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An investigation of cell-penetrating peptides (CPPs) by using combination of Artificial Neural Networks (ANN) and Principle Component Analysis (PCA) revealed that the penetration capability (penetrating/non-penetrating) of 101 examined peptides can be predicted with accuracy of 80%-100%. The inputs of the ANN are the main characteristics classifying the penetration. These molecular characteristics (descriptors) were calculated for each peptide and they provide bio-chemical insights for the criteria of penetration. Deeper analysis of the PCA results also showed clear clusterization of the peptides according to their molecular features.

Original publication

DOI

10.2174/157340910791202478

Type

Journal article

Journal

Curr Comput Aided Drug Des

Publication Date

2010

Volume

6

Pages

79 - 89

Keywords

Animals, Cell-Penetrating Peptides, Cells, Computer Simulation, Humans, Neural Networks, Computer, Principal Component Analysis