Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for type 2 diabetes (T2D) treatment. We first integrate...
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doaj-dcca4da7dec1415f8b9092f511c4740a2020-12-27T00:00:54ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-12-012216616610.3390/ijms22010166Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design SpecificationsShen Chang0Jian-You Chen1Yung-Jen Chuang2Bor-Sen Chen3Laboratory of Automatic Control, Signal Processing and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, TaiwanLaboratory of Automatic Control, Signal Processing and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, TaiwanInstitute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu 30013, TaiwanLaboratory of Automatic Control, Signal Processing and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu 30013, TaiwanIn this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for type 2 diabetes (T2D) treatment. We first integrated databases to construct the genome-wide genetic and epigenetic networks (GWGENs), which consist of protein–protein interaction networks (PPINs) and gene regulatory networks (GRNs) for T2D and non-T2D (health), respectively. Second, the relevant “real GWGENs” are identified by system identification and system order detection methods performed on the T2D and non-T2D RNA-seq data. To simplify network analysis, principal network projection (PNP) was thereby exploited to extract core GWGENs from real GWGENs. Then, with the help of KEGG pathway annotation, core signaling pathways were constructed to identify significant biomarkers. Furthermore, in order to discover potential drugs for the selected pathogenic biomarkers (i.e., drug targets) from the core signaling pathways, not only did we train a deep neural network (DNN)-based drug–target interaction (DTI) model to predict candidate drug’s binding with the identified biomarkers but also considered a set of design specifications, including drug regulation ability, toxicity, sensitivity, and side effects to sieve out promising drugs suitable for T2D.https://www.mdpi.com/1422-0067/22/1/166type 2 diabetes (T2D)pathogenic mechanismdeep neural network (DNN)-based DTI modelpathogenic biomarkersdrug design specificationmultiple-molecule targeting drug |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shen Chang Jian-You Chen Yung-Jen Chuang Bor-Sen Chen |
spellingShingle |
Shen Chang Jian-You Chen Yung-Jen Chuang Bor-Sen Chen Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications International Journal of Molecular Sciences type 2 diabetes (T2D) pathogenic mechanism deep neural network (DNN)-based DTI model pathogenic biomarkers drug design specification multiple-molecule targeting drug |
author_facet |
Shen Chang Jian-You Chen Yung-Jen Chuang Bor-Sen Chen |
author_sort |
Shen Chang |
title |
Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications |
title_short |
Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications |
title_full |
Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications |
title_fullStr |
Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications |
title_full_unstemmed |
Systems Approach to Pathogenic Mechanism of Type 2 Diabetes and Drug Discovery Design Based on Deep Learning and Drug Design Specifications |
title_sort |
systems approach to pathogenic mechanism of type 2 diabetes and drug discovery design based on deep learning and drug design specifications |
publisher |
MDPI AG |
series |
International Journal of Molecular Sciences |
issn |
1661-6596 1422-0067 |
publishDate |
2021-12-01 |
description |
In this study, we proposed a systems biology approach to investigate the pathogenic mechanism for identifying significant biomarkers as drug targets and a systematic drug discovery strategy to design a potential multiple-molecule targeting drug for type 2 diabetes (T2D) treatment. We first integrated databases to construct the genome-wide genetic and epigenetic networks (GWGENs), which consist of protein–protein interaction networks (PPINs) and gene regulatory networks (GRNs) for T2D and non-T2D (health), respectively. Second, the relevant “real GWGENs” are identified by system identification and system order detection methods performed on the T2D and non-T2D RNA-seq data. To simplify network analysis, principal network projection (PNP) was thereby exploited to extract core GWGENs from real GWGENs. Then, with the help of KEGG pathway annotation, core signaling pathways were constructed to identify significant biomarkers. Furthermore, in order to discover potential drugs for the selected pathogenic biomarkers (i.e., drug targets) from the core signaling pathways, not only did we train a deep neural network (DNN)-based drug–target interaction (DTI) model to predict candidate drug’s binding with the identified biomarkers but also considered a set of design specifications, including drug regulation ability, toxicity, sensitivity, and side effects to sieve out promising drugs suitable for T2D. |
topic |
type 2 diabetes (T2D) pathogenic mechanism deep neural network (DNN)-based DTI model pathogenic biomarkers drug design specification multiple-molecule targeting drug |
url |
https://www.mdpi.com/1422-0067/22/1/166 |
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