RaptRanker: in silico RNA aptamer selection from HT-SELEX experiment based on local sequence and structure information

Aptamers are short single-stranded RNA/DNA molecules that bind to specific target molecules. Aptamers have emerged as new target-specific drugs to replace antibodies due to their diversity, low immunogenicity, and ease of synthesis. Aptamers with high binding-affinity and target specificity are identified using an in vitro procedure called high throughput systematic evolution of ligands by exponential enrichment (HT-SELEX). However, the development of aptamer drugs takes a considerable amount of time and is costly because HT-SELEX produces a large dataset of candidate sequences, some of which have insufficient binding-affinity. Therefore, it is essential to further identify the aptamers with high binding-affinity from the HT-SELEX data. Here, we present RNA aptamer Ranker (RaptRanker), a novel in silico method for identifying truly high binding- affinity aptamers from HT-SELEX data by scoring and ranking. RaptRanker analyzes HT-SELEX data by evaluating the nucleotide sequence and secondary structure simultaneously, and by ranking according to scores reflecting local structure and sequence frequencies. For the HT-SELEX datasets tested, the performance of RaptRanker was superior to those of the existing methods.