Mammalian cargo receptors for endoplasmic reticulum-to-Golgi transport: mechanisms and interactions is a research paper published in Biochemical Society Transactions (2023). On theSindex it has a DataRank of 0.747. It has been cited 22 times, with 21 citing works in its 1-hop citation network.
Proteins that are destined to enter the secretory pathway are synthesized on the rough endoplasmic reticulum (ER) and then translocated into the ER lumen, where they undergo posttranslational modifications, folding, and assembly. After passing a quality control system, the cargo proteins are packaged into coat protein complex II (COPII) vesicles to exit the ER. In metazoans, most COPII subunits have multiple paralogs, enabling COPII vesicles the flexibility to transport a diverse range of cargo. The cytoplasmic domains of transmembrane proteins can interact with SEC24 subunits of COPII to enter the ER exit sites. Some transmembrane proteins may also act as cargo receptors that bind soluble secretory proteins within the ER lumen, enabling them to enter COPII vesicles. The cytoplasmic domains of cargo receptors also contain coat protein complex I binding motifs that allow for their cycling back to the ER after unloading their cargo in the ER-Golgi intermediate compartment and cis-Golgi. Once unloaded, the soluble cargo proteins continue maturation through the Golgi before reaching their final destinations. This review provides an overview of receptor-mediated transport of secretory proteins from the ER to the Golgi, with a focus on the current understanding of two mammalian cargo receptors: the LMAN1–MCFD2 complex and SURF4, and their roles in human health and disease.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.470
From this paper's citation signal
Citation Network Contribution
0.277
From 14 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 63% comes from its base citations and 37% from the citation network (14 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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