Small Molecule Pan-Dengue and West Nile Virus NS3 Protease Inhibitors is a research paper published in Antiviral Chemistry and Chemotherapy (2011). On theSindex it has a DataRank of 2.3. It has been cited 57 times, with 56 citing works in its 1-hop citation network.
Background: Dengue fever, dengue haemorrhagic fever, and dengue shock syndrome are caused by infections with any of the four serotypes of the dengue virus (DENV), and are an increasing global health risk. The related West Nile virus (WNV) causes significant morbidity and mortality as well, and continues to be a threat in endemic areas. Currently no FDA-approved vaccines or therapeutics are available to prevent or treat any of these infections. Like the other members of Flaviviridae, DENV and WNV encode a protease (NS3) which is essential for viral replication and therefore is a promising target for developing therapies to treat dengue and West Nile infections. Methods: Flaviviral protease inhibitors were identified and biologically characterized for mechanism of inhibition and DENV antiviral activity. Results: A guanidinylated 2,5-dideoxystreptamine class of compounds was identified that competitively inhibited the NS3 protease from DENV(1–4) and WNV with 50% inhibitory concentration values in the 1–70 μM range. Cytotoxicity was low; however, antiviral activity versus DENV-2 on VERO cells was not detectable. Conclusions: This class of compounds is the first to demonstrate competitive pan-dengue and WNV NS3 protease inhibition and, given the sequence conservation among flavivirus NS3 proteins, suggests that developing a pan-dengue or possibly pan-flavivirus therapeutic is feasible.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.609
From this paper's citation signal
Citation Network Contribution
1.7
From 52 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 26% comes from its base citations and 74% from the citation network (52 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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