Evidence map›Paper›PMID 42482306›Full record

ArticlemAbs2026

Glycosylation penetrance of N-X-S/T sequons in antibody variable domains: a structural survey of 19,265 human antibody structures reassessing the histidine/glutamine suppression hypothesis.

Christopher L Gaughan

Abstract read
In one paragraph

Article in mAbs, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Christopher L GaughanAntibodyML Consulting LLC, North Brunswick, NJ, USA.ORCID 0009-0009-2650-6724

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Machine learning (ML) approaches for de novo antibody design generate thousands of candidate sequences, but most lack a robust assessment of post-translational modification liabilities. N-linked glycosylation in variable domains can fundamentally alter antibody function, yet current penetrance estimates are derived from glycosylation-enriched datasets inflating risk estimates. We surveyed 19,265 human antibody structures from the Protein Data Bank (PDB), identifying 1,368 N-X-S/T sequons in variable domains (this study) with 7.82% observed penetrance (107/1,368; Wilson 95% CI 6.5-9.4%) - a crystallographic lower bound reflecting selection against glycosylated structures in the PDB - compared with 16.47% from a previously published glycosylation-enriched corpus. At the X-position, no glycosylation was observed at histidine (0/61; Wilson 95% upper bound 5.9%), lysine (0/26; upper bound 12.9%), or tryptophan (0/26), consistent with suppression. Glutamine showed 6.45% penetrance (2/31), indistinguishable from baseline and refuting its prior classification as a suppressor. Variable light domains showed higher aggregate penetrance than variable heavy (9.62% vs 6.79%; Fisher OR = 1.46,

Indexed as

AntibodiesGlutamineHistidineDatabases, ProteinGlycosylationHumansMachine LearningPenetranceProtein Processing, Post-TranslationalAntibodiesGlutamineHistidineantibody variable domainBayesian logistic regressioncomputational antibody designglycosylation penetranceN-linked glycosylationoligosaccharyltransferasepost-translational modificationRFdiffusionsequon

Identifiers

PMID42482306
PMCPMC13393236

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.