Computational analysis has become an indispensable bioinformatics approaches for the characterization of proteins regarding the physicochemical properties, prediction of signal peptides and 3D structure. Additionally, computational studies of protein-ligand interactions provide a rational basis for the speedy identification of novel leads for drug. To date no any computational analysis evaluating such parameters for GM-CSF-Rα, IL-3-Rα and IL-5-Rα. Hence, the present work aimed at identifying the theoretical basis of the physicochemical, structural and functional proprieties for these proteins using online computational tools. In the present study, different bioinformatics tools were used to characterize the properties and structure of the GM-CSF-Rα, IL3Rα, and IL5Rα proteins. Firstly, the Physico-chemical characterization was computed by ExPasy's (ProtParam). Then Fingerprinting analysis was done with ScanProsite. Followed by the functional characterization of the transmembrane regions and phosphorylation sites using SOSUI server and NetPhos server respectively. Afterwards, secondary structure prediction and the protein-ligand binding site residues were predicted by PDBSUM, and the detected ligands and their interactions were visualized by LIGPLOT and Protein ligand interaction profiler (PILP) softwares. The residues in GM-CSF-Rα, IL-3Rα and IL-5Rα proteins that may undergo ubiquitination were detected by using the UbPred and BDM-PUB programs, the predicted peptides for sumoylation in GM-CSF-Rα, IL-3Rα and IL-5Rα proteins were detected by GPS-SUMO online service. Finally, the 3D structure of proteins was built by Chimera 1.8 program. In addition, the models were surveyed using ERRAT server; as a confirmation for the quality of the models. Our results revealed that GM-CSF-Rα is stable whereas the IL3Rα and IL5Rα are classified as unstable proteins. All proteins are membrane proteins, acidic and hydrophilic in nature, with serine being the most phosphorylated amino acid. Interestingly, fibronectin type-III (FN3) domain was detected among these proteins. Also, we detected the sequences belonging to the following families: HEMATOPO_REC_S_F2, ASN_GLYCOSYLATION, CK2_PHOSPHO_SITE, PKC_PHOSPHO_SITE, MYRISTYL, CAMP_PHOSPHO_SITE, and TYR_PHOSPHO. Moreover, we detected 9 kinases in GM-CSF-Rα, while 13 kinases in IL-3-Rα and 15 kinases in IL-5-Rα. In GM-CSF-Rα 3 binding sites were detected with two ligands (GOL and NAG), and 5 binding sites in IL-3-Rα and IL-5-Rα with 3ligands (NAG, FUL and BMA) and one ligand (BGC) respectively. Secondary structure prediction showed that Beta sheet dominated all the other conformations. Modeling the 3 D structure of proteins resulted in a quality of less than 90%. computational analysis of GM-CSF-Rα, IL-3-Rα and IL-5-Rα will give a deep insight and provide opportunities for understanding the function of these proteins, and developing novel therapeutics for treating certain leukemia and inflammatory diseases.
