Identification of novel anti-ZIKV drugs from viral-infection temporal gene expression profiles

Abstract

Zika virus (ZIKV) infections are typically asymptomatic but cause severe neurological complications (e.g. Guillain–Barré syndrome in adults, and microcephaly in newborns). There are currently no specific therapy or vaccine options available to prevent ZIKV infections. Temporal gene expression profiles of ZIKV-infected human brain microvascular endothelial cells (HBMECs) were used in this study to identify genes essential for viral replication. These genes were then used to identify novel anti-ZIKV agents and validated in publicly available data and functional wet-lab experiments. Here, we found that ZIKV effectively evaded activation of immune response-related genes and completely reprogrammed cellular transcriptional architectures. Knockdown of genes, which gradually upregulated during viral infection but showed distinct expression patterns between ZIKV- and mock infection, discovered novel proviral and antiviral factors. One-third of the 74 drugs found through signature-based drug repositioning and cross-reference with the Drug Gene Interaction Database (DGIdb) were known anti-ZIKV agents. In cellular assays, two promising antiviral candidates (Luminespib/NVP-AUY922, L-161982) were found to reduce viral replication without causing cell toxicity. Overall, our time-series transcriptome-based methods offer a novel and feasible strategy for antiviral drug discovery. Our strategies, which combine conventional and data-driven analysis, can be extended for other pathogens causing pandemics in the future.

A Marine Natural Product, Harzianopyridone, as an Anti-ZIKV Agent by Targeting RNA-Dependent RNA Polymerase

“…Nowadays, ZIKV transmission has diminished, but it is still important to remain vigilant for its reemergence and global spread [ 4 ]. In addition to preventive measures, antiviral drug treatment is also an important strategy against infectious diseases [ 39 ]. To date, no specific antiviral drugs have been permitted for the treatment of ZIKV infection.…”

Integrated ML-Based Strategy Identifies Drug Repurposing for Idiopathic Pulmonary Fibrosis

“…Many approaches such as machine learning (ML), , virtual screening, and network-science have been used in DR for rare and sporadic diseases such as IPF and also in viral diseases to identify potential new uses for existing drugs. It is done by analyzing large amounts of data, such as gene expression, drug interactions, and clinical outcomes. , For example, a study published in used ML to identify existing drugs repurposable for the treatment of Zika virus infection by analyzing gene expression profiles from infected human cells. Similarly, another study done in performed DR through an in-silico analysis, as a result, BI2536, a specific inhibitor of polo-like kinase (PLK) 1/2, was chosen as a potential candidate for the treatment of pulmonary fibrosis.…”