Identification of Candidate TLR9 Inhibitors Using the RF3 Metric

Abstract

Recombinant adeno-associated virus (AAV) has become an important tool in gene delivery and gene therapy. Although AAV is considered low immunogenic, the AAV genome triggers toll-like receptor 9 (TLR9) activity in the brain, resulting in an immune response. TLR9 activation induces an upregulation in inflammatory proteins that simplify dendritic complexity; TLR9 inhibition may minimize these harmful consequences of AAV. Although TLR9 inhibitors are currently available, they are costly and moderately effective. Furthermore, the inhibitors are created with naturally derived sequences that may provide less inhibitory potential than synthetically generated ones. To quantify the TLR9-inhibitory potential of randomly generated sequences, the risk factor 3 (RF3) metric was used. Sequences between 3 and 30 nucleotides were generated using the Random DNA Sequence Generator website, and the RF3 value for each sequence was calculated using The CpG Assist Tool website. To determine the inhibitory potential of specific sequence lengths, the mean, median, mode, and range RF3 for each sequence length was analyzed. The two most negative RF3 values were exhibited by specific 6 and 10 nucleotide sequences. These sequences hold the most inhibitory potential out of all sequences analyzed and hold promise as TLR9 inhibitors. To validate the sequence predictions made by RF3, an in vitro experiment is proposed. The inhibitory sequences will be added to TLR9 reporter cells in order to compare the inhibitory capabilities of the 6 and 10 nucleotide sequences with those of commercially available TLR9 inhibitors (ODN2088 and ODN io2, respectively). Validating and refining RF3 predictions will aid in developing optimal TLR9 antagonists and agonists, which can be used to enhance gene therapy and combat pathogenic infections.