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      Experimental Validation of Multi-Epitope Peptides Including Promising MHC Class I- and II-Restricted Epitopes of Four Known Leishmania infantum Proteins

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          Abstract

          Leishmaniasis is a significant worldwide health problem for which no vaccine exists. Activation of CD4 + and CD8 + T cells is crucial for the generation of protective immunity against parasite. Recent trend in vaccine design has been shifted to epitope-based vaccines that are more specific, safe, and easy to produce. In the present study, four known antigenic Leishmania infantum proteins, cysteine peptidase A (CPA), histone H1, KMP-11, and Leishmania eukaryotic initiation factor (LeIF) were analyzed for the prediction of binding epitopes to H2 d MHC class I and II molecules, using online available algorithms. Based on in silico analysis, eight peptides including highly scored MHC class I- and II-restricted epitopes were synthesized. Peptide immunogenicity was validated in MHC compatible BALB/c mice immunized with each synthetic peptide emulsified in complete Freund’s adjuvant/incomplete Freund’s adjuvant. CPA_p2, CPA_p3, H1_p1, and LeIF_p6 induced strong spleen cell proliferation upon in vitro peptide re-stimulation. In addition, the majority of the peptides, except of LeIF_p1 and KMP-11_p1, induced IFN-γ secretion, while KMP-11_p1 indicated a suppressive effect on IL-10 production. CPA_p2, CPA_p3, LeIF_p3, and LeIF_p6 induced IFN-γ-producing CD4 + T cells indicating a T H1-type response. In addition, CPA_p2, CPA_p3, and H1_p1 induced also the induction of CD8 + T cells. The induction of peptide-specific IgG in immunized mice designated also the existence of B cell epitopes in peptide sequences. Combining immunoinformatic tools and experimental validation, we demonstrated that CPA_p2, CPA_p3, H1_p1, H1_p3, CPA_p2, LeIF_p3, and LeIF_p6 are likely to include potential epitopes for the induction of protective cytotoxic and/or T H1-type immune responses supporting the feasibility of peptide-based vaccine development for leishmaniasis.

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          M-1/M-2 macrophages and the Th1/Th2 paradigm.

          Evidence is provided that macrophages can make M-1 or M-2 responses. The concept of M-1/M-2 fomented from observations that macrophages from prototypical Th1 strains (C57BL/6, B10D2) are more easily activated to produce NO with either IFN-gamma or LPS than macrophages from Th2 strains (BALB/c, DBA/2). In marked contrast, LPS stimulates Th2, but not Th1, macrophages to increase arginine metabolism to ornithine. Thus, M-1/M-2 does not simply describe activated or unactivated macrophages, but cells expressing distinct metabolic programs. Because NO inhibits cell division, while ornithine can stimulate cell division (via polyamines), these results also indicate that M-1 and M-2 responses can influence inflammatory reactions in opposite ways. Macrophage TGF-beta1, which inhibits inducible NO synthase and stimulates arginase, appears to play an important role in regulating the balance between M-1 and M-2. M-1/M-2 phenotypes are independent of T or B lymphocytes because C57BL/6 and BALB/c NUDE or SCID macrophages also exhibit M-1/M-2. Indeed, M-1/M-2 proclivities are magnified in NUDE and SCID mice. Finally, C57BL/6 SCID macrophages cause CB6F1 lymphocytes to increase IFN-gamma production, while BALB/c SCID macrophages increase TGF-beta production. Together, the results indicate that M-1- or M-2-dominant macrophage responses can influence whether Th1/Th2 or other types of inflammatory responses occur.
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            ClusPro: a fully automated algorithm for protein-protein docking.

            ClusPro (http://nrc.bu.edu/cluster) represents the first fully automated, web-based program for the computational docking of protein structures. Users may upload the coordinate files of two protein structures through ClusPro's web interface, or enter the PDB codes of the respective structures, which ClusPro will then download from the PDB server (http://www.rcsb.org/pdb/). The docking algorithms evaluate billions of putative complexes, retaining a preset number with favorable surface complementarities. A filtering method is then applied to this set of structures, selecting those with good electrostatic and desolvation free energies for further clustering. The program output is a short list of putative complexes ranked according to their clustering properties, which is automatically sent back to the user via email.
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              How good is automated protein docking?

              The protein docking server ClusPro has been participating in critical assessment of prediction of interactions (CAPRI) since its introduction in 2004. This article evaluates the performance of ClusPro 2.0 for targets 46-58 in Rounds 22-27 of CAPRI. The analysis leads to a number of important observations. First, ClusPro reliably yields acceptable or medium accuracy models for targets of moderate difficulty that have also been successfully predicted by other groups, and fails only for targets that have few acceptable models submitted. Second, the quality of automated docking by ClusPro is very close to that of the best human predictor groups, including our own submissions. This is very important, because servers have to submit results within 48 h and the predictions should be reproducible, whereas human predictors have several weeks and can use any type of information. Third, while we refined the ClusPro results for manual submission by running computationally costly Monte Carlo minimization simulations, we observed significant improvement in accuracy only for two of the six complexes correctly predicted by ClusPro. Fourth, new developments, not seen in previous rounds of CAPRI, are that the top ranked model provided by ClusPro was acceptable or better quality for all these six targets, and that the top ranked model was also the highest quality for five of the six, confirming that ranking models based on cluster size can reliably identify the best near-native conformations. Copyright © 2013 Wiley Periodicals, Inc.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                10 June 2014
                2014
                : 5
                : 268
                Affiliations
                [1] 1Laboratory of Cellular Immunology, Department of Microbiology, Hellenic Pasteur Institute , Athens, Greece
                Author notes

                Edited by: Hira Nakhasi, US Food and Drug Administration, USA

                Reviewed by: Paola Massari, Boston University, USA; Syamal Roy, CSIR-Indian Institute of Chemical Biology, India

                *Correspondence: Evdokia Karagouni, Laboratory of Cellular Immunology, Department of Microbiology, Hellenic Pasteur Institute, 127 Vas. Sofias Avenue, Athens 115 21, Greece e-mail: ekaragouni@ 123456pasteur.gr

                Evita Athanasiou and Olga Koutsoni have contributed equally to this work.

                This article was submitted to Immunotherapies and Vaccines, a section of the journal Frontiers in Immunology.

                Article
                10.3389/fimmu.2014.00268
                4051127
                24959167
                de7e591c-3263-4c6f-b726-6906f825a088
                Copyright © 2014 Agallou, Athanasiou, Koutsoni, Dotsika and Karagouni.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 March 2014
                : 25 May 2014
                Page count
                Figures: 4, Tables: 4, Equations: 0, References: 94, Pages: 16, Words: 10497
                Categories
                Immunology
                Original Research

                Immunology
                in silico analysis,cysteine peptidase a,histone h1,kinetoplastid membrane protein 11,leishmania eukaryotic initiation factor,lymphocyte proliferation,cd8+ifn-γ+ t cells,cd4+ifn-γ+ t cells

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