Ligand properties receptor interactions

The final part is devoted to a survey of molecular properties of special interest to the medicinal chemist. The Theory of Atoms in Molecules by R. F.W. Bader et al., presented in Chapter 7, enables the quantitative use of chemical concepts, for example those of the functional group in organic chemistry or molecular similarity in medicinal chemistry, for prediction and understanding of chemical processes. This contribution also discusses possible applications of the theory to QSAR. Another important property that can be derived by use of QC calculations is the molecular electrostatic potential. J.S. Murray and P. Politzer describe the use of this property for description of noncovalent interactions between ligand and receptor, and the design of new compounds with specific features (Chapter 8). In Chapter 9, H.D. and M. Holtje describe the use of QC methods to parameterize force-field parameters, and applications to a pharmacophore search of enzyme inhibitors. The authors also show the use of QC methods for investigation of charge-transfer complexes. 

The use of receptor-dependent (RD) QSAR adds to the QSAR model through the inclusion of ligand-receptor interactions. 5D-QSAR is unique because it mimics the binding site of the receptor (constructed from experimental data or random placement of physicochemical properties) to aid in the construction of an optimal QSAR model and to aid in the construction of a pharmacophore, yet is also alignment dependent. The FEFF 3D-QSAR method is a true RD-QSAR method using the solved 3D structure of the receptor in the calculation of ligand-receptor interaction values. 

LigandScout should serve as a basis for the comparison of feature locations and properties. Therefore, we needed to design a chemical feature set that is still universal but yet selective enough to reflect all relevant types of ligand-receptor interaction. This set is described in the next section. 

Bertin B, Freissmuth M, Breyer RM, Schutz W, Strosberg AD, Marullo S. Functional expression of the human serotonin 5-HT1A receptor in Escherichia coli. Ligand binding properties and interaction with recombinant G protein alpha-subunits. J Biol Chem 1992 267 8200-8206. 

Moreover, a final 3D-QSAR model vahdation was done using a prospective study with an external test set. The 82 compounds from the data set were used in a lead optimization project. A CoMFA model gave an (cross validated) value of 0.698 for four relevant PLS components and a conventional of 0.938 were obtained for those 82 compounds. The steric descriptors contributed 54% to the total variance, whereas the electrostatic field explained 46%. The CoMSIA model led to an (cross vahdated) value of 0.660 for five PLS components and a conventional of 0.933. The contributions for steric, electrostatic, and hydrophobic fields were 25, 44, and 31%. As a result, it was proved that the basic S4-directed substituents should be replaced against more hydrophobic building blocks to improve pharmacokinetic properties. The structural and chemical interpretation of CoMFA and CoMSIA contour maps directly pointed to those regions in the Factor Xa binding site, where steric, electronic, or hydrophobic effects play a dominant role in ligand-receptor interactions. 

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