ArticleProtein engineering, design & selection : PEDS2017
Deep sequencing of phage-displayed peptide libraries reveals sequence motif that detects norovirus.
Article in Protein engineering, design & selection : PEDS, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Identification of Antibacterial Cyclic Peptides with a High-Throughput Cell-Based Dropout Screen.Journal of the American Chemical Society · 2026Article
- Next Generation SICLOPPS Screening for the Identification of Inhibitors of the HIF-1α/HIF-1β Protein-Protein Interaction.ACS chemical biology · 2024Article
- Depth of Sequencing Plays a Determining Role in the Characterization of Phage Display Peptide Libraries by NGS.International journal of molecular sciences · 2023Article
- In vivo phage display: identification of organ-specific peptides using deep sequencing and differential profiling across tissues.Nucleic acids research · 2021Article
- Article
- Mapping Protein-Protein Interaction Interface Peptides with Jun-Fos Assisted Phage Display and Deep Sequencing.ACS synthetic biology · 2020Article
- Phage display peptide libraries: deviations from randomness and correctives.Nucleic acids research · 2018Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Norovirus infections are the leading cause of non-bacterial gastroenteritis and result in about 21 million new cases and $2 billion in costs per year in the United States. Existing diagnostics have limited feasibility for point-of-care applications, so there is a clear need for more reliable, rapid, and simple-to-use diagnostic tools in order to contain outbreaks and prevent inappropriate treatments. In this study, a combination of phage display technology, deep sequencing and computational analysis was used to identify 12-mer peptides with specific binding to norovirus genotype GI.1 virus-like particles (VLPs). After biopanning, phage populations were sequenced and analyzed to identify a consensus peptide motif-YRSWXP. Two 12-mer peptides containing this sequence, NV-O-R5-3 and NV-O-R5-6, were further characterized to evaluate the motif's functional ability to detect VLPs and virus. Results indicated that these peptides effectively detect GI.1 VLPs in solid-phase peptide arrays, ELISAs and dot blots. Further, their specificity for the S-domain of the major capsid protein enables them to detect a wide range of GI and GII norovirus genotypes. Both peptides were able to detect virus in norovirus-positive clinical stool samples. Overall, the work reported here demonstrates the application of phage display coupled with next generation sequencing and computational analysis to uncover peptides with specific binding ability to a target protein for diagnostic applications. Further, the reagents characterized here can be integrated into existing diagnostic formats to detect clinically relevant genotypes of norovirus in stool.
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Registered trials
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