Abstract:
This thesis presents a repository CancerPPD2, which is an updated version of CancerPPD, developed to maintain comprehensive information about An-ticancer peptides and proteins. It contains 6521 entries, each entry provides detailed information about an anticancer activity of peptides or proteins that include origin of the peptide, cancer cell line, type of cancer, peptide sequence, and structure. These anticancer peptides have been tested against 392 types of cancer cell lines and 28 types of cancer-associated tissues. In addition to natural anticancer peptides, CancerPPD2 contains 781 entries for chemically modified and 3018 entries for N-/C- terminus modified anticancer peptides. Few entries are also linked with 47 clinical studies and have provided the cross reference to Uniprot and NCT. On average, CancerPPD2 contains around 85% more information than its previous version, CancerPPD. The structures of these anticancer peptides and proteins were either obtained from the Protein Data Bank (PDB) or predicted using PEPstrMOD, I-TASSER, or AlphaFold. A wide range of tools have been integrated into CancerPPD2 for data retrieval and similarity searches. Additionally, we integrated a REST API into this repository to facilitate automatic data retrieval via programs. In this study, we have also made an initial attempt to develop a method for classifying chemically modified anticancer peptides. To the best of our knowledge, no previous efforts have been made in this direction, making this the first study to address this unexplored aspect. This work lays the foundation for future computational models aimed at understanding and predicting the functional behaviour of modified anticancer peptides.
