title: Computational drug repositioning for peripheral arterial disease: prediction of anti-inflammatory and pro-angiogenic therapeutics.
abstract: Peripheral arterial disease (PAD) results from atherosclerosis that leads to blocked arteries and reduced blood flow, most commonly in the arteries of the legs. PAD clinical trials to induce angiogenesis to improve blood flow conducted in the last decade have not succeeded. We have recently constructed PADPIN, protein-protein interaction network (PIN) of PAD, and here we combine it with the drug-target relations to identify potential drug targets for PAD. Specifically, the proteins in the PADPIN were classified as belonging to the angiome, immunome, and arteriome, characterizing the processes of angiogenesis, immune response/inflammation, and arteriogenesis, respectively. Using the network-based approach we predict the candidate drugs for repositioning that have potential applications to PAD. By compiling the drug information in two drug databases DrugBank and PharmGKB, we predict FDA-approved drugs whose targets are the proteins annotated as anti-angiogenic and pro-inflammatory, respectively. Examples of pro-angiogenic drugs are carvedilol and urokinase. Examples of anti-inflammatory drugs are ACE inhibitors and maraviroc. This is the first computational drug repositioning study for PAD.
authors.affiliation: Department of Biomedical Engineering, School of Medicine, Johns Hopkins University Baltimore, MD, USA.
authors.forename: Liang-Hui
authors.initials: LH
authors.lastname: Chu
authors.affiliation: Division of Cardiovascular Medicine, Department of Medicine and Robert M. Berne Cardiovascular Research Center, University of Virginia School of Medicine Charlottesville, VA, USA.
authors.forename: Brian H
authors.initials: BH
authors.lastname: Annex
authors.affiliation: Department of Biomedical Engineering, School of Medicine, Johns Hopkins University Baltimore, MD, USA.
authors.forename: Aleksander S
authors.initials: AS
authors.lastname: Popel
keywords: angiogenesis; bioinformatics; cardiovascular disease; computational drug repositioning; drug-target network; inflammation; peripheral arterial disease