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Research Paper|Volume 11, Issue 24|pp 12428—12451

System level characterization of small molecule drugs and their affected long noncoding RNAs

Haixiu Yang1, Yanan Jiang2,3, Yunpeng Zhang1, Yanjun Xu1, Chunlong Zhang1, Junwei Han1, Fei Su1, Xiaoqi Liu4, Kai Mi1, Bing Liu2,3, Desi Shang1
  • 1College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
  • 2Translational Medicine Research and Cooperation Center of Northern China, Heilongjiang Academy of Medical Sciences, Harbin 150081, Heilongjiang, China
  • 3Department of Pharmacology (State-Province Key Laboratories of Biomedicine-Pharmaceutics of China, Key Laboratory of Cardiovascular Research, Ministry of Education), College of Pharmacy, Harbin Medical University, Harbin 150081, Heilongjiang, China
  • 4Department of Orthopedic Surgery, The Second Affiliated Hospital, Harbin Medical University, Harbin 150001, China
* Equal contribution
Received: July 8, 2019Accepted: November 26, 2019Published: December 18, 2019
https://doi.org/10.18632/aging.102581

Copyright © 2019 Yang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Long noncoding RNAs (lncRNAs) have multiple regulatory roles and are involved in many human diseases. A potential therapeutic strategy based on targeting lncRNAs was recently developed. To gain insight into the global relationship between small molecule drugs and their affected lncRNAs, we constructed a small molecule lncRNA network consisting of 1206 nodes (1033 drugs and 173 lncRNAs) and 4770 drug-lncRNA associations using LNCmap, which reannotated the microarray data from the Connectivity Map (CMap) database. Based on network biology, we found that the connected drug pairs tended to share the same targets, indications, and side effects. In addition, the connected drug pairs tended to have a similar structure. By inferring the functions of lncRNAs through their co-expressing mRNAs, we found that lncRNA functions related to the modular interface were associated with the mode of action or side effects of the corresponding connected drugs, suggesting that lncRNAs may directly/indirectly participate in specific biological processes after drug administration. Finally, we investigated the tissue-specificity of drug-affected lncRNAs and found that some kinds of drugs tended to have a broader influence (e.g. antineoplastic and immunomodulating drugs), whereas some tissue-specific lncRNAs (nervous system) tended to be affected by multiple types of drugs.