Dataset Information

Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks.

ABSTRACT: The dependency between the primary structure of HIV envelope glycoproteins (ENV) and the neutralization data for given antibodies is very complicated and depends on a large number of factors, such as the binding affinity of a given antibody for a given ENV protein, and the intrinsic infection kinetics of the viral strain. This paper presents a first approach to learning these dependencies using an artificial feedforward neural network which is trained to learn from experimental data. The results presented here demonstrate that the trained neural network is able to generalize on new viral strains and to predict reliable values of neutralizing activities of given antibodies against HIV-1.

SUBMITTER: Buiu C

PROVIDER: S-EPMC5085742 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks.

Buiu Cătălin C Putz Mihai V MV Avram Speranta S

International journal of molecular sciences 20161011 10

The dependency between the primary structure of HIV envelope glycoproteins (ENV) and the neutralization data for given antibodies is very complicated and depends on a large number of factors, such as the binding affinity of a given antibody for a given ENV protein, and the intrinsic infection kinetics of the viral strain. This paper presents a first approach to learning these dependencies using an artificial feedforward neural network which is trained to learn from experimental data. The results ...[more]

PMID: 27727189

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Project description:Although effective hepatitis C virus (HCV) antivirals are on the horizon, a global prophylactic vaccine for HCV remains elusive. The diversity of the virus is a major concern for vaccine development; there are 7 major genotypes of HCV found globally. Therefore, a successful vaccine will need to protect against HCV infection by all genotypes. Despite the diversity, many monoclonal antibodies (MAbs) with broadly cross-neutralizing activity have been described, suggesting the presence of conserved epitopes that can be targeted to prevent infection. Similarly, a vaccine comprising recombinant envelope glycoproteins (rE1E2) derived from the genotype 1a HCV-1 strain has been shown to be capable of eliciting cross-neutralizing antibodies in guinea pigs, chimpanzees, and healthy human volunteers. In order to investigate the basis for this cross-neutralization, epitope mapping of anti-E1E2 antibodies present within antisera from goats and humans immunized with HCV-1 rE1E2 was conducted through peptide mapping and competition studies with a panel of cross-neutralizing MAbs targeting various epitopes within E1E2. The immunized-goat antiserum was shown to compete with the binding of all MAbs tested (AP33, HC33.4, HC84.26, 1:7, AR3B, AR4A, AR5A, IGH526, and A4). Antisera showed the best competition against HC84.26 and AR3B and the weakest competition against AR4A. Furthermore, antisera from five immunized human vaccinees were shown to compete with five preselected MAbs (AP33, AR3B, AR4A, AR5A, and IGH526). These data show that immunization with HCV-1 rE1E2 elicits antibodies targeting multiple cross-neutralizing epitopes. Our results further support the use of such a vaccine antigen to induce cross-genotype neutralization.An effective prophylactic vaccine for HCV is needed for optimal control of the disease burden. The high diversity of HCV has posed a challenge for developing vaccines that elicit neutralizing antibodies for protection against infection. Despite this, we have previously shown that a vaccine comprising recombinant envelope glycoproteins derived from a single genotype 1a strain was capable of eliciting a cross-neutralizing antibody response in human volunteers. Here, we have used competition binding assays and peptide binding assays to show that antibodies present in the antisera from vaccinated goats and humans bind epitopes overlapping with those of a variety of well-characterized cross-neutralizing monoclonal antibodies. This provides a mechanism for the cross-neutralizing human antisera: antibodies present in the antisera bind to conserved regions associated with cross-neutralization. Importantly, this work provides further support for a vaccine comprising recombinant envelope glycoproteins, perhaps in a formulation with a vaccine component eliciting strong anti-HCV CD4(+) and CD8(+) T cell responses.

Dataset Information

Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks.

Publications

Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks.

Similar Datasets

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