Computer-Aided Directed Evolution Generates Novel AAV Variants with High Transduction Efficiency

Abstract

Adeno-associated viruses (AAVs) have become safe and effective tools for therapeutic in vivo gene drug delivery. Among many AAV serotypes, AAV2 is the most well-characterized. Although many studies have been carried out on the engineering of the capsid VR-VIII region, few attempts have been made in the VR-IV region. Here, we targeted amino acid positions 442–469 of the VR-IV region and established an engineering paradigm of computer-aided directed evolution, based on training samples from previous datasets, to obtain a viral vector library with high diversity (~95,089). We further examined two variants selected from the library. The transduction efficiency of these two novel AAV variants, AAV2.A1 and AAV2.A2, in the central nervous system was 10–15 times higher than that of AAV2. This finding provides new vehicles for delivering gene drugs to the brain.