Aptamers are expected to be next-generation drugs, but identifying candidate aptamers is a challenging task given the large search space. Now, an artificial intelligence (AI)-powered tool called RaptGen is proposed for improving the successful identification of aptamer sequences.
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References
Keefe, A., Pai, S. & Ellington, A. Nat. Rev. Drug Discov. 9, 537–550 (2010).
Iwano, N., Adachi, T., Aoki, K., Nakamura, Y. & Hamada, M. Nat. Comput. Sci. https://doi.org/10.1038/s43588-022-00249-6 (2022).
Tuerk, C. & Gold, L. Science 249, 505–510 (1990).
Ellington, A. D. & Szostak, J. W. Nature 346, 818–822 (1990).
Wang, R. E., Wu, H., Niu, Y. & Cai, J. Curr. Med. Chem. 18, 4126–4138 (2011).
Ishida, R. et al. Nucleic Acids Res. 48, e82–e82 (2020).
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Khabbazian, M., Jabbari, H. AI-powered aptamer generation. Nat Comput Sci 2, 356–357 (2022). https://doi.org/10.1038/s43588-022-00253-w
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DOI: https://doi.org/10.1038/s43588-022-00253-w
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