Literature DB >> 29956612

Development and Application of Computational Methods in Phage Display Technology.

Bifang He1,2, Anthony Mackitz Dzisoo1, Ratmir Derda3, Jian Huang1.   

Abstract

BACKGROUND: Phage display is a powerful and versatile technology for the identification of peptide ligands binding to multiple targets, which has been successfully employed in various fields, such as diagnostics and therapeutics, drug-delivery and material science. The integration of next generation sequencing technology with phage display makes this methodology more productive. With the widespread use of this technique and the fast accumulation of phage display data, databases for these data and computational methods have become an indispensable part in this community. This review aims to summarize and discuss recent progress in the development and application of computational methods in the field of phage display.
METHODS: We undertook a comprehensive search of bioinformatics resources and computational methods for phage display data via Google Scholar and PubMed. The methods and tools were further divided into different categories according to their uses.
RESULTS: We described seven special or relevant databases for phage display data, which provided an evidence-based source for phage display researchers to clean their biopanning results. These databases can identify and report possible target-unrelated peptides (TUPs), thereby excluding false-positive data from peptides obtained from phage display screening experiments. More than 20 computational methods for analyzing biopanning data were also reviewed. These methods were classified into computational methods for reporting TUPs, for predicting epitopes and for analyzing next generation phage display data.
CONCLUSION: The current bioinformatics archives, methods and tools reviewed here have benefitted the biopanning community. To develop better or new computational tools, some promising directions are also discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Keywords:  Phage display; computational method; database; epitope prediction; mimotope; next-generation sequencing; target-unrelated peptide.

Year:  2019        PMID: 29956612     DOI: 10.2174/0929867325666180629123117

Source DB:  PubMed          Journal:  Curr Med Chem        ISSN: 0929-8673            Impact factor:   4.530


  6 in total

1.  Discovery of vascular Rho kinase (ROCK) inhibitory peptides.

Authors:  Reza Abbasgholizadeh; Hua Zhang; John W Craft; Robert M Bryan; Steven J Bark; James M Briggs; Robert O Fox; Anton Agarkov; Warren E Zimmer; Scott R Gilbertson; Robert J Schwartz
Journal:  Exp Biol Med (Maywood)       Date:  2019-05-27

2.  TUPDB: Target-Unrelated Peptide Data Bank.

Authors:  Bifang He; Shanshan Yang; Jinjin Long; Xue Chen; Qianyue Zhang; Hui Gao; Heng Chen; Jian Huang
Journal:  Interdiscip Sci       Date:  2021-05-16       Impact factor: 2.233

3.  InteractomeSeq: a web server for the identification and profiling of domains and epitopes from phage display and next generation sequencing data.

Authors:  Simone Puccio; Giorgio Grillo; Arianna Consiglio; Maria Felicia Soluri; Daniele Sblattero; Diego Cotella; Claudio Santoro; Sabino Liuni; Gianluca De Bellis; Enrico Lugli; Clelia Peano; Flavio Licciulli
Journal:  Nucleic Acids Res       Date:  2020-07-02       Impact factor: 16.971

4.  SAROTUP: a suite of tools for finding potential target-unrelated peptides from phage display data.

Authors:  Bifang He; Heng Chen; Ning Li; Jian Huang
Journal:  Int J Biol Sci       Date:  2019-06-02       Impact factor: 6.580

Review 5.  High-Throughput Monoclonal Antibody Discovery from Phage Libraries: Challenging the Current Preclinical Pipeline to Keep the Pace with the Increasing mAb Demand.

Authors:  Nicola Zambrano; Guendalina Froechlich; Dejan Lazarevic; Margherita Passariello; Alfredo Nicosia; Claudia De Lorenzo; Marco J Morelli; Emanuele Sasso
Journal:  Cancers (Basel)       Date:  2022-03-04       Impact factor: 6.639

6.  PDL1Binder: Identifying programmed cell death ligand 1 binding peptides by incorporating next-generation phage display data and different peptide descriptors.

Authors:  Bifang He; Bowen Li; Xue Chen; Qianyue Zhang; Chunying Lu; Shanshan Yang; Jinjin Long; Lin Ning; Heng Chen; Jian Huang
Journal:  Front Microbiol       Date:  2022-07-15       Impact factor: 6.064

  6 in total

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