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Computationally guided discovery of Ly6e/LY6E-dependent AAV capsid variants.

Overview

Authors: Hiroaki Ono1, Shoko Fujino1, Genshiro A Sunagawa1,2
  1. Laboratory for Hibernation Biology, RIKEN Center for Biosystems Dynamics Research (BDR), Hyogo 651-0092, Japan
  2. Suntory Rising Stars Encouragement Program in Life Sciences (SunRiSE) Fellow, Suntory Foundation for Life Sciences, Kyoto 619-0284, Japan
Journal: iScience, volume 29, issue 5, article 115554
Dates: received 24 November 2025; accepted 27 March 2026; published online 1 April 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1016/j.isci.2026.115554 · PMID 42028008 · PMCID PMC13101293 · OpenAlex W7147546213
Open access: gold, a free copy (OpenAlex)
Status: code on request
Categories: cellular / molecular (subfield)
Methods: Spectral & time-frequency, Statistics
Keywords: Drug delivery system, Neuroscience, Genetic engineering
Topic: Virus-based gene therapy research (Genetics, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: Suntory Foundation for Life Sciences; Japan Society for the Promotion of Science (23H04941, 23K14130); RIKEN
Citations: not cited yet (Europe PMC); 74 references in the paper

Abstract

Systemic adeno-associated virus (AAV) delivery to the central nervous system (CNS) would broaden neuroscience studies and therapeutic development, but capsids evolved in mice often underperform across species. We used structure-guided computational prioritization of short peptide inserts predicted to engage the BBB-associated Ly6-family receptor Ly6e/LY6E, grafting candidates into a surface loop of an AAV9 capsid. Selected variants increased blood-brain barrier transduction and enabled widespread CNS gene delivery in Syrian hamsters after intravenous dosing, with lead capsids showing Ly6e-dependent binding and transduction in cell assays. Using the same strategy for the human ortholog, we identified multiple AAV9 variants with LY6E-dependent enhancement of in vitro transduction. These capsids support species-matched CNS delivery and demonstrate how receptor-informed computation can focus experimental screening when in vivo library selection is impractical.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper says that its authors' code is available on request: it was not published with the paper, so there is nothing to verify.

The paper's code and data availability statement is in the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none (its code is available on request), so it has no map.

Data

Datasets cited

Data and code availability

Peptide sequence data generated in this study are provided in the figures. Publicly available datasets used in this study include UniProt protein sequence records for mouse Ly6A (UniProt: P05533 (https://www.uniprot.org/uniprotkb/https://www.uniprot.org/P05533)), Syrian hamster Ly6e (UniProt: A0A1U7Q6V5) and human LY6E (UniProt: Q16553 (https://www.uniprot.org/uniprotkb/https://www.uniprot.org/Q16553)), as well as human brain expression data from the Human Protein Atlas (genes analyzed: LY6E, TFRC, and SLC2A1; https://www.proteinatlas.org/humanproteome/brain). Structural model files generated in this study and image data underlying the figures are available from the lead contact upon reasonable request.

Custom Python code used for analysis has been deposited in Mendeley Data and is publicly available as of the date of publication at https://doi.org/10.17632/g49ycssrnv.1.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request. Plasmids generated in this study are available from Addgene as listed in the key resources table.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 2, 28 September 2026

  • Authors: added Hiroaki Ono (0000-0002-4987-6797); removed Hiroaki Ono

Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 3 keywords, 3 funders, 74 references.

Cite

This paper

Ono, H., Fujino, S., & Sunagawa, G. A. (2026). Computationally guided discovery of Ly6e/LY6E-dependent AAV capsid variants. iScience, 29(5), 115554. https://doi.org/10.1016/j.isci.2026.115554

BibTeX

@article{ono2026computationally,
author = {Ono, Hiroaki and Fujino, Shoko and Sunagawa, Genshiro A},
title = {{Computationally guided discovery of Ly6e/LY6E-dependent AAV capsid variants}},
journal = {iScience},
year = {2026},
month = apr,
volume = {29},
number = {5},
pages = {115554},
publisher = {Elsevier},
issn = {2589-0042},
doi = {10.1016/j.isci.2026.115554},
url = {https://doi.org/10.1016/j.isci.2026.115554},
pmid = {42028008},
pmcid = {PMC13101293}
}

RIS

TY - JOUR
AU - Ono, Hiroaki
AU - Fujino, Shoko
AU - Sunagawa, Genshiro A
TI - Computationally guided discovery of Ly6e/LY6E-dependent AAV capsid variants
T2 - iScience
J2 - iScience
PY - 2026
DA - 2026/04/01
VL - 29
IS - 5
SP - 115554
SN - 2589-0042
PB - Elsevier
DO - 10.1016/j.isci.2026.115554
UR - https://doi.org/10.1016/j.isci.2026.115554
LA - en
ER -

CSL-JSON

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