AAVDiff: Experimental Validation of Enhanced Viability and Diversity in Recombinant Adeno-Associated Virus (AAV) Capsids through Diffusion Generation

TL;DR

This paper introduces a diffusion model to generate diverse and viable AAV capsid sequences, significantly improving the design process for gene therapy vectors by enabling efficient exploration of sequence space.

Contribution

The study presents an end-to-end diffusion model for designing AAV capsids, demonstrating superior performance over traditional methods and enabling generation of viable sequences with minimal mutations.

Findings

Generated 38,000 diverse AAV2 VP sequences with high viability.

Successfully generated viable AAV9 sequences with up to 9 mutations.

Enhanced AAV9 VP sequences through mutagenesis, improving transduction efficiency.

Abstract

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.