Arora, P., Abhigyan, R., Periwal, N. et al. IL2Pepscan: A machine learning framework for predicting IL-2
inducing peptides and their identification across global viral proteomes. Sci Rep 16, 6701 (2026).
https://doi.org/10.1038/s41598-026-35977-6
Welcome to IL2PepScan
A crucial cytokine, IL-2 is mostly generated by activated T cells and is essential for controlling immunological
responses, particularly for T cell survival, differentiation,
and proliferation. It coordinates intricate immune system connections, affecting the maturation of regulatory T
cells (Tregs) and enhancing effector T cell responses.
This dual function highlights its possible therapeutic uses in gene therapy and immunotherapy for a range of
cancers and autoimmune disorder. Therefore prediction and characterization of new
molecules/peptides which can regulate IL-2 induction might lead to novel therapeutics.
Key modules of IL2PepScan are as follows:
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Predict: This module enables users to predict the IL-2 and non-IL-2 induction potential of given
peptide sequences.
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Design: This module generates all possible single mutants of a given peptide sequence and predicts
the IL-2 induction potential for each mutant.
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Protein Scan: This module generates all possible overlapping peptides from a given protein sequence
and predicts their IL-2 induction potential.