TY - JOUR
T1 - Computer-aided virtual screening and designing of cell- penetrating peptides
AU - Gautam, Ankur
AU - Chaudhary, Kumardeep
AU - Kumar, Rahul
AU - Raghava, Gajendra Pal Singh
N1 - Publisher Copyright:
© Springer Science+Business Media New York 2015.
PY - 2015
Y1 - 2015
N2 - Cell-penetrating peptides (CPPs) have proven their potential as versatile drug delivery vehicles. Last decade has witnessed an unprecedented growth in CPP-based research, demonstrating the potential of CPPs as therapeutic candidates. In the past, many in silico algorithms have been developed for the prediction and screening of CPPs, which expedites the CPP-based research. In silico screening/prediction of CPPs followed by experimental validation seems to be a reliable, less time-consuming, and cost-effective approach. This chapter describes the prediction, screening, and designing of novel efficient CPPs using “CellPPD,” an in silico tool.
AB - Cell-penetrating peptides (CPPs) have proven their potential as versatile drug delivery vehicles. Last decade has witnessed an unprecedented growth in CPP-based research, demonstrating the potential of CPPs as therapeutic candidates. In the past, many in silico algorithms have been developed for the prediction and screening of CPPs, which expedites the CPP-based research. In silico screening/prediction of CPPs followed by experimental validation seems to be a reliable, less time-consuming, and cost-effective approach. This chapter describes the prediction, screening, and designing of novel efficient CPPs using “CellPPD,” an in silico tool.
KW - Cell-penetrating peptides
KW - Drug delivery system
KW - Machine learning approach
KW - Prediction
KW - Support vector machine
KW - Virtual screening
UR - https://www.scopus.com/pages/publications/84938089513
U2 - 10.1007/978-1-4939-2806-4_4
DO - 10.1007/978-1-4939-2806-4_4
M3 - Article
AN - SCOPUS:84938089513
SN - 1064-3745
VL - 1324
SP - 59
EP - 69
JO - Methods in Molecular Biology
JF - Methods in Molecular Biology
ER -