Angiogenesis is the process of formation of new blood vessels to make a supply of nutrients and a waste disposal pathway. This physiological process is a vital event in cancer progression-transition tumors from a benign state to a malignant one- and spread of a tumor (metastasis). Nowdays, decreasing or inhibiting angiogenesis is a new area in cancer therapy and is in the center of other angiogenesis-dependent disease therapy. Recognition the anti-angiogenic peptides has stimulated great interest among researchers in the cancer treatment field during recent years.
A user-friendly web server for the prediction of anti-angiogenic peptides. A user can submit the peptide sequence in the ‘Predict’ module of the web server and can predict whether his/her peptide has anti-angiogenic property or not. User can also get the single mutant analogs of the submitted peptide along with their prediction. AntiAngioPred will also help a user to identify minimum mutations and their location in a peptide sequence so as to have anti-angiogenic properties in that peptide. If a user has multiple peptides then ‘Multiple Peptide’ module helps him/her to predict the anti-angiogenic nature of all of his/her peptides using a single submission form.
Identifies anti-angiogenic peptides. AntAngioCOOL can serve to determine pseudo amino acid composition, k-mer composition, physico-chemical profile and atomic profile. It was construct thanks to a machine learning method. This tool was developed on the basis of a comparison between 227 different classifiers, and then a selection of three classifiers that show good performance in sensitivity, specificity and accuracy.