AmylPepPred: Amyloidogenic Peptide Prediction tool

We present an efficient computational architecture designed using supervised machine learning model to predict amyloid fibrilforming protein segments, named AmylPepPred. The proposed prediction model is based on bio-physio-chemical properties ofprimary sequences and auto-correlation function of their amino acid indices. AmylPepPred provides a user friendly web interfacefor the researchers to easily observe the fibril forming and non-fibril forming hexmers in a given protein sequence. We expect thatthis stratagem will be highly encouraging in discovering fibril forming regions in proteins thereby benefit in finding therapeuticagents that specifically aim these sequences for the inhibition and cure of amyloid illnesses.

Availability

AmylPepPred is available freely for academic use at www.zoommicro.in/amylpeppred