title: Structural, phylogenetic and docking studies of D-amino acid oxidase activator (DAOA), a candidate schizophrenia gene.
abstract: BACKGROUND
  Schizophrenia is a neurodegenerative disorder that occurs worldwide and can be difficult to diagnose. It is the foremost neurological disorder leading to suicide among patients in both developed and underdeveloped countries. D-amino acid oxidase activator (DAOA), also known as G72, is directly implicated in the glutamateric hypothesis of schizophrenia. It activates D-amino acid oxidase, which oxidizes D-serine, leading to modulation of the N-methyl-D-aspartate receptor.
  
  
  METHODS
  MODELLER (9v10) was utilized to generate three dimensional structures of the DAOA candidate gene. The HOPE server was used for mutational analysis. The Molecular Evolutionary Genetics Analysis (MEGA5) tool was utilized to reconstruct the evolutionary history of the candidate gene DAOA. AutoDock was used for protein-ligand docking and Gramm-X and PatchDock for protein-protein docking.
  
  
  RESULTS
  A suitable template (1ZCA) was selected by employing BLASTp on the basis of 33% query coverage, 27% identity and E-value 4.9. The Rampage evaluation tool showed 91.1% favored region, 4.9% allowed region and 4.1% outlier region in DAOA. ERRAT demonstrated that the predicted model had a 50.909% quality factor. Mutational analysis of DAOA revealed significant effects on hydrogen bonding and correct folding of the DAOA protein, which in turn affect protein conformation. Ciona was inferred as the outgroup. Tetrapods were in their appropriate clusters with bifurcations. Human amino acid sequences are conserved, with chimpanzee and gorilla showing more than 80% homology and bootstrap value based on 1000 replications. Molecular docking analysis was employed to elucidate the binding mode of the reported ligand complex for DAOA. The docking experiment demonstrated that DAOA is involved in major amino acid interactions: the residues that interact most strongly with the ligand C28H28N3O5PS2 are polar but uncharged (Gln36, Asn38, Thr 122) and non-polar hydrophobic (Ile119, Ser171, Ser21, Ala31). Protein-protein docking simulation demonstrated two ionic bonds and one hydrogen bond involving DAOA. Lys-7 of the receptor protein interacted with Lys-163 and Asp-2037. Tyr-03 interacted with Arg-286 of the ligand protein and formed a hydrogen bond.
  
  
  CONCLUSIONS
  The predicted interactions might serve to inhibit the disease-related allele. It is assumed that current bioinformatics methods will contribute significantly to identifying, analyzing and curing schizophrenia. There is an urgent need to develop effective drugs for schizophrenia, and tools for examining candidate genes more accurately and efficiently are required.
authors.affiliation: Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan.
authors.forename: Sheikh Arslan
authors.initials: SA
authors.lastname: Sehgal
authors.forename: Naureen Aslam
authors.initials: NA
authors.lastname: Khattak
authors.forename: Asif
authors.initials: A
authors.lastname: Mir
mesh_terms: D002352:Carrier Proteins / Q000235:genetics*; D020536:Enzyme Activators / Q000737:chemistry / Q000494:pharmacology*; D006801:Humans; D047908:Intracellular Signaling Peptides and Proteins; D008958:Models, Molecular; D015394:Molecular Structure; D010802:Phylogeny; D011485:Protein Binding; D012559:Schizophrenia / Q000235:genetics*
chemical_list: D002352:Carrier Proteins; C475071:DAOA protein, human; D020536:Enzyme Activators; D047908:Intracellular Signaling Peptides and Proteins