Identificationof GPR15as novel suggested co-receptor forbinding of IZUMO(sperm-egg fusion protein) receptor to JUNOby integrating system biology, modeling and molecular docking

Document Type : Full Research Paper

Authors

1 Department of Basic Sciences, Faculty of Veterinary Medicine, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

2 Department of Anatomy, School of Medicine, Tehran University of medical sciences, Tehran, Iran.

3 Laboratory animal reproduction lab, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREO), Karaj, Iran.

Abstract

Introduction: For fertilization process, sperm cell-surface protein called "IZUMO” requiredas a ligand for IZUMO1R/JUNO and CD9 receptor on egg. The IZUMO1:IZUMO1R/JUNO interaction is a crucial adhesion step between sperm and oocytein plasma membrane binding and fusion, but also is not sufficient for cell fusion and others receptors are play roles in this interaction. Here, we found G protein-coupled receptor 15 (GPR15) as another partner of sperm-egg interaction which is located on egg. Methods: Initially,system biology methods applied for known and predicted protein-protein network interactions of IZUMO1. Also, primary structure of IZUMO1 and its IZUMO1R:JUNO receptors retrieved from reference databases, and their 3-dimensional structure (3D) were modeled by both Threading and homology modeling. Then, modeled structure were energetically minimized and validated by Rammapageplots and eventually prepared for molecular docking (hydrogen and atomic charges) by Chimera UCSF 1.10. Also, the docking studies were performed by HEX version 8. Finally, binding energy, pose of interactions,RMSD, hydrogen and electrostatics bonds were analyzed. Results: System biology analysis showed that beside IZUMO1R/JUNO and CD9 ,GPR15 maybe is another functional partner for IZUMO1 by score of 0.705 (text mining approach). Also, Rammachandran plot of modeled structures represent high quality of modeling procedure and so modeled structure used for docking. Molecular docking analysis showed GPR15 could interact with IZUMO by SER176,THR91, ARG236 and SER240, ASN239and ASN151hydrogens. The strongest hydrogen bond is between thoronine 91 (THR91) and serine 240 (SER240). On the other hand, amino acids Threonine 91 and ASN239 are the most important amino acids for binding to hydrogen bonding two proteins to each other and react simultaneously with two amino acids. Also, 21 amino acids from IZUMO1 and GRP15 play a role in the hydrophobic bond between two proteins. Discussion: The results of this bioinformatics study can help to find out more about fertility and Sperm fertilization. Further studies on the role of GPR15 in the binding of sperm and oocyte should also be made.

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1. Hindumathi V, Kranthi T, Rao SB, Manimaran P. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach. Molecular BioSystems. 2014;10(6):1450-60.
2. Toshimori K. Dynamics of the mammalian sperm head: modifications and maturation events from spermatogenesis to egg activation. Advances in anatomy, embryology, and cell biology. 2009;204:5-94.
3. Liu H, Beck TN, Golemis EA, Serebriiskii IG. Integrating In Silico Resources to Map a Signaling Network. In: Ochs MF, editor. Gene Function Analysis. Totowa, NJ: Humana Press; 2014. p. 197-245.
4. Wu J, Vallenius T, Ovaska K, Westermarck J, Mäkelä TP, Hautaniemi S. Integrated network analysis platform for protein-protein interactions. Nature Methods. 2008;6:75.
5. Rolland T, Tasan M, Charloteaux B, Pevzner SJ, Zhong Q, Sahni N, et al. A proteome-scale map of the human interactome network. Cell. 2014;159(5):1212-26.
6. Bapat SA, Krishnan A, Ghanate AD, Kusumbe AP, Kalra RS. Gene expression: protein interaction systems network modeling identifies transformation-associated molecules and pathways in ovarian cancer. Cancer research. 2010;70(12):4809-19.
7. Li M, Wu X, Wang J, Pan Y. Towards the identification of protein complexes and functional modules by integrating PPI network and gene expression data. BMC bioinformatics. 2012;13:109.
8. Pedamallu CS, Ozdamar L, editors. A Review on Protein-Protein Interaction Network Databases2014; Cham: Springer International Publishing.