TSignal : a transformer model for signal peptide prediction
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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2023-06-01
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en
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Bioinformatics, Volume 39, pp. I347-I356
Abstract
Motivation: Signal peptides (SPs) are short amino acid segments present at the N-terminus of newly synthesized proteins that facilitate protein translocation into the lumen of the endoplasmic reticulum, after which they are cleaved off. Specific regions of SPs influence the efficiency of protein translocation, and small changes in their primary structure can abolish protein secretion altogether. The lack of conserved motifs across SPs, sensitivity to mutations, and variability in the length of the peptides make SP prediction a challenging task that has been extensively pursued over the years. Results: We introduce TSignal, a deep transformer-based neural network architecture that utilizes BERT language models and dot-product attention techniques. TSignal predicts the presence of SPs and the cleavage site between the SP and the translocated mature protein. We use common benchmark datasets and show competitive accuracy in terms of SP presence prediction and state-of-the-art accuracy in terms of cleavage site prediction for most of the SP types and organism groups. We further illustrate that our fully data-driven trained model identifies useful biological information on heterogeneous test sequences.Description
Funding Information: This work was supported by the Academy of Finland [grant numbers 314445 and 328401 to H.L. and 338836 and 314672 to V.O.P.]; by Sigrid Juselius Foundation [grant to V.O.P]; by the Jane and Aatos Erkko Foundation [grant to V.O.P] and by National Institute of Health [grant number 1R01GM132649 to V.O.P.]. Publisher Copyright: © 2023 The Author(s). Published by Oxford University Press.
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Dumitrescu, A, Jokinen, E, Paatero, A, Kellosalo, J, Paavilainen, V O & Lähdesmäki, H 2023, ' TSignal : a transformer model for signal peptide prediction ', Bioinformatics, vol. 39, pp. I347-I356 . https://doi.org/10.1093/bioinformatics/btad228