Identification of new target proteins of a Urotensin-II receptor antagonist using transcriptome-based drug repositioning approach

Jae Yong Ryu,Byung Ho Lee,Jeong Hyun Lee,Chae Jo Lim,Kwang-Seok Oh,Gyutae Lim

doi:10.1038/s41598-021-96612-0

Abstract

Drug repositioning research using transcriptome data has recently attracted attention. In this study, we attempted to identify new target proteins of the urotensin-II receptor antagonist, KR-37524 (4-(3-bromo-4-(piperidin-4-yloxy)benzyl)-N-(3-(dimethylamino)phenyl)piperazine-1-carboxamide dihydrochloride), using a transcriptome-based drug repositioning approach. To do this, we obtained KR-37524-induced gene expression profile changes in four cell lines (A375, A549, MCF7, and PC3), and compared them with the approved drug-induced gene expression profile changes available in the LINCS L1000 database to identify approved drugs with similar gene expression profile changes. Here, the similarity between the two gene expression profile changes was calculated using the connectivity score. We then selected proteins that are known targets of the top three approved drugs with the highest connectivity score in each cell line (12 drugs in total) as potential targets of KR-37524. Seven potential target proteins were experimentally confirmed using an in vitro binding assay. Through this analysis, we identified that neurologically regulated serotonin transporter proteins are new target proteins of KR-37524. These results indicate that the transcriptome-based drug repositioning approach can be used to identify new target proteins of a given compound, and we provide a standalone software developed in this study that will serve as a useful tool for drug repositioning.

Highlights

Novel drug development is still a time-consuming and expensive t ask[1,2] because it is difficult to predict side effects or toxicity in a dvance[3]
KR-37524 is an analogue of the piperazine-carboxamide family and these analogs exhibit various biological activities such as platelet-derived growth factor receptor (PDGFR) inhibitors[26], monoacylglycerol lipase (MAGL) inhibitor[27], serotonin (5-HT1B) receptor a ntagonists[28], chemokine receptor (CCR) antagonists[29,30] or fatty acid amide hydrolase (FAAH) inhibitors[31,32,33]
We compared the gene expression profile changes induced by KR-37524 in each cell line to the approved drug-induced gene expression profile changes provided in the Library of Integrated Network-based Cellular Signatures (LINCS) L1000 database and found approved drugs with similar gene expression profile changes

Summary

Introduction

Novel drug development is still a time-consuming and expensive t ask[1,2] because it is difficult to predict side effects or toxicity in a dvance[3]. Since approved drugs have already passed the verification of in vivo toxicity and side effects through clinical trials, drug repositioning or repurposing approaches can find potential new target proteins and improve drug usability[5,6] This is more efficient and easier than the development of an entirely new d rug[7,8]. Various computational drug repositioning methods have been developed using transcriptome data to identify potential new target proteins for drugs, such as comparing gene expression profile changes between disease models and drug treatment conditions[9,10], prediction of drug-protein interactions[11,12,13], and network integration[14,15]. We provide standalone software used in the current study to generalize our strategy (i.e., transcriptome-based drug repositioning)

Methods

Results

Discussion

Conclusion