Abstract

Schizophrenia is a neuropsychiatric disorder that is caused by many factors including changes in the chemistry of the brain, structure of the brain, and genetic factors. The neuropathology of the disorder has been identified morphologically and physiologically through a number of parameters from a reduction in brain size and abnormalities in the neurotransmitter network affecting the brain to changes in the molecular composition of specific cell populations in the brain. Over a long period of time, clinicians and researchers have identified schizophrenia as a complex neurological genetic disorder as a result of the functionality of several susceptible genes. Various scientists are of the opinion that there are about 20 candidate genes that cause schizophrenia. Several genes like Dysbindin, Neuregulin, DAAO, G72, PRODH, COMT, and RGS4 have been proven to be the risk factors for schizophrenia disease. RGS4 was identified as a target gene for schizophrenia. Hence the present study was taken up to identify a Novel Drug/Lead Molecule from 12 selected drugs based on a bioinformatics approach for schizophrenia targeting the RGS4 gene. The genomics and proteomics approach of the RGS4 gene was carried out for nucleotide and protein sequences and the protein was modeled using SPDBV with 80% accuracy. The potential active site amino acids were predicted using molecular cavities based on energy and surface area and the protein was targeted using the best active site amino acids. The protein-ligand interactions were also performed using the Argus Lab engine with flexible docking. The data of the present study reveals that ziprasidone is showing maximum inhibition of the RGS4 gene among the 12 drugs selected for screening. It is thus concluded that ziprasidone with the lowest free energy and high affinity is the best inhibitor for the schizophrenia protein and hence it can be suggested for the treatment of schizophrenia.

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