BChemRF-CPPred (Beyond Chemical Rules-based Framework for CPP Prediction) is a machine learning-based framework developed to predict cell-penetrating peptides (CPPs) using algorithms trained with structure-based and sequence-based descriptors grouped in Feature Compositions (FCs). BChemRF-CPPred accepts both primary and tertiary peptide structures in the form of FASTA and PDB files, respectively.
The algorithm version that uses tertiary structures satisfactorily predicts peptides with residues containing chemical modifications. The user can also obtain peptide structures in PDB using their amino acid sequences in other webservers, such as PEP-FOLD and CABS-FOLD.
For more information to set the framework parameters, please read the ‘How to use’ page, and for more information about the framework and the applied FCs, read the ‘About’ page.
Upload your peptides to begin.
You can enable ‘Demonstration mode’ instead to use sample peptides as input.