Computational Characterization of Human Vascular Endothelial Growth Factor Proteins

We present an in silico learning method to discriminate the pathologically important vascular endothelial growth factor (VEGF) protein through proteomic tools. Prima ry structure analysis showed most of the VEGF human proteins are rich in hydrophilic residues. The average molecular weight of VEGF human proteins calculated as 76244 Dalton. Grand Average hydropathy (GRAVY) index of all the VEGF human proteins are ranging from -0.2 to 0.1 except the protein 014495 which has comparatively high GRAVY value. Antigenic sites for all the proteins are recognized as C, Y, L, V, P, and K residues-EMBOSS antigenic program. The computed pT value indicates that most of the proteins are basic (pI>7) in nature. SOPM and SOPMA program shows that all the VEGF human proteins are different in secondary structural content. The presence of disulfide bridges are identified by CYS_REC tool, also visualized through 3D structure. The SOSUI server classifies the proteins P15692, P49765 and 043915 as soluble proteins and other proteins as transmembrane proteins. The projected technique provides more accurate information about 3D structure, geometry, cystines involved in the disulfide bond. It would provide biological insights about protein hubs and their roles in interaction networks.