MDL-100453

NR2 subunits of N-methyl-d-aspartic acid (NMDA) receptors are known to bind the neurotransmitter glutamate, competitive agonists, and antagonists. Since crystallographic data of these proteins are not available, we built a homology model of the ligand binding domain of the NR2A subunit. A consensus binding mode of selected AP5-like NMDA antagonists has been ascertained using molecular docking. The present 3D model gives insights for the design of new NMDA subtype selective compounds.

Glutamic acid is an excitatory amino acid neurotransmitter in the mammalian central nervous system and the NMDA mol. binds to NMDA-type glutamic acid receptors as a glutamic acid analog, in vitro.The NMDA-type glutamic acid receptors are known for their function in many neural processes, such as neural plasticity, learning and memory.In addition, excessive NMDA receptor activity has been shown to be related to neurodegenerative diseases like epilepsy so the design of new NMDA antagonists has extra importance as potent drugs for various neural diseases.Potential antagonist mols. are usually synthesized and their activity is measured by exptl. techniques.Here, computational chem. methods are applied to develop a model, which allows one to predict the activity of potent competitive NMDA antagonists.First, various mol. parameters are calculated for a series of competitive NMDA antagonists with known activity values and those parameters are used to make a regression anal. which provides a model that relates the computationally calculated parameters to exptl. determined activity values.By the quant. structure activity relationship (QSAR) model developed here, it is possible to predict the activity of a potent drug before its synthesis since only theor. determined mol. parameters are used for the prediction.