  Recombinant adeno-associated virus (rAAV) vectors have revolutionized gene
therapy, but their broad tropism and suboptimal transduction efficiency limit
their clinical applications. To overcome these limitations, researchers have
focused on designing and screening capsid libraries to identify improved
vectors. However, the large sequence space and limited resources present
challenges in identifying viable capsid variants. In this study, we propose an
end-to-end diffusion model to generate capsid sequences with enhanced
viability. Using publicly available AAV2 data, we generated 38,000 diverse AAV2
viral protein (VP) sequences, and evaluated 8,000 for viral selection. The
results attested the superiority of our model compared to traditional methods.
Additionally, in the absence of AAV9 capsid data, apart from one wild-type
sequence, we used the same model to directly generate a number of viable
sequences with up to 9 mutations. we transferred the remaining 30,000 samples
to the AAV9 domain. Furthermore, we conducted mutagenesis on AAV9 VP
hypervariable regions VI and V, contributing to the continuous improvement of
the AAV9 VP sequence. This research represents a significant advancement in the
design and functional validation of rAAV vectors, offering innovative solutions
to enhance specificity and transduction efficiency in gene therapy
applications.
