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Systematic Multi-trait AAV Capsid Engineering for Efficient Gene Delivery

Eid et al., Nature Communications. 2024.

https://doi.org/10.1038/s41467-024-50555-y

Engineering novel functions into proteins while retaining desired traits is a key challenge for developers of viral vectors, antibodies, and inhibitors of medical and industrial value. In this study, investigators developed Fit4Function, a generalizable machine learning (ML) approach for systematically engineering multi-trait adeno-associated virus (AAV) capsids. Fit4Function was used to generate reproducible screening data from a capsid library that samples the entire manufacturable sequence space. The Fit4Function data were used to train accurate sequence-to-function models, which were combined to develop a library of capsid candidates. Compared to AAV9, top candidates from the Fit4Function capsid library exhibited comparable production yields; more efficient murine liver transduction; up to 1,000-fold greater human hepatocyte transduction; and increased enrichment in a screen for liver transduction in macaques. The Fit4Function strategy enables prediction of peptide-modified AAV capsid traits across species and is a critical step toward assembling an ML atlas that predicts AAV capsid performance across dozens of traits. Supported by ORIP (P51OD011107, U42OD027094), NIDDK, NIMH, and NINDS.

AAV Capsid Variants with Brain-Wide Transgene Expression and Decreased Liver Targeting After Intravenous Delivery in Mouse and Marmoset

Goertsen et al., Nature Neuroscience. 2021.

https://www.nature.com/articles/s41593-021-00969-4

Genetic intervention is increasingly being explored as a therapeutic option for debilitating disorders of the central nervous system (CNS). This project focused on organ-specific targeting of adeno-associated virus (AAV) capsids after intravenous delivery. These results constitute an important step forward toward achieving the goal of engineered AAV vectors that can be used to broadly deliver gene therapies to the CNS in humans. Supported by ORIP (U24OD026638), NIMH, and NINDS.