creators_name: Kumar, Vinod
creators_name: Agrawal, Piyush
creators_name: Kumar, Rajesh
creators_name: Bhalla, Sherry
creators_name: Usmani, Salman Sadullah
creators_name: Varshney, Grish C
creators_name: Raghava, Gajendra P S
type: article
datestamp: 2019-03-25 15:07:34
lastmod: 2019-03-25 15:07:34
metadata_visibility: show
title: Prediction of Cell-Penetrating Potential of Modified Peptides Containing Natural and Chemically Modified Residues.
ispublished: pub
subjects: QR
keywords: Random Forest; SVM; antimicrobial peptide; chemical descriptors; in silico method; machine learning; modified cell-penetrating peptides
abstract: Designing drug delivery vehicles using cell-penetrating peptides is a hot area of research in the field of medicine. In the past, number of  methods have been developed for predicting cell-penetrating property of peptides containing natural residues. In this study, first time attempt has been made to predict cell-penetrating property of peptides containing natural and modified residues. The dataset used to develop prediction models, include structure and sequence of 732 chemically modified cell-penetrating peptides and an equal number of non-cell penetrating peptides. We analyzed the structure of both class of peptides and observed that positive charge groups, atoms, and residues are preferred in cell-penetrating peptides. In this study, models were developed to predict cell-penetrating peptides from its tertiary structure using a wide range of descriptors (2D, 3D descriptors, and fingerprints). Random Forest model developed by using PaDEL descriptors (combination of 2D, 3D, and fingerprints) achieved maximum accuracy of 95.10%, MCC of 0.90 and AUROC of 0.99 on the main dataset. The performance of model was also evaluated on validation/independent dataset which achieved AUROC of 0.98. In order to assist the scientific community, we have developed a web server "CellPPDMod" for predicting the cell-penetrating property of modified peptides (http://webs.iiitd.edu.in/raghava/cellppdmod/).
date: 2018-04-12
date_type: published
publication: Frontiers in microbiology
volume: 9
publisher: Frontiers Media S.A
pagerange: 725
refereed: TRUE
issn: 1664-302X
official_url: https://www.frontiersin.org/articles/10.3389/fmicb.2018.00725/full
citation:   Kumar, Vinod and Agrawal, Piyush and Kumar, Rajesh and Bhalla, Sherry and Usmani, Salman Sadullah and Varshney, Grish C and Raghava, Gajendra P S  (2018) Prediction of Cell-Penetrating Potential of Modified Peptides Containing Natural and Chemically Modified Residues.  Frontiers in microbiology, 9.  p. 725.  ISSN 1664-302X