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Record W2768244177 · doi:10.1038/s41467-017-01706-x

Receptor-binding loops in alphacoronavirus adaptation and evolution

2017· article· en· W2768244177 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsCanada Research ChairsInstitut National de la Recherche ScientifiqueUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanadian Light Source
KeywordsEctodomainMutationBiologyReceptorPopulationGeneticsAdaptation (eye)CoronavirusChemistryVirologyGeneCoronavirus disease 2019 (COVID-19)Medicine

Abstract

fetched live from OpenAlex

RNA viruses are characterized by a high mutation rate, a buffer against environmental change. Nevertheless, the means by which random mutation improves viral fitness is not well characterized. Here we report the X-ray crystal structure of the receptor-binding domain (RBD) of the human coronavirus, HCoV-229E, in complex with the ectodomain of its receptor, aminopeptidase N (APN). Three extended loops are solely responsible for receptor binding and the evolution of HCoV-229E and its close relatives is accompanied by changing loop-receptor interactions. Phylogenetic analysis shows that the natural HCoV-229E receptor-binding loop variation observed defines six RBD classes whose viruses have successively replaced each other in the human population over the past 50 years. These RBD classes differ in their affinity for APN and their ability to bind an HCoV-229E neutralizing antibody. Together, our results provide a model for alphacoronavirus adaptation and evolution based on the use of extended loops for receptor binding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.311
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it