In the past few decades, a large number of cell-penetrating peptides (CPPs) have been discovered. These CPPs have a wide range of applications including drug delivery vehicles. Numerous in silico tools have been developed over the years to design and predict the cell-penetrating peptides that contain natural amino acids. The majority of natural cell-penetrating peptides have several limitations including stability, immunogenicity as well as got entrapped in the cell's endosomes. The chemical modification is commonly used to most of these limitations. An in silico tool called CellPPDMod have been developed by our group to predict cell-penetration potential of chemically modified peptides. This chapter is dedicated for designing therapeutically important cell-penetrating peptides using CellPPDMod ( http://webs.iiitd.edu.in/raghava/cellppdmod/ ).
Keywords: Chemical modified cell-penetrating peptides; Drug delivery vehicles; Machine learning (prediction).
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