Computational approaches to assess the binding properties of ligands: The case of the nmda receptor

One of the important issues in drug design is the identification of the biological activity of receptor ligands. Development, synthesis and activity measurements of ligands have a major importance in drug design. However, there are certain limits in experimental studies; synthesis of a large number of compounds to cover all the potentially active molecules is unrealistic. Computational studies could therefore provide a valuable aid to experimental studies on ligand design for glutamate receptors. By combining the strengths of Molecular Dynamics and Quantum Chemical approaches, a more focused inspection, characterisation and rationalization of the drug design studies is allowed to be established. In this dissertation, computational methods have been used to investigate the intrinsic properties of the biologically active molecules that cause the selectivity. The results of this study will be introduced in 4 chapters. In Chapters 4 and 5, we aimed to differentiate between agonists, antagonists and partial agonists based on Quantum Chemical descriptors and binding Gibbs free energies. Several molecular properties that could play a role in ligand binding to the glycine GluN1 subunit of NMDA and calculated binding Gibbs free energies were further used to provide a link between the efficacies and binding affinities of the ligands. Prediction of the acid dissociation constants of amino acids in proteins and ligands allows us to have information about the binding affinity and efficacy of the ligand to its target protein. Considering the significance of pKa's, how atomic charges of carboxylic acids can be related to the prediction of pKa of the ligands have been explored in Chapter 6. In order to shed light on the origins of the stereoselectivity of biologically active ligands, several mechanistic pathways have been evaluated for 2-thiohydantoins which are potent androgen receptor antagonists and the results are given in Chapter 7.