학술논문
Combination of Experimental and Bioinformatic Approaches for Identification of Immunologically Relevant Protein-Peptide Interactions.
Document Type
Academic Journal
Author
Debeljak J; Laboratory for Clinical Immunology and Molecular Genetics, University Clinic of Respiratory and Allergic Diseases Golnik, 4204 Golnik, Slovenia.; Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia.; Korošec P; Laboratory for Clinical Immunology and Molecular Genetics, University Clinic of Respiratory and Allergic Diseases Golnik, 4204 Golnik, Slovenia.; Faculty of Pharmacy, University of Ljubljana, 1000 Ljubljana, Slovenia.; Šelb J; Laboratory for Clinical Immunology and Molecular Genetics, University Clinic of Respiratory and Allergic Diseases Golnik, 4204 Golnik, Slovenia.; Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia.; Rijavec M; Laboratory for Clinical Immunology and Molecular Genetics, University Clinic of Respiratory and Allergic Diseases Golnik, 4204 Golnik, Slovenia.; Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia.; Košnik M; Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia.; Allergy Department, University Clinic of Respiratory and Allergic Diseases Golnik, 4204 Golnik, Slovenia.; Lunder M; Faculty of Pharmacy, University of Ljubljana, 1000 Ljubljana, Slovenia.
Source
Publisher: MDPI Country of Publication: Switzerland NLM ID: 101596414 Publication Model: Electronic Cited Medium: Internet ISSN: 2218-273X (Electronic) Linking ISSN: 2218273X NLM ISO Abbreviation: Biomolecules Subsets: MEDLINE
Subject
Language
English
Abstract
Protein-peptide interactions are an essential player in cellular processes and, thus, of great interest as potential therapeutic agents. However, identifying the protein's interacting surface has been shown to be a challenging task. Here, we present a methodology for protein-peptide interaction identification, implementing phage panning, next-generation sequencing and bioinformatic analysis. One of the uses of this methodology is identification of allergen epitopes, especially suitable for globular inhaled and venom allergens, where their binding capability is determined by the allergen's conformation, meaning their interaction cannot be properly studied when denatured. A Ph.D. commercial system based on the M13 phage vector was used for the panning process. Utilization of various bioinformatic tools, such as PuLSE, SAROTUP, MEME, Hammock and Pepitope, allowed us to evaluate a large amount of obtained data. Using the described methodology, we identified three peptide clusters representing potential epitopes on the major wasp venom allergen Ves v 5.