The coronavirus disease 2019 (COVID-19) epidemic is currently raging around the world with a rapid speed. Among the COVID-19 patients, SARS-CoV-2 associated acute respiratory distress syndrome (ARDS) is the main contribution to the high ratio of morbidity and mortality. However, clinical manifestations between SARS-CoV-2-caused-ARDS and non-SARS-CoV-2-caused-ARDS are quite common and their therapy is limited owing to the intricated pathophysiology are not fully understood. In this study, we constructed a candidate host-pathogen interspecies genome-wide genetic and epigenetic network (HPI-GWGEN) via database mining at first. With the help of host-pathogen microarray data, real HPI-GWGEN of COVID-19-ARDS and Non-Viral-ARDS were obtained by system modeling, system identification and Akaike information criterion (AIC) of model order selection method to delete the false positives in candidate HPI-GWGEN. Afterwards, principal network projection (PNP) approach is utilized to extract core HPI-GWGEN and their core signaling pathways of COVID-19-ARDS and Non-Viral-ARDS annotated by KEGG pathways. In order to design multiple-molecule drugs of COVID-19-ARDS and Non-Viral-ARDS, we identified essential biomarkers of pathogenesis by comparing the core signal pathways between COVID-19-ARDS and Non-Viral-ARDS. The deep neural network of drug-target interaction model (DNN-DTI) would be trained by drug-target interaction databases in advance to predict candidate drugs for the identified biomarkers. We further narrowed down these predicted drug candidates as potential multiple-molecule drug by filters of drug design specifications, including regulation ability, sensitivity, excretion, toxicity and drug-likeness. Taken together, we not only enlighten the etiologic mechanisms under COVID-19-ARDS but also provided novel therapeutic options for COVID-19-ARDS and Non-viral-ARDS.
CITATION STYLE
Ting, C. T., Yeh, S. J., & Chen, B. S. (2021). COVID-19-related Versus Non-Viral Acute Respiratory Distress Syndrome: Comparison of Upper Airway Molecular Pathway and Drug Discovery Design based on Systems Biology and Deep Learning Methods. In 2021 International Automatic Control Conference, CACS 2021. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/CACS52606.2021.9639034
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