Evidence map›Paper›PMID 41040335›Full record

ArticlebioRxiv : the preprint server for biology2025

Efficient generation of epitope-targeted

Luis S Mille-Fragoso, John N Wang, Claudia L Driscoll, Haoyu Dai, Talal Widatalla, Xiaowei Zhang, Brian L Hie, Xiaojing J Gao

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

8 authors.

Luis S Mille-FragosoDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID 0000-0001-7072-1522
John N WangDepartment of Computer Science, Stanford University, Stanford, CA, USA.ORCID 0009-0008-1549-0360
Claudia L DriscollArc Institute, Palo Alto, CA, USA.ORCID 0000-0003-2285-6910
Haoyu DaiDepartment of Chemical Engineering, Stanford University, Stanford, CA, USA.ORCID 0009-0008-4920-6815
Talal WidatallaArc Institute, Palo Alto, CA, USA.ORCID 0009-0003-1870-4460
Xiaowei ZhangDepartment of Bioengineering, Stanford University, Stanford, CA, USA.ORCID 0000-0002-7749-4382
Brian L HieSarafan ChEM-H, Stanford University, Stanford, CA, USA.ORCID 0000-0003-3224-8142
Xiaojing J GaoSarafan ChEM-H, Stanford University, Stanford, CA, USA.ORCID 0000-0002-3094-1456

Funding

A Novel Class of Synthetic Receptors to Empower the Age of mRNA TherapiesDP2EB035891 · NIBIB · STANFORD UNIVERSITY · PI Xiaojing J Gao · 2023 to 2026
$2.3M
NIBIB NIH HHS DP2 EB035891
6 · The paper itself

Abstract

Obtaining novel antibodies against specific protein targets is a widely important yet experimentally laborious process. Meanwhile, computational methods for antibody design have been limited by low success rates that currently require resource-intensive screening. Here, we introduce Germinal, a broadly enabling generative framework that designs antibodies against specific epitopes with nanomolar binding affinities while requiring only low-n experimental testing. Our method co-optimizes antibody structure and sequence by integrating a structure predictor with an antibody-specific protein language model to perform

Identifiers

PMID41040335
PMCPMC12485712

What OpenQuestion 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 OpenQuestion graph.