Background: Vascular endothelial growth factor (VEGF) is an endothelial cell-specific angiogenic and vasculogenic mitogen. VEGF also plays a role in pathogenic vascularization which is associated with a number of clinical disorders, including cancer and rheumatoid arthritis. The development of VEGF antagonists, which prevent the interaction of VEGF with its receptor, may be important for the treatment of such disorders. VEGF is a homodimeric member of the cystine knot growth factor superfamily, showing greatest similarity to platelet-derived growth factor (PDGF). VEGF binds to two different tyrosine kinase receptors, kinase domain receptor (KDR) and Fms-like tyrosine kinase 1 (Flt-1), and a number of VEGF homologs are known with distinct patterns of specificity for these same receptors. The structure of VEGF will help define the location of the receptor-binding site, and shed light on the differences in specificity and cross-reactivity among the VEGF homologs.
Results: We have determined the crystal structure of the receptor-binding domain of VEGF at 1.93 A resolution in a triclinic space group containing eight monomers in the asymmetric unit. Superposition of the eight copies of VEGF shows that the beta-sheet core regions of the monomers are very similar, with slightly greater differences in most loop regions. For one loop, the different copies represent different snapshots of a concerted motion. Mutagenesis mapping shows that this loop is part of the receptor-binding site of VEGF.
Conclusions: A comparison of the eight independent copies of VEGF in the asymmetric unit indicates the conformational space sampled by the protein in solution; the root mean square differences observed are similar to those seen in ensembles of the highest precision NMR structures. Mapping the receptor-binding determinants on a multiple sequence alignment of VEGF homologs, suggests the differences in specificity towards KDR and Flt-1 may derive from both sequence variation and changes in the flexibility of binding loops. The structure can also be used to predict possible receptor-binding determinants for related cystine knot growth factors, such as PDGF.