In one paragraphArticle 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. 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
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
17 authors.
Annika PhilominDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0009-0008-0305-9709 Ria SonigraDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0002-1657-6210 Sagardip MajumderDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0002-4736-6945 Hsien-Jui Michelin LinDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0009-0001-6732-366X Yanjing LiDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0009-0001-3116-525X Ryan D KiblerDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0001-6984-9887 Claire K BaldusMaseeh Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, TX, USA.ORCID 0000-0001-9615-8897 Eva TrapidoDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0009-0003-0721-2540 Amelie MedeirosDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0009-0006-1578-6159 Brian CoventryDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0002-6910-6255 Asim K BeraDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0001-9473-2912 Alex KangDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0001-5487-0499 Johnny MendozaDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0003-1573-4202 Manish KumarMaseeh Department of Civil, Architectural, and Environmental Engineering, University of Texas at Austin, TX, USA.ORCID 0000-0001-5545-3793 David BakerDepartment of Biochemistry, Institute for Protein Design, University of Washington, Seattle, WA, 98195, USA.ORCID 0000-0001-7896-6217 Funding
X-ray Scattering Technology CoreP30GM133893 · NIGMS · BROOKHAVEN SCIENCE ASSOC-BROOKHAVEN LAB · PI Vivian Stojanoff · 2019 to 2026
$38.6MUser Training and OutreachP30GM124165 · NIGMS · CORNELL UNIVERSITY · PI STEVEN E EALICK · 2018 to 2026
$34.2MPixel Array Detector for Macromolecular CrystallographyS10OD021527 · OD · CORNELL UNIVERSITY · PI EALICK, STEVEN E · 2016 to 2016
$2.0MNIGMS NIH HHS P30 GM124165NIGMS NIH HHS P30 GM133893NIH HHS S10 OD021527
6 · The paper itselfAbstract
Protein nanopores are powerful tools for molecular sensing, sequencing, and separation, but designing pores with programmable function remains challenging. Native homo-oligomeric transmembrane β barrels (TMBs) are used for these applications, but their uniform lumens limit spatial resolution and analyte discrimination. Although monomeric TMBs can be designed using energy-based methods, these approaches remain highly manual and limited to structural design rather than function. Here, we present a generative AI framework for TMB design, with backbone and sequence design models trained on a curated distillation set. We characterized 48 designs spanning 0.7-1.5 nm in diameter, diverse lumen chemistries, and hydrophobic thicknesses. Crystal structures closely match the design models. We demonstrate that our method produces customizable nanopores for ion sensing, DNA translocation, and transport across polymer membranes.
Identifiers
PMID42282680
PMCPMC13252360
What OpenQuestion holds
Textmetadata
LicenceCC BY
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