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Protease cleavage sites in HIV-1 gp120 recognized by antigen processing enzymes are conserved and located at receptor binding sites.

ABSTRACT: The identification of vaccine immunogens able to elicit broadly neutralizing antibodies (bNAbs) is a major goal in HIV vaccine research. Although it has been possible to produce recombinant envelope glycoproteins able to adsorb bNAbs from HIV-positive sera, immunization with these proteins has failed to elicit antibody responses effective against clinical isolates of HIV-1. Thus, the epitopes recognized by bNAbs are present on recombinant proteins, but they are not immunogenic. These results led us to consider the possibility that changes in the pattern of antigen processing might alter the immune response to the envelope glycoprotein to better elicit protective immunity. In these studies, we have defined protease cleavage sites on HIV gp120 recognized by three major human proteases (cathepsins L, S, and D) important for antigen processing and presentation. Remarkably, six of the eight sites identified in gp120 were highly conserved and clustered in regions of the molecule associated with receptor binding and/or the binding of neutralizing antibodies. These results suggested that HIV may have evolved to take advantage of major histocompatibility complex (MHC) class II antigen processing enzymes in order to evade or direct the antiviral immune response.

SUBMITTER: Yu B

PROVIDER: S-EPMC2812349 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Protease cleavage sites in HIV-1 gp120 recognized by antigen processing enzymes are conserved and located at receptor binding sites.

Yu Bin B Fonseca Dora P A J DP O'Rourke Sara M SM Berman Phillip W PW

Journal of virology 20091125 3

The identification of vaccine immunogens able to elicit broadly neutralizing antibodies (bNAbs) is a major goal in HIV vaccine research. Although it has been possible to produce recombinant envelope glycoproteins able to adsorb bNAbs from HIV-positive sera, immunization with these proteins has failed to elicit antibody responses effective against clinical isolates of HIV-1. Thus, the epitopes recognized by bNAbs are present on recombinant proteins, but they are not immunogenic. These results led ...[more]

PMID: 19939935

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Project description:The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s). Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database) with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate sequence using machine learning techniques. It is freely available at http://lightning.med.monash.edu.au/PROSPER/.

Dataset Information

Protease cleavage sites in HIV-1 gp120 recognized by antigen processing enzymes are conserved and located at receptor binding sites.

Publications

Protease cleavage sites in HIV-1 gp120 recognized by antigen processing enzymes are conserved and located at receptor binding sites.

Similar Datasets

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