European Molecular Biology Laboratory. Meyerhofstr. 1, D-69117 Heidelberg, Germany
Many therapeutic agents act by binding specifically and tightly to a particular macromolecular target such as a receptor protein or a nucleic acid. Such binding is dependent on the energetics of the interactions between the atoms of the active compound and the atoms of the macromolecular target. In this chapter, we will discuss approaches to ligand design based on molecular interaction energies. For a molecule of known 3D structure, molecular interaction fields can be calculated. These describe how the interaction energy between the molecule and different ligands or fragments of ligands varies in the surrounding volume. Regions of large positive interaction energy indicate regions from which the ligand fragments are repelled while those of large negative energy correspond to energetically favorable binding regions for the ligand fragments. These regions can be exploited in the design of ligands to bind with high affinity and specificity to particular molecules.
The strategy adopted in order to design therapeutic agents is dependent upon how much structural information is available about active compounds and about the target macromolecule(s). If the 3D structure of the target macromolecule is known, molecular interaction fields can be calculated, and may be used in order to design ligands de novo or to dock known ligands in their binding site. In many cases, however, the 3D structure of the target macromolecule is unknown. Then,information about the potency of a number of compounds is required in order to derive structure-activity relationships (SARs) which can be used to design new compounds with improved activity. In 3D QSAR studies, molecular interaction fields for different compounds are analyzed statistically to derive SARs. Compounds binding to the same target macromolecule can be expected to have molecular interaction fields that share some common features. The physicochemical properties of active compounds, such as lipophilicity, are also dependent on their molecular interaction fields and can be optimized by 3D QSAR methods.
In ``3D QSAR in Drug Design. Theory, Methods and Applications''
ESCOM, Leiden, (1993), pp486-505.