A yellow fever virus NS4B inhibitor not only suppresses viral replication, but also enhances the virus activation of RIG-I-like receptor-mediated innate immune response

Abstract

Flavivirus infection of cells induces massive rearrangements of the endoplasmic reticulum (ER) membrane to form viral replication organelles (ROs) which segregates viral RNA replication intermediates from the cytoplasmic RNA sensors. Among other viral nonstructural (NS) proteins, available evidence suggests for a prominent role of NS4B, an ER membrane protein with multiple transmembrane domains, in the formation of ROs and the evasion of the innate immune response. We previously reported a benzodiazepine compound, BDAA, which specifically inhibited yellow fever virus (YFV) replication in cultured cells and in vivo in hamsters, with resistant mutation mapped to P219 of NS4B protein. In the following mechanistic studies, we found that BDAA specifically enhances YFV induced inflammatory cytokine response in association with the induction of dramatic structural alteration of ROs and exposure of double-stranded RNA (dsRNA) in virus-infected cells. Interestingly, the BDAA-enhanced cytokine response in YFV-infected cells is attenuated in RIG-I or MAD5 knockout cells and completely abolished in MAVS knockout cells. However, BDAA inhibited YFV replication at a similar extent in the parent cells and cells deficient of RIG-I, MDA5 or MAVS. These results thus provided multiple lines of biological evidence to support a model that BDAA interaction with NS4B may impair the integrity of YFV ROs, which not only inhibits viral RNA replication, but also promotes the release of viral RNA from ROs, which consequentially activates RIG-I and MDA5. Although the innate immune enhancement activity of BDAA is not required for its antiviral activity in cultured cells, its dual antiviral mechanism is unique among all the reported antiviral agents thus far and warrants further investigation in animal models in future.

Exposure of negative-sense viral RNA in the cytoplasm initiates innate immunity to West Nile virus

“…Viral RNA residing in replication compartments within the ER membrane thus is not accessible with digitonin permeabilization. The use of stronger detergents such as Triton X-100 is required to permeabilize ER membranes 35 . We first confirmed this specificity by treating infected cells with either digitonin or Triton X-100, followed by exposure to RNase III, which digests dsRNA.…”

Gain without pain: Adaptation and increased virulence of Zika virus in vertebrate host without fitness cost in mosquito vector

“…ZIKV NS4A specifically has been shown to antagonize interferon induction via interactions with the RIG-I-like-receptors (RLRs), retinoic acid-inducible gene I (RIG-I), and melanoma-differentiation-associated gene 5 (MDA-5), which are cytosolic RNA sensors that sense viral RNAs during infection and trigger signaling pathways resulting in the production of type I interferon and proinflammatory cytokines (19, 20). Since our experiments were done in mice that lack type I IFN receptor 1 function, we expect that this antagonism occurs via RLR signaling through the mitochondrial antiviral-signaling protein (MAVS) pathway (21). Indeed, increasing evidence suggests that viruses can escape the host antiviral response by interfering at multiple points in the MAVS signaling pathway, thereby maintaining viral replication and expanding tropism (22).…”

1-Sulfonyl-3-amino-1H-1,2,4-triazoles as Yellow Fever Virus Inhibitors: Synthesis and Structure–Activity Relationship

“…As we face new viral pandemics, there is a continued need for the identification of broad-spectrum antivirals . Many examples of antivirals for YFV have been described that are nucleosides − and in contrast, there appear fewer examples of heterocyclic compounds demonstrating activity. , We have previously described the identification of the pyrazolesulfonamide derivative RCB16003 with low micromolar potency against YFV . This represented a starting point for hit-to-lead optimization, which was identified by machine learning.…”