SABinder: A Web Service for Predicting Streptavidin-Binding Peptides

Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylate...

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Main Authors:	He, Bifang, Kang, Juanjuan, Ru, Beibei, Ding, Hui, Zhou, Peng, Huang, Jian
Format:	Online
Language:	English
Published:	Hindawi Publishing Corporation 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005764/

id	pubmed-5005764
recordtype	oai_dc
spelling	pubmed-50057642016-09-08 SABinder: A Web Service for Predicting Streptavidin-Binding Peptides He, Bifang Kang, Juanjuan Ru, Beibei Ding, Hui Zhou, Peng Huang, Jian Research Article Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community. Hindawi Publishing Corporation 2016 2016-08-17 /pmc/articles/PMC5005764/ /pubmed/27610387 http://dx.doi.org/10.1155/2016/9175143 Text en Copyright © 2016 Bifang He et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	He, Bifang Kang, Juanjuan Ru, Beibei Ding, Hui Zhou, Peng Huang, Jian
spellingShingle	He, Bifang Kang, Juanjuan Ru, Beibei Ding, Hui Zhou, Peng Huang, Jian SABinder: A Web Service for Predicting Streptavidin-Binding Peptides
author_facet	He, Bifang Kang, Juanjuan Ru, Beibei Ding, Hui Zhou, Peng Huang, Jian
author_sort	He, Bifang
title	SABinder: A Web Service for Predicting Streptavidin-Binding Peptides
title_short	SABinder: A Web Service for Predicting Streptavidin-Binding Peptides
title_full	SABinder: A Web Service for Predicting Streptavidin-Binding Peptides
title_fullStr	SABinder: A Web Service for Predicting Streptavidin-Binding Peptides
title_full_unstemmed	SABinder: A Web Service for Predicting Streptavidin-Binding Peptides
title_sort	sabinder: a web service for predicting streptavidin-binding peptides
description	Streptavidin is sometimes used as the intended target to screen phage-displayed combinatorial peptide libraries for streptavidin-binding peptides (SBPs). More often in the biopanning system, however, streptavidin is just a commonly used anchoring molecule that can efficiently capture the biotinylated target. In this case, SBPs creeping into the biopanning results are not desired binders but target-unrelated peptides (TUP). Taking them as intended binders may mislead subsequent studies. Therefore, it is important to find if a peptide is likely to be an SBP when streptavidin is either the intended target or just the anchoring molecule. In this paper, we describe an SVM-based ensemble predictor called SABinder. It is the first predictor for SBP. The model was built with the feature of optimized dipeptide composition. It was observed that 89.20% (MCC = 0.78; AUC = 0.93; permutation test, p < 0.001) of peptides were correctly classified. As a web server, SABinder is freely accessible. The tool provides a highly efficient way to exclude potential SBP when they are TUP or to facilitate identification of possibly new SBP when they are the desired binders. In either case, it will be helpful and can benefit related scientific community.
publisher	Hindawi Publishing Corporation
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005764/
_version_	1613639685405409280

SABinder: A Web Service for Predicting Streptavidin-Binding Peptides

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