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.

A public–private collaboration model for clinical innovation

“… Brian Annex, MD , was the principal investigator on an award made to University of Virginia to test an AstraZeneca drug (ZD5054 link to: ncats.nih.gov/files/ZD5054.pdf) in patients with peripheral artery disease. The trial used imaging as a noninvasive method to measure calf blood flow at rest and during exercise was used as a more objective and quantitatively reproducible POC end point compared to the traditionally used subjective and effort‐dependent 6‐min walk test measuring the distance traveled over a 6‐min period 14 . This was also shown to decrease POC study size and duration, thus, improving the likelihood of more frequent testing of novel agents (previously limited by study expense, subjectivity, and outcome variability) for this indication in the future. John Krystal, MD (link to: https://reporter.nih.gov/search/B9Xu1HDwMUKpl1maeyaAPg/project‐details/8913287) was the principal investigator on an award made to Yale University to test a Pfizer drug (PF‐03463275: link to ncats.nih.gov/files/PF‐03463275.pdf) in patients with schizophrenia.…”

Systems biology of angiogenesis signaling: Computational models and omics

“…By combining PADPIN with gene expression data collected from ischemic and nonischemic gastrocnemius muscles from two mouse strains (C57BL/6 and BALB/c) subjected to hindlimb ischemia (a commonly used experimental PAD mouse model), the authors identified a list of genes with potential therapeutic significance in PAD and demonstrated the feasibility of using such an omics‐based in silico platform for PAD research. Later, PADPIN was also combined with extensive drug‐target relationships derived from public drug databases to facilitate the identification of potential drug repositioning candidates for PAD from the aspect of promoting angiogenesis and alleviating inflammation (Chu, Annex, & Popel, 2015).…”

The application of proteomics in the diagnosis and treatment of bronchial asthma

“…Only a limited number of genes are activated, and large amounts of proteins and peptides are produced after the transcription, translation, and post-translational modifications of these genes. The body has a complex protein network, which ensures that every cell, tissue, and organ achieves its biological function by adhering to the physiological laws (9,10). Therefore, proteomic analysis is an important part of modern bioinformatics.…”