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Biomedicines
Volume 8
Issue 9
10.3390/biomedicines8090320
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Article

Investigating Core Signaling Pathways of Hepatitis B Virus Pathogenesis for Biomarkers Identification and Drug Discovery via Systems Biology and Deep Learning Method

by
Shen Chang
1,
Lily Hui-Ching Wang
2 and
Bor-Sen Chen
1,*
1
Laboratory of Automatic Control, Signal Processing and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan
2
Institute of Molecular and Cellular Biology, National Tsing Hua University, Hsinchu 30013, Taiwan
*
Author to whom correspondence should be addressed.
Biomedicines 2020, 8(9), 320; https://doi.org/10.3390/biomedicines8090320
Received: 6 July 2020 / Revised: 19 August 2020 / Accepted: 21 August 2020 / Published: 31 August 2020
(This article belongs to the Section Drug Discovery and Development)
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Abstract

Hepatitis B Virus (HBV) infection is a major cause of morbidity and mortality worldwide. However, poor understanding of its pathogenesis often gives rise to intractable immune escape and prognosis recurrence. Thus, a valid systematic approach based on big data mining and genome-wide RNA-seq data is imperative to further investigate the pathogenetic mechanism and identify biomarkers for drug design. In this study, systems biology method was applied to trim false positives from the host/pathogen genetic and epigenetic interaction network (HPI-GEN) under HBV infection by two-side RNA-seq data. Then, via the principal network projection (PNP) approach and the annotation of KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, significant biomarkers related to cellular dysfunctions were identified from the core cross-talk signaling pathways as drug targets. Further, based on the pre-trained deep learning-based drug-target interaction (DTI) model and the validated pharmacological properties from databases, i.e., drug regulation ability, toxicity, and sensitivity, a combination of promising multi-target drugs was designed as a multiple-molecule drug to create more possibility for the treatment of HBV infection. Therefore, with the proposed systems medicine discovery and repositioning procedure, we not only shed light on the etiologic mechanism during HBV infection but also efficiently provided a potential drug combination for therapeutic treatment of Hepatitis B. View Full-Text
Keywords: hepatitis B virus infection; pathogenesis; host/pathogen interspecies genetic and epigenetic network (HPI-GEN); systems medicine discovery; drug-target interaction (DTI) model; deep learning; multiple-molecule drug hepatitis B virus infection; pathogenesis; host/pathogen interspecies genetic and epigenetic network (HPI-GEN); systems medicine discovery; drug-target interaction (DTI) model; deep learning; multiple-molecule drug
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MDPI and ACS Style

Chang, S.; Wang, L.H.-C.; Chen, B.-S. Investigating Core Signaling Pathways of Hepatitis B Virus Pathogenesis for Biomarkers Identification and Drug Discovery via Systems Biology and Deep Learning Method. Biomedicines 2020, 8, 320. https://doi.org/10.3390/biomedicines8090320

AMA Style

Chang S, Wang LH-C, Chen B-S. Investigating Core Signaling Pathways of Hepatitis B Virus Pathogenesis for Biomarkers Identification and Drug Discovery via Systems Biology and Deep Learning Method. Biomedicines. 2020; 8(9):320. https://doi.org/10.3390/biomedicines8090320

Chicago/Turabian Style

Chang, Shen, Lily H.-C. Wang, and Bor-Sen Chen. 2020. "Investigating Core Signaling Pathways of Hepatitis B Virus Pathogenesis for Biomarkers Identification and Drug Discovery via Systems Biology and Deep Learning Method" Biomedicines 8, no. 9: 320. https://doi.org/10.3390/biomedicines8090320

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