This module contains machine learning-based algorithms that perform the prediction of blood-brain barrier penetrating peptides (BrainPepPass), cell-penetrating peptides (BChemRF-CPPred), and quorum sensing peptides (QuorumPep-Pred). This module can receive synthetic and natural (non-modified) peptides using as input PDB and FASTA formats.
To use this module, firstly the user must select the algorithm. The second step is the upload of peptides files (FASTA or PDB) using one of the options below. Then, the user must click on the button 'SUBMIT' to start the prediction, or click on 'RESET' to clean the uploaded files.
Select the algorithm
BrainPepPass:
de Oliveira ECL, Hirmz H, Wynendaele E, Seixas Feio JA, Moreira IMS, da Costa KS, Lima AH, De Spiegeleer B, de Sales Júnior CS.
BrainPepPass: A Framework Based on Supervised Dimensionality Reduction for Predicting Blood-Brain Barrier-Penetrating Peptides.
J Chem Inf Model. 2024 Apr 8;64(7):2368-2382. PMID: 38054399.
DOI: 10.1021/acs.jcim.3c00951
ConvBoostCPPred:
Seixas Feio JA, de Oliveira ECL, de Sales CS Junior, da Costa KS, E Lima AHL.
Investigating molecular descriptors in cell-penetrating peptides prediction with deep learning: Employing N, O, and hydrophobicity according to the Eisenberg scale.
PLoS One. 2024 Jun 13;19(6):e0305253. PMID: 38870192; PMCID: PMC11175476.
DOI: 10.1371/journal.pone.0305253