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Predicting peptide vaccine candidates against H1N1 influenza virus through theoretical approaches

Identification of potential epitopes that might activate the immune system has been facilitated by the employment of algorithms that use experimental data as templates. However, in order to prove the affinity and the map of interactions between the receptor (major histocompatibility complex, MHC, or...

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Published in:Immunologic research 2015-05, Vol.62 (1), p.3-15
Main Authors: Bello, Martiniano, Campos-Rodriguez, Rafael, Rojas-Hernandez, Saul, Contis-Montes de Oca, Arturo, Correa-Basurto, José
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container_title Immunologic research
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description Identification of potential epitopes that might activate the immune system has been facilitated by the employment of algorithms that use experimental data as templates. However, in order to prove the affinity and the map of interactions between the receptor (major histocompatibility complex, MHC, or T-cell receptor) and the potential epitope, further computational studies are required. Docking and molecular dynamics (MDs) simulations have been an effective source of generating structural information at molecular level in immunology. Herein, in order to provide a detailed understanding of the origins of epitope recognition and to select the best peptide candidate to develop an epitope-based vaccine, docking and MDs simulations in combination with MMGBSA free energy calculations and per-residue free energy decomposition were performed, taking as starting complexes those formed between four designed epitopes (P1–P4) from hemagglutinin (HA) of the H1N1 influenza virus and MHC-II anchored in POPC membrane. Our results revealed that the energetic contributions of individual amino acids within the pMHC-II complexes are mainly dictated by van der Waals interactions and the nonpolar part of solvation energy, whereas the electrostatic interactions corresponding to hydrogen bonds and salt bridges determine the binding specificity, being the most favorable interactions formed between p4 and MHC-II. Then, P1–P4 epitopes were synthesized and tested experimentally to compare theoretical and experimental results. Experimental results show that P4 elicited the highest strong humoral immune response to HA of the H1N1 and may induce antibodies that are cross-reactive to other influenza subtypes, suggesting that it could be a good candidate for the development of a peptide-based vaccine.
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subjects Allergology
Amino acids
Animals
Biomedical and Life Sciences
Biomedicine
Epitopes - administration & dosage
Epitopes - chemistry
Epitopes - immunology
Hemagglutinin Glycoproteins, Influenza Virus - immunology
Histocompatibility Antigens Class II - chemistry
Histocompatibility Antigens Class II - immunology
Immune system
Immunoglobulin G - blood
Immunology
Influenza A Virus, H1N1 Subtype
Influenza Vaccines - administration & dosage
Internal Medicine
Lipid Bilayers - chemistry
Medicine/Public Health
Molecular Docking Simulation
Molecular Dynamics Simulation
Peptides
Peptides - administration & dosage
Peptides - chemistry
Peptides - immunology
Phosphatidylcholines - chemistry
Rabbits
Swine flu
Vaccines
title Predicting peptide vaccine candidates against H1N1 influenza virus through theoretical approaches
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