Abstract
We introduce a systematic computational methodology based on bioinformatics that has enabled us to identify and classify >120 endogenous peptide inhibitors of endothelial cell proliferation and migration. These peptides are derived from members of the type IV collagen, thrombospondin, and CXC chemokine protein families, as well as somatotropin hormones, serpins, and various kringle-containing proteins. Their activity in suppressing the proliferation and migration of endothelial cells in vitro provides proof of principle for the validity of this computational method. Interestingly, some of the peptides are derived from proteins known to be proangiogenic. By performing receptor neutralization studies, we have identified receptors to which these peptides bind. On the basis of this receptor-binding information, we evaluated several examples of peptide-based combinatorial screening strategies. In some cases, this combinatorial screening identified strong synergism between peptides. The current work provides a guideline for a computational-based peptidomics approach for the discovery of endogenous bioactive peptides.