iIL13Pred: Improved prediction of IL-13 inducing peptides



Arora P, Periwal N, Goyal Y, Sood V, Kaur B. iIL13Pred: improved prediction of IL-13 inducing peptides using popular machine learning classifiers. BMC Bioinformatics. 2023 Apr 11;24(1):141. doi: 10.1186/s12859-023-05248-6. PMID: 37041520; PMCID: PMC10088697.

Welcome to iIL13Pred




Interleukin (IL)-13 is a pleiotropic cytokine that is secreted by T-Helper 2 cells, basophils, mast cells, eosinophils, and natural killer cells. IL-13 is known to be associated with a number of infectious and non-infectious diseases. Interestingly, the recent association of IL-13 with COVID-19 severity has sparked interest in this cytokine. Therefore prediction and characterization of new molecules/peptides which can regulate IL-13 induction might lead to novel therapeutics.



Major features of iIL13Pred are as follows:

  1. Predict : The user can use this module to predict whether the given peptide sequence can induce IL-13 or not.

  2. Design : This module allows the user to generate all the possible single mutants of a given peptide and then predict whether the mutants have IL-13 induction activity or not. This module generates all the mutants of a given peptide sequence. Then IL-13 induction ability of these peptides is predicted.

  3. Protein Scan : This module generates all the possible overlapping peptides of a given protein sequence. These peptide sequences are then predicted to induce IL-13.