CPPpred: prediction of cell penetrating peptides.
Cell penetrating peptides (CPPs) are attracting much attention as a means of overcoming the inherently poor cellular uptake of various bioactive molecules. Here, we introduce CPPpred, a web server for the prediction of CPPs using a N-to-1 neural network. The server takes one or more peptide sequences, between 5 and 30 amino acids in length, as input and returns a prediction of how likely each peptide is to be cell penetrating. CPPpred was developed with redundancy reduced training and test sets, offering an advantage over the only other currently available CPP prediction method.
Complex and Adaptive Systems Laboratory, Conway Institute of Biomolecular and Biomedical Science, School of Medicine and Medical Science, Food For Health Ireland and School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland.
Thérèse A
TA
Holton
Gianluca
G
Pollastri
Denis C
DC
Shields
Catherine
C
Mooney
D057846:Cell-Penetrating Peptides / Q000737:chemistry* / Q000378:metabolism; D019295:Computational Biology; D030562:Databases, Protein; D006801:Humans; D020407:Internet; D016571:Neural Networks, Computer; D020539:Sequence Analysis, Protein; D012984:Software
D057846:Cell-Penetrating Peptides