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Record W2586232813 · doi:10.1038/ncomms14369

An unexpected N-terminal loop in PD-1 dominates binding by nivolumab

2017· article· en· W2586232813 on OpenAlexfundno aff
Shuguang Tan, Hao Zhang, Yan Chai, Hao Song, Zhou Tong, Qihui Wang, Jianxun Qi, Gary Wong, Xiaodong Zhu, William J. Liu, Shan Gao, Zhongfu Wang, Yi Shi, Fuquan Yang, George F. Gao, Jinghua Yan

Bibliographic record

VenueNature Communications · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchChinese Academy of SciencesNational Natural Science Foundation of ChinaSalt Science Research Foundation
KeywordsNivolumabPembrolizumabGlycosylationMonoclonal antibodyImmunotherapyImmune checkpointChemistryPD-L1Computational biologyCancer researchAntibodyImmune systemMedicineBiochemistryBiologyImmunology

Abstract

fetched live from OpenAlex

Cancer immunotherapy by targeting of immune checkpoint molecules has been a research 'hot-spot' in recent years. Nivolumab, a human monoclonal antibody targeting PD-1, has been widely used clinically since 2014. However, the binding mechanism of nivolumab to PD-1 has not yet been shown, despite a recent report describing the complex structure of pembrolizumab/PD-1. It has previously been speculated that PD-1 glycosylation is involved in nivolumab recognition. Here we report the complex structure of nivolumab with PD-1 and evaluate the effects of PD-1 N-glycosylation on the interactions with nivolumab. Structural and functional analyses unexpectedly reveal an N-terminal loop outside the IgV domain of PD-1. This loop is not involved in recognition of PD-L1 but dominates binding to nivolumab, whereas N-glycosylation is not involved in binding at all. Nivolumab binds to a completely different area than pembrolizumab. These results provide the basis for the design of future inhibitory molecules targeting PD-1.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.435

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 science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.360
Teacher spread0.338 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations260
Published2017
Admission routes1
Has abstractyes

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