1. Academic Validation
  2. Quantitative and systems pharmacology 4. Network-based analysis of drug pleiotropy on coronary artery disease

Quantitative and systems pharmacology 4. Network-based analysis of drug pleiotropy on coronary artery disease

  • Eur J Med Chem. 2019 Jan 1:161:192-204. doi: 10.1016/j.ejmech.2018.10.020.
Jiansong Fang 1 Chuipu Cai 1 Yanting Chai 1 Jingwei Zhou 1 Yujie Huang 1 Li Gao 2 Qi Wang 1 Feixiong Cheng 3
Affiliations

Affiliations

  • 1 Institute of Clinical Pharmacology, Guangzhou University of Chinese Medicine, Guangzhou 510405, China.
  • 2 Modern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China.
  • 3 Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA; CASE Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA. Electronic address: chengf@ccf.org.
Abstract

Despite recent advance of therapeutic development, coronary artery disease (CAD) remains one of the major issues to public health. The use of genomics and systems biology approaches to inform drug discovery and development have offered the possibilities for new target identification and in silico drug repurposing. In this study, we propose a network-based, systems pharmacology framework for target identification and drug repurposing in pharmacologic treatment and chemoprevention of CAD. Specifically, we build in silico models by integrating known drug-target interactions, CAD genes derived from the genetic and genomic studies, and the human protein-protein interactome. We demonstrate that the proposed in silico models can successfully uncover approved drugs and novel Natural Products in potentially treating and preventing CAD. In case studies, we highlight several approved drugs (e.g., fasudil, parecoxib, and dexamethasone) or Natural Products (e.g., resveratrol, luteolin, daidzein and caffeic acid) with new mechanism-of-action in chemical intervention of CAD by network analysis. In summary, this study offers a powerful systems pharmacology approach for target identification and in silico drug repurposing on CAD.

Keywords

Coronary artery disease; Drug repurposing; Drug-target network; Genomics; Natural product; Protein-protein interaction; Systems pharmacology.

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