Literature DB >> 26202262

Computer-Aided Virtual Screening and Designing of Cell-Penetrating Peptides.

Ankur Gautam1, Kumardeep Chaudhary, Rahul Kumar, Gajendra Pal Singh Raghava.   

Abstract

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.

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Year:  2015        PMID: 26202262     DOI: 10.1007/978-1-4939-2806-4_4

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  10 in total

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Review 5.  Peptides with Dual Antimicrobial-Anticancer Activity: Strategies to Overcome Peptide Limitations and Rational Design of Anticancer Peptides.

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6.  The Cytotoxicity of RNase-Derived Peptides.

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8.  AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest.

Authors:  Balachandran Manavalan; Tae H Shin; Myeong O Kim; Gwang Lee
Journal:  Front Pharmacol       Date:  2018-03-27       Impact factor: 5.810

9.  iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction.

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Journal:  Front Immunol       Date:  2018-07-27       Impact factor: 7.561

10.  A Method for Predicting Hemolytic Potency of Chemically Modified Peptides From Its Structure.

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  10 in total

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