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Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

ABSTRACT: Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug-gene-adverse drug reaction (ADR) interaction network. For the first time, the drug safety was assessed in a broad landscape of 1,156 distinct ADRs. We also designed a parameter ToxicityScore to quantify the overall drug safety. Moreover, we determined association strength for every 3,807,631 gene-ADR interactions, which clues mechanistic exploration of ADRs. For convenience, we deployed the model as a web service ADRAlert-gene at http://www.bio-add.org/ADRAlert/. In summary, this study offers insights into prioritizing safe drug therapy. It helps reduce the attrition rate of new drug discovery by providing a reliable ADR profile in the early preclinical stage.

SUBMITTER: Liu K

PROVIDER: S-EPMC7325315 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Liu Ke K Ding Ruo-Fan RF Xu Han H Qin Yang-Mei YM He Qiu-Shun QS Du Fei F Zhang Yun Y Yao Li-Xia LX You Pan P Xiang Yan-Ping YP Ji Zhi-Liang ZL

Clinical pharmacology and therapeutics 20200228 6

Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug-gene-adverse drug reaction (ADR) interaction network. For the first time, the drug safety was assessed in a broad landscape of 1,1 ...[more]

PMID: 31868917

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Project description:Despite to outbreaks of highly pathogenic beta and alpha coronaviruses including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and human coronavirus, the newly emerged 2019 coronavirus (COVID-19) is considered as a lethal zoonotic virus due to its deadly respiratory syndrome and high mortality rate among the human. Globally, more than 3,517,345 cases have been confirmed with 243,401 deaths due to Acute Respiratory Distress Syndrome (ARDS) caused by COVID-19. The antiviral drug discovery activity is required to control the persistence of COVID-19 circulation and the potential of the future emergence of coronavirus. However, the present review aims to highlight the important antiviral approaches, including interferons, ribavirin, mycophenolic acids, ritonavir, lopinavir, inhibitors, and monoclonal antibodies (mAbs) to provoke the nonstructural proteins and deactivate the structural and essential host elements of the virus to control and treat the infection of COVID-19 by inhibiting the viral entry, viral RNA replication and suppressing the viral protein expression. Moreover, the present review investigates the epidemiology, diagnosis, structure, and replication of COVID-19 for better understanding. It is recommended that these proteases, inhibitors, and antibodies could be a good therapeutic option in drug discovery to control the newly emerged coronavirus.HighlightsCOVID-19 has more than 79.5% identical sequence to SARS-CoV and a 96% identical sequence of the whole genome of bat coronaviruses.Acute respiratory distress syndrome (ARDS), renal failure, and septic shock are the possible clinical symptoms associated with COVID-19.Different antivirals, including interferons, ribavirin, lopinavir, and monoclonal antibodies (mAbs) could be the potent therapeutic agents against COVID-19.The initial clinical trials on hydroquinone in combination with azithromycin showed an admirable result in the reduction of COVID-19.The overexpression of inflammation response, cytokine dysregulation, and induction of apoptosis could be an well-organized factors to reduce the pathogenicity of COVID-19.

Dataset Information

Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Publications

Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

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