Summary
Adeno-associated virus (AAV) capsids have shown clinical promise as delivery vectors for gene therapy. However, the high prevalence of pre-existing immunity against natural capsids poses a challenge for widespread treatment. The generation of diverse capsids that are potentially more capable of immune evasion is challenging because introducing multiple mutations often breaks capsid assembly. Here we target a representative, immunologically relevant 28-amino-acid segment of the AAV2 capsid and show that a low-complexity Variational Auto-encoder (VAE) can interpolate in sequence space to produce diverse and novel capsids capable of packaging their own genomes. We first train the VAE on a 564-sample Multiple-Sequence Alignment (MSA) of dependo-parvoviruses, and then further augment this dataset by adding 22,704 samples from a deep mutational exploration (DME) on the target region. In both cases the VAE generated viable variants with many mutations, which we validated experimentally. We propose that this simple approach can be used to optimize and diversify other proteins, as well as other capsid traits of interest for gene delivery.
Competing Interest Statement
EK, NJ, SS, GMC performed research while at Harvard University and EK, SS also performed research while at Dyno Therapeutics. EK, SS, and GMC hold equity at Dyno Therapeutics. A full list of GMCs tech transfer, advisory roles, and funding sources can be found on the labs website: http://arep.med.harvard.edu/gmc/tech.html. Harvard University has filed a patent application for inventions related to this work.
