SMILES
Chemical and Physical Property Prediction (CPPP) is an algorithm based on RDKit to predict chemical and physical properties of cyclic peptides, such as Topological Polar Surface Area, Complexity, Log(P), Hydrogen Bond Donor Count, Hydrogen Bond Acceptor Count, Rotatable Bond Count, Drug likeness, and Fingerprints. The details of CPPP are available at dfwlab/cyclicpepedia on GitHub.
essential amino acids one-letter amino acid code
Peptide Sequence Properties are predicted by the "Peptides" package of R (Osorio, D., Rondon-Villarreal, P. & Torres, R. Peptides: A package for data mining of antimicrobial peptides. The R Journal. 7(1), 4–14 (2015).). It predicts more than 100 indices, such as the Boman index, Charge, Aliphatic index, Instability index, and Amino acid composition. The details of sequence property prediction are available at dfwlab/cyclicpepedia on GitHub.
Peptide Sequence Property Prediction may take some time.