license:openrail region:us
PRJDB9110
https://www.ebi.ac.uk/ena/browser/view/PRJDB9110
To generate RNA aptamers against human transglutaminase 2, we have performed the high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX). Of the eight performed rounds, the rounds 0 to 8 have been sequenced.
@article{10.1093/nar/gkaa484,
    author = {Ishida, Ryoga and Adachi, Tatsuo and Yokota, Aya and Yoshihara, Hidehito and Aoki, Kazuteru and Nakamura,     Yoshikazu and Hamada, Michiaki},
    title = "{RaptRanker: in silico RNA aptamer selection from HT-SELEX experiment based on local sequence and     structure information}",
    journal = {Nucleic Acids Research},
    volume = {48},
    number = {14},
    pages = {e82-e82},
    year = {2020},
    month = {06},
    abstract = "{Aptamers are short single-stranded RNA/DNA molecules that bind to specific target molecules.     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 affinity reagents 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. Here, we present RNA aptamer     Ranker (RaptRanker), a novel in silico method for identifying 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.     To evaluate the performance of RaptRanker, we performed two new HT-SELEX experiments, and evaluated     binding affinities of a part of sequences that include aptamers with low binding-affinity. In both datasets,     the performance of RaptRanker was superior to Frequency, Enrichment and MPBind. We also confirmed that     the consideration of secondary structures is effective in HT-SELEX data analysis, and that RaptRanker     successfully predicted the essential subsequence motifs in each identified sequence.}",
    issn = {0305-1048},
    doi = {10.1093/nar/gkaa484},
    url = {https://doi.org/10.1093/nar/gkaa484},
    eprint = {https://academic.oup.com/nar/article-pdf/48/14/e82/34130937/gkaa484.pdf},
}
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license: openrail
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