A conditional probability solution strategy for the in silico identification of the NMDA and metabotropic glutamate receptor subtype 5 targeted by a conantokin GGX1X1SAX1X1LTX5 peptide mimo-formula as an advanced promising antipsychotic potentiator

Glutamate is the primary excitatory neurotransmitter in the mammalian central nervous system (CNS) and activates metabotropic glutamate receptors (mGluRs), which are coupled to downstream effector systems through guanine nucleotide binding proteins (G proteins). The mGluRs provide a mechanism by which glutamate can modulate or fine-tune activity at the same synapses on which it elicits fast synaptic responses. Because of the wide diversity, heterogeneous distribution, and diverse physiological roles of mGluR subtypes, the opportunity exists for developing therapeutic agents that selectively interact with mGluRs involved in only one or a limited number of CNS functions. Such drugs could have a dramatic impact on the development of novel treatment strategies for a variety of psychiatric disorders including depression, anxiety disorders, schizophrenia and Parkinson's disease. The mGluR5 receptor subtype is a closely associated signaling partner of the ionotropic NMDA receptor (NMDAR) and may play a significant role in setting the tone of NMDAR function in the forebrain regions containing neuronal circuits important for cognitive behavior and for reporting on the efficacy of antipsychotic agents. The conantokins are structurally unique. It has been established that the conantokins have N-methyl-D-aspartate (NMDA) antagonist activity, and consequently target the NMDA receptor. In this study we performed a systematic analysis, with the classic kinetic models of enzyme-substrate-inhibitor interactions with different number of substrates, different reaction mechanisms, and different types or mechanisms of inhibition by modeling this situation through Monte Carlo error propagation, in which a distribution of free energy estimates is constructed by repeatedly evaluating the free energy after perturbing the microstate energies according to probability density functions describing their inherent imprecision resulting in the generation of a multi-conserved pharmaco-scaffold consisting of five key active pharmacophores peptide mimicking to the NMDA and Glutamate Receptor Subtype 5 conantokin activated pathway. Here, finally we provided for the first time a conditional probability solution computer-aided molecular strategy for the in silico identification of the ionotropic NMDA receptor and Metabotropic Glutamate Receptor Subtype 5 conantokin X6GQDDSX1X1X1DSQX2VMX2HGQRRERR peptidomimetic formula as an advanced binding site promising future drug potentiator.