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  • Review
  • Open Access

BioAfrica's HIV-1 Proteomics Resource: Combining protein data with bioinformatics tools

  • 1Email author,
  • 1,
  • 2,
  • 1,
  • 1 and
  • 1, 3

  • Received: 30 September 2004
  • Accepted: 09 March 2005
  • Published:


Most Internet online resources for investigating HIV biology contain either bioinformatics tools, protein information or sequence data. The objective of this study was to develop a comprehensive online proteomics resource that integrates bioinformatics with the latest information on HIV-1 protein structure, gene expression, post-transcriptional/post-translational modification, functional activity, and protein-macromolecule interactions. The BioAfrica HIV-1 Proteomics Resource is a website that contains detailed information about the HIV-1 proteome and protease cleavage sites, as well as data-mining tools that can be used to manipulate and query protein sequence data, a BLAST tool for initiating structural analyses of HIV-1 proteins, and a proteomics tools directory. The Proteome section contains extensive data on each of 19 HIV-1 proteins, including their functional properties, a sample analysis of HIV-1HXB2, structural models and links to other online resources. The HIV-1 Protease Cleavage Sites section provides information on the position, subtype variation and genetic evolution of Gag, Gag-Pol and Nef cleavage sites. The HIV-1 Protein Data-mining Tool includes a set of 27 group M (subtypes A through K) reference sequences that can be used to assess the influence of genetic variation on immunological and functional domains of the protein. The BLAST Structure Tool identifies proteins with similar, experimentally determined topologies, and the Tools Directory provides a categorized list of websites and relevant software programs. This combined database and software repository is designed to facilitate the capture, retrieval and analysis of HIV-1 protein data, and to convert it into clinically useful information relating to the pathogenesis, transmission and therapeutic response of different HIV-1 variants. The HIV-1 Proteomics Resource is readily accessible through the BioAfrica website at:


  • Protein Data Bank
  • Protease Cleavage Site
  • Natural Polymorphism
  • Proteomics Tool
  • Protein Structure Analysis


Although the HIV-1 genome contains only 9 genes, it is capable of generating more than 19 gene products. These products can be divided into three major categories: structural and enzymatic (Gag, Pol, Env); immediate-early regulatory (Tat, Rev and Nef), and late regulatory (Vif, Vpu, Vpr) proteins. Tat, Rev and Nef are synthesized from small multiply-spliced mRNAs; Env, Vif, Vpu and Vpr are generated from singly-spliced mRNAs, the Gag and Gag-Pol precursor polyproteins are synthesized from full-length mRNA. The matrix (p17), capsid (p24) and nucleocapsid (p7) proteins are produced by protease cleavage of Gag and Gag-Pol, a fusion protein derived by ribosomal frame-shifting. Cleavage of Nef generates two different protein isoforms; one myristylated, the other non-myristylated. The viral enzymes (protease, reverse transcriptase, RNase H and integrase) are formed by protease cleavage of Gag-Pol. Alternative splicing, together with co-translational and post-translational modification, leads to additional protein variability [1].

Phylogenetic analysis, on its own, provides little information about the conformational, immunological and functional properties of HIV-1 proteins, but instead, focuses on the evolution and historical significance of sequence variants. To understand the clinical significance of genetic variation, sequence analysis needs to be combined with methods that assess change in the structural and biological properties of HIV-1 proteins. At present, information and tools for the systematic analysis of HIV-1 proteins are limited, and are scattered across a wide-range of online resources [2, 3]. To facilitate studies of the biological consequences of genetic variation, we have developed an integrated, user-friendly proteomics resource that integrates common approaches to HIV-1 protein analysis (Figure 1). We are currently using this resource to better understand the structure-function relationships underlying the emergence of antiretroviral drug resistance, and to examine the process of immune escape from cytotoxic T-lymphocytes (CTLs).
Figure 1
Figure 1

Site map of BioAfrica's HIV-1 Proteomics Resource, showing the separation of Beginner's and the Advanced area of the website, along with all major subject headings.

We have categorized the Proteomics Resource into the following main subject headings (Figure 2 &3):
Figure 2
Figure 2

Schematic representation of BioAfrica's HIV-1 Proteomics Resource, showing its five major components: the HIV-1 Proteome (General Overview, Domains/Folds/Motifs, Genomic Location, Protein-Macromolecule Interactions, Primary and Secondary Database Entries, and References and Recommended Readings), the HIV-1 Protease Cleavage Sites section, the HIV-1 Protein Data-mining Tool, the HIV-1 BLAST Structure Tool, and the Proteomics Tools Directory (for Beginners and Advanced investigators).

Figure 3
Figure 3

The central webpage of BioAfrica's HIV Proteomics Resource

1. HIV Proteome– Information about structure and sequence, as well as references and tutorials, for each of the HIV-1 proteins (Figure 4);
Figure 4
Figure 4

The central webpage of the HIV-1 Proteome section of the BioAfrica website

2. HIV-1 Cleavage Sites– Information about the position and sequence of HIV-1 Gag, Pol and Nef cleavage sites (Figure 5);
Figure 5
Figure 5

The HIV-1 Protease Cleavage Sites section of the BioAfrica website

3. HIV Protein Data Mining Tool– Application for detecting the characteristics of HIV-1 M group isolate (subtype A to K) proteins using information available in public databases and tools (Figure 6);
Figure 6
Figure 6

The central webpage of the HIV-1 Protein Data Mining Tool section of the BioAfrica website, where a specific HIV-1 genomic region is selected to be analyzed

4. HIV Structure BLAST– Similarity search for analyzing HIV protein sequences with corresponding structural data (Figure 7);
Figure 7
Figure 7

The BLAST HIV-1 protein structure similarity search is an online tool that searches for all protein structure data within the PDB that have an amino acid sequence similar to the query sequence

5. Proteomics Online Tools– Directory of data resources and tools available for both protein sequence and protein structure analyses of HIV (Figure 8 &9).
Figure 8
Figure 8

The introductory listing of proteomics resources for HIV research chosen to give a general overview of online tools and databases relevant for the analysis of HIV protein data

Figure 9
Figure 9

The advanced listing of online tools and databases relevant for the analysis of HIV protein data

The proteome link

Protease cleavage sites link

Protein data-mining tools link

The blast structure tool link

The proteomics tools directory link


The impending rollout of antiretroviral therapy to millions of HIV-1-infected people in sub-Saharan Africa provides a unique opportunity to monitor the efficacy of non-B treatment programs from their very inception, and to obtain critical new information for the optimization of treatment strategies that are safe, affordable and appropriate for the developing world. An integral part of this massive humanitarian effort will be the collection of large amounts of clinical and laboratory data, including genetic information on viral subtype and resistance mutations, as well as routine CD4+ T-cell counts and viral load measurements. The mere collection of this data, however, does not ensure that it will be used to its maximum potential. To achieve full benefit from this explosive source of new information, the data will need to be appropriately collated, stored, analyzed and interpreted.

The rapidly emerging field of Bioinformatics has the capacity to greatly enhance treatment (and vaccine) efforts by serving as a bridge between Medical Informatics and Experimental Science. By correlating genetic variation and potential changes in protein structure with clinical risk factors, disease presentation, and differential response to treatment and vaccine candidates, it may be possible to obtain valuable new insights that can be used to support and guide rationale decision-making, both at the clinical and public health levels. The HIV-1 Proteomics Resource, described in this report, is an initial first step in the development of improved methods for extracting and analyzing genomics data, converting it into biologically useful information related to the structure, function and physiology of HIV-1 proteins, and for assessing the role these proteins play in disease progression and response to therapy. The Resource, developed at the Molecular Virology and Bioinformatics Unit of the Africa Centre of Health and Population Studies, is a centralized user-friendly database that is easily accessed through the BioAfrica website at[23].

List of abbreviations used


Amino Acid


Basic Local Alignment Search Tool


casein kinase II


cytotoxic T-lymphocytes


Database of Interacting Proteins


deoxyribonucleic acid


envelope glycoprotein


group-specific antigen polyprotein


Graphics Interchange Format


Human Immunodeficiency Virus


Human Immunodeficiency Virus Type-1


Hypertext Transfer Protocol


long-terminal repeat


messenger RNA


National Center for Biotechnology Information


negative factor


Protein Data Bank


isoelectric point


protease inhibitors


protein kinase C


polymerase polyprotein


ART/TRS anti-repression transactivator protein


ribonucleic acid

RNase H: 

ribonuclease H


transactivating regulatory protein


virion infectivity factor


viral protein R


viral protein U



Development of the Bioafrica HIV-1 Proteomics Resource was supported by a program grant from the Wellcome Trust U.K. (#061238). The website is hosted by the South African Medical Research Council (MRC).

Authors’ Affiliations

Molecular Virology and Bioinformatics Unit, Africa Centre for Health and Population Studies, Doris Duke Medical Research Institute, Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
Biomedical Informatics Research Division, South African Medical Research Council, Cape Town, South Africa
Department of Medical Virology, University of Pretoria, Pretoria, South Africa


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© Doherty et al; licensee BioMed Central Ltd. 2005

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