Competitive Translation Efficiency at the Picornavirus Type 1 Internal Ribosome Entry Site Facilitated by Viral<i>cis</i>and<i>trans</i>Factors is a research paper published in Journal of Virology (2006). On theSindex it has a DataRank of 1.3. It has been cited 38 times, with 22 citing works in its 1-hop citation network.
ABSTRACTEnteroviruses (EVs) overcome their host cells by usurping the translation machinery to benefit viral gene expression. This is accomplished through alternative translation initiation in a cap-independent manner at the viral internal ribosomal entry site (IRES). We have investigated the role ofcis- andtrans-acting viral factors in EV IRES translation in living cells. We observed that considerable portions of the viral genome, including the 5′-proximal open reading frame and the 3′ untranslated region, contribute to stimulation of IRES-mediated translation. With the IRES in proper context, translation via internal initiation in uninfected cells is as efficient as at capped messages with short, unstructured 5′ untranslated regions. IRES function is enhanced in cells infected with the EV coxsackievirus B3, but the related poliovirus has no significant stimulatory activity. This differential is due to the inherent properties of their 2A protease and is not coupled to 2A-mediated proteolytic degradation of the eukaryotic initiation factor 4G. Our results suggest that the efficiency of alternative translation initiation at EV IRESs depends on a properly configured template rather than on targeted alterations of the host cell translation machinery.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.550
From this paper's citation signal
Citation Network Contribution
0.781
From 19 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 41% comes from its base citations and 59% from the citation network (19 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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