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Adaptive evolution and elucidating the potential inhibitor against schizophrenia to target DAOA (G72) isoforms

Authors Sehgal SA, Mannan S, Kanwal S, Naveed I, Mir A

Received 12 March 2014

Accepted for publication 29 April 2014

Published 3 July 2015 Volume 2015:9 Pages 3471—3480


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Sheikh Arslan Sehgal,1,2 Shazia Mannan,2,* Sumaira Kanwal,2,* Ishrat Naveed,1 Asif Mir1

1Department of Bioinformatics and Biotechnology, International Islamic University, Islamabad, Pakistan; 2Department of Biosciences, COMSATS Institute of Information Technology, Sahiwal, Pakistan

*These authors contributed equally to this work

Abstract: Schizophrenia (SZ), a chronic mental and heritable disorder characterized by neurophysiological impairment and neuropsychological abnormalities, is strongly associated with d-amino acid oxidase activator (DAOA, G72). Research studies emphasized that overexpression of DAOA may be responsible for improper functioning of neurotransmitters, resulting in neurological disorders like SZ. In the present study, a hybrid approach of comparative modeling and molecular docking followed by inhibitor identification and structure modeling was employed. Screening was performed by two-dimensional similarity search against selected inhibitor, keeping in view the physiochemical properties of the inhibitor. Here, we report an inhibitor compound which showed maximum binding affinity against four selected isoforms of DAOA. Docking studies revealed that Glu-53, Thr-54, Lys-58, Val-85, Ser-86, Tyr-87, Leu-88, Glu-90, Leu-95, Val-98, Ser-100, Glu-112, Tyr-116, Lys-120, Asp-121, and Arg-122 are critical residues for receptor–ligand interaction. The C-terminal of selected isoforms is conserved, and binding was observed on the conserved region of isoforms. We propose that selected inhibitor might be more potent on the basis of binding energy values. Further analysis of this inhibitor through site-directed mutagenesis could be helpful for exploring the details of ligand-binding pockets. Overall, the findings of this study may be helpful in designing novel therapeutic targets to cure SZ.

Keywords: schizophrenia, bioinformatics, modeling, docking, DAOA, G72, DAO, computer-aided drug designing, phylogenetic analysis, d-amino acid oxidase activator

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