scholarly journals Combinatorial Peptide Libraries: Mining for Cell-Binding Peptides

2013 ◽  
Vol 114 (2) ◽  
pp. 1020-1081 ◽  
Author(s):  
Bethany Powell Gray ◽  
Kathlynn C. Brown
2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Bifang He ◽  
Juanjuan Kang ◽  
Beibei Ru ◽  
Hui Ding ◽  
Peng Zhou ◽  
...  

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.


2000 ◽  
Vol 97 (23) ◽  
pp. 12487-12492 ◽  
Author(s):  
F. J. M. Detmers ◽  
F. C. Lanfermeijer ◽  
R. Abele ◽  
R. W. Jack ◽  
R. Tampe ◽  
...  

2002 ◽  
Vol 12 (11) ◽  
pp. 1473-1476 ◽  
Author(s):  
B Kundu ◽  
T Srinivasan ◽  
A. P Kesarwani ◽  
A Kavishwar ◽  
S. K Raghuwanshi ◽  
...  

2002 ◽  
Vol 48 (12) ◽  
pp. 2208-2216 ◽  
Author(s):  
Jari Leinonen ◽  
Ping Wu ◽  
Ulf-Håkan Stenman

Abstract Background: Prostate-specific antigen (PSA) is the most important marker for prostate cancer, but PSA concentrations determined by various assays can differ significantly because of differences in specificity of the antibodies used. To identify epitopes recognized by various monoclonal antibodies (MAbs) to PSA, we have isolated peptides that react with the paratopes of these. Methods: Six anti-PSA MAbs representing three major epitope groups were screened with five cyclic phage display peptide libraries. After selection, the peptide sequences were determined by sequencing of the relevant part of viral DNA. Binding of the phage peptides to the MAbs was monitored by immunoassay. Results: For each MAb, several paratope-binding peptides with distinct sequence motifs were identified, but only ∼10% showed similarity with the PSA sequence. Some of these correctly predicted the location of the epitopes. By sequential panning of the library with two closely related MAbs, we identified peptides reacting equally with both MAbs. When analyzed against a large panel of PSA MAbs, the peptides generally showed restricted specificity toward the MAb used for selection, but some peptides bound to several related MAbs. Conclusions: Most of the cyclic peptides selected with PSA MAbs are specific for the MAb used for selection and do not resemble any sequence on the antigen. Peptides reactive with two MAbs recognizing the same epitope can be obtained by sequential panning. This method can be used to predict the location of some epitopes, but additional methods are needed to confirm the result.


2006 ◽  
Vol 49 (11) ◽  
pp. 3430-3430 ◽  
Author(s):  
Dirk Wildemann ◽  
Frank Erdmann ◽  
Birte Hernandez Alvarez ◽  
Gerlind Stoller ◽  
Xiao Z. Zhou ◽  
...  

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