The nature of a human medical disorder is often elucidated through biological markers and behavioral studies. Diagnosis of mental disorders is very difficult because it primarily relies on behavioral markers. An example of a complex mental disorder is schizophrenia (SZ), diagnosis of which depends on abnormal behavior such as paranoia, dampening of emotions and auditory hallucinations. Genome-wide studies have attained a major role in SZ research because high-throughput technologies are valuable for discovering relevant genes. SZ is a psychiatric disorder with severe manifestations - abnormal behavior, disorganized speech and figments of the imagination - and an estimated heritability of about 80%. Negative symptoms can also include affective flattening, avolition, and alogia. Approximately 1% of the population is affected during the course of life. The effects of SZ usually start during the patient’s late teens to early twenties; females have an age of onset five years later than males. A recent meta-data analysis estimated the risk of SZ in males to be about 40% higher than in females. Epidemiological studies of SZ have shown that it occurs in all populations with a prevalence of approximately 1.5-4.5 per thousand and an incidence of 0.17-0.43 per thousand.
According to analysis of gene linkage data and meta-analysis of genome scans, highly vulnerable genes on chromosomes 1q, 3p, 5q, 6p, 8p, 11q, 14p, 20q and 22q[6, 7] contribute to SZ. Both functional and positional candidate SZ genes have been studied and various promising candidates that might be involved in risk for the disease have been identified.
The symptoms of SZ have different dimensions that usually occur together and can reflect substantial variation among patient phenotypes[8–10]. Different researchers have formulated various models of these dimensions but the most widely appreciated 3D models were first proposed by Bilder et al. and Liddle[9, 11]. These authors concluded that the main symptoms are poverty of speech, formal thought disorder, decreased voluntary movement, psychomotor impairment, bizarre behavior, hallucinations, abnormal acts, inappropriate affects, flat affects, flattening, avolition, and alogia.
A genome-wide association study (GWAS) for SZ was conducted in 2008 but no significant loci were reported, though 7000 samples were used[12, 13].
The gene DAOA, located on chromosome 13q3, encodes the D-amino acid oxidase activator protein, as shown by functional and expression studies. It is significantly associated with SZ and is also known as G72. The D-amino acid oxidase activator (DAOA) is directly implicated in the glutamateric hypothesis of SZ. When D-amino acid oxidase is activated, D-serine is oxidized and the product modulates the N-methyl-D-aspartate receptor. Modulation of this receptor leads to the cause of SZ; glutamate signaling is involved in important pathways directly linked to SZ.
DAOA is also involved in other psychotic disorders and can modify the cognitive and negative symptoms of mood. It could be the primary genetic cause of the observed overlap of phenotypes between bipolar disorder and SZ.
Bioinformatics has been used for in silico analysis of biological queries using mathematical and statistical techniques. X-ray and NMR techniques are expensive and time-consuming for structural modeling of proteins. Screening of small chemical compounds against target receptors by high throughput screening (HTS) is very expensive.
In this work, we predicted the 3D structure and the protein-ligand and protein-protein docking of DAOA using different bioinformatics strategies. The main aim of our research was to predict the 3D structure and docking. The objective of the present study was to elucidate the interactions of DAOA protein with ligands and other proteins and to identify the connection of DAOA to SZ. Protein-protein docking and interaction simulations reveal hydrogen and ionic bonds. The present work was conducted to provide molecular insights into the structure of the protein and to find its most plausible function.