Abstract
Biocomputational network approaches are being successfully applied to predict and extract previously unknown information of novel molecular components of biological systems. In the present work, we have used this approach to predict new potential targets of anti-angiogenic therapies. For experimental validation of predictions, we made use of two in vitro assays related to two key steps of the angiogenic process, namely, endothelial cell migration and formation of “tubular-like” structures on Matrigel. From 7 predicted candidates, experimental tests clearly show that superoxide dismutase 3 silencing or blocking with specific antibodies inhibit both key steps of angiogenesis. This experimental validation was further confirmed with additional in vitro assays showing that superoxide dismutase 3 blocking produces inhibitory effects on the capacity of endothelial cells to form “tubular-like” structure within type I collagen matrix, to adhere to elastin-coated plates and to invade a Matrigel layer. Furthermore, angiogenesis was also inhibited in the en vivo aortic ring assay and in the in vivo mouse Matrigel plug assay. Therefore, superoxide dismutase 3 is confirmed as a putative target for anti-angiogenic therapy.
Highlights
An important goal in the field of protein interactions is to recognise interactions that are involved in disease genesis and progression
From 7 predicted candidates, experimental tests clearly show that superoxide dismutase 3 silencing or blocking with specific antibodies inhibit both key steps of angiogenesis
These top ranked proteins were filtered by an expert manual curation based on available literature and biological databases in order to confirm their novelty as angiogenic proteins
Summary
An important goal in the field of protein interactions is to recognise interactions that are involved in disease genesis and progression. In spite of the efforts devoted to elucidate interactomes in the last decades, surprisingly only about 10% of human protein-protein interactions (PPIs) are experimentally known, about one-third of human proteins have no known interactions, and more than half of all identified human protein-coding genes have no experimental evidence of their function [1, 2]. The exploration of these unknown areas of proteins functionality has been enhanced with the emergence of new high-throughput techniques. The arduous task, the cost and the risk involved in the study of new targets in many cases deter researchers to initiate such investigations
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