Evidence map›Paper›PMID 42146395›Full record

ArticlebioRxiv : the preprint server for biology2026

Fast and Ultra-Capable Protein Design: Advancing the Frontier Through Atomistic SE(3)-Equivariance with Genie 3.

Yeqing Lin, Minji Lee, Aakarsh Vermani, Ellena Jiang, Sebastiaan De Cooman, Matej Špetko, Mohammed AlQuraishi

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Yeqing LinDepartment of Systems Biology, Columbia University, NY, USA.
Minji LeeDepartment of Systems Biology, Columbia University, NY, USA.
Aakarsh VermaniDepartment of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, USA.
Ellena JiangDepartment of Computer Science, Columbia University, NY, USA.
Sebastiaan De CoomanPuxano BV, Ghent, Belgium.
Matej ŠpetkoIT4Innovations National Supercomputing Center, VŠB-Technical University of Ostrava.
Mohammed AlQuraishiDepartment of Systems Biology, Columbia University, NY, USA.

Funding

Machine learning of biomolecular interactions and the human signaling networks they compriseR35GM150546 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Mohammed Nazar AlQuraishi · 2023 to 2026
$1.6M
NIGMS NIH HHS R35 GM150546
6 · The paper itself

Abstract

Despite the breakneck pace of progress in protein design methodology, frontier problems remain challenging, with leading methods struggling to design high-affinity binders, scaffold multiple functional motifs, or stabilize large multi-domain proteins. Recent research efforts have focused on two areas: improving model reasoning when generating active sites or binding interfaces, and improving concordance between the design process and the

Identifiers

PMID42146395
PMCPMC13174375

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.