Computational Analysis Comparison Prediction of Anticancer Peptide (ACP)

Abstract

Abstract: Anticancer peptides (ACPs) contain short peptides composed of 10–60 amino acids that can inhibit tumors cell proliferation or migration, or suppress the formation of tumors blood vessels, and are less likely to cause drug resistance. The aforementioned merits make ACPs the most promising anti-cancer candidate. ACPs may be degraded by proteases and result in cytotoxicity in many cases. To overcome these drawbacks, a plethora of research has focused on the reconstruction or modification of ACPs to improve their anti-cancer activity, while reducing their cytotoxicity. ACPs modification mainly includes main chain reconstruction and side-chain modification. After summarizing the classification and mechanism of action of ACPs, this paper focuses on recent development and progress in their reconstruction and modification. The information collected here may provide some ideas for further research on ACPs, in particular their modification. ACPs were extracted from various search engines like PubMed, Google scholar and Patent lens. Specific searches were carried out using a combination of keywords like ‘ACPs’, ‘antitumor peptides’, ‘anti-angiogenic peptides’, ‘anti-metastatic peptides’ and ‘host defence peptides. The comprehensive information related to a peptide like its source of origin, nature of the peptide, anticancer activity, N- and Cterminal modifications, conformation, etc. Additionally, CancerPPD provides information on around 249 types of cancer cell lines and 16 different assays used for testing the ACPs. In natural peptides, CancerPPD contains peptides having non-natural, chemically modified residues and D-amino acids. Besides this primary information, CancerPPD stores predicted tertiary structures as well as peptide sequences in SMILES format.