drug discovery projects. A wide range of
computational methods are used to i nd new active compounds and to optimize these compounds in
order to produce new candidate drug molecules. The methods used depend on the available struc-
tural information of the target protein (or more generally the target biomacromolecule). If a three-
dimensional (3D) structure of a target enzyme or receptor with a cocrystallized ligand is available
from x-ray crystallography, a detailed knowledge of the nature of the ligand-binding site, the ligand-
binding mode, and the interactions between the ligand and the receptor/enzyme can be obtained.
On this basis, new ligands may computationally be “docked” into the binding site in order to study
if they can effectively interact with the receptor. This can be performed by using sophisticated auto-
mated l exible docking and scoring computer programs. New and promising compounds identii ed
by such computational experiments may then be synthesized and tested pharmacologically. This
procedure is known as “structure-based drug design” and is discussed in Chapter 2.
However, many proteins of high interest as drug targets have so far resisted all attempts of crys-
tallization and 3D-structure determination. This is, for instance, the case for most members of the large
and important class of seven-transmembrane (7-TM) G-protein-coupled neurotransmitter recep-
tors (see Chapter 12). In the absence of an experimentally determined 3D structure of the receptor,
computational methodologies based on an analysis of the physicochemical and pharmacological
properties of known ligands may be used for the design/discovery of new ligands. This computational
procedure is called “ligand-based drug design” and is the subject of this chapter. The purpose
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