MétaCan
Menu
Back to cohort
Record W2000885937 · doi:10.1126/science.1245625

Crystal Structure of a Soluble Cleaved HIV-1 Envelope Trimer

2013· article· en· W2000885937 on OpenAlexfundno aff
Jean‐Philippe Julien, Albert Cupo, Devin Sok, Robyn L. Stanfield, Dmitry Lyumkis, Marc C. Deller, Per-Johan Klasse, Dennis R. Burton, Rogier W. Sanders, John P. Moore, Andrew B. Ward, Ian A. Wilson

Bibliographic record

VenueScience · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute of General Medical SciencesNational Cancer InstituteNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health Research
KeywordsTrimerGp41ChemistryEpitopeGlycoproteinBiophysicsAntibodyBiologyBiochemistryDimer

Abstract

fetched live from OpenAlex

HIV-1 entry into CD4(+) target cells is mediated by cleaved envelope glycoprotein (Env) trimers that have been challenging to characterize structurally. Here, we describe the crystal structure at 4.7 angstroms of a soluble, cleaved Env trimer that is stabilized and antigenically near-native (termed the BG505 SOSIP.664 gp140 trimer) in complex with a potent broadly neutralizing antibody, PGT122. The structure shows a prefusion state of gp41, the interaction between the component gp120 and gp41 subunits, and how a close association between the gp120 V1/V2/V3 loops stabilizes the trimer apex around the threefold axis. The complete epitope of PGT122 on the trimer involves gp120 V1, V3, and several surrounding glycans. This trimer structure advances our understanding of how Env functions and is presented to the immune system, and provides a blueprint for structure-based vaccine design.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.256
Teacher spread0.243 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations826
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueScienceSame topicHIV Research and TreatmentFrench-language works237,207