The ability of HIV-1 to develop high levels of genetic diversity and acquire mutations to escape immune pressures contributes to our difficulties in producing a vaccine. David Nickle et al present here an efficient algorithm to develop vaccines that cope with the diversity of HIV or other variable pathogens.
This computational method clarifies and analyzes the variation found in the strains of the virus by describing the molecules which stimulate the immune response to HIV (immunogens) that have multiple forms of variable elements of the virus. These antigens compress the variation found in many viral strains into lengths suitable for vaccine immunogens. "We can capture 62% of the variation found in the Nef protein and 81% of the variation in the Gag protein into immunogens of three gene lengths", says Nickle.
These short-length immunogens are potentially useable in a vaccine, as they reflect the diversity of features in HIV-1 strains. These immunogens should elicit immune responses against high frequency viral strains as well as against most mutant forms of the virus.
PLEASE MENTION THE OPEN-ACCESS JOURNAL PLoS COMPUTATIONAL BIOLOGY (www.ploscompbiol.org) AS THE SOURCE FOR THIS ARTICLE AND PROVIDE A LINK TO THE FREELY-AVAILABLE TEXT. THANK YOU.
*** Please note: there is an EMBARGO in place until Thursday 26th April 5pm Pacific time***
PLEASE ADD THIS LINK TO THE PUBLISHED ARTICLE IN ONLINE VERSIONS OF YOUR REPORT: http://compbiol.plosjournals.org/perlserv/?request=get-document&doi=10.1371/journal.pcbi.0030075 (link will go live on April 27th)
CITATION: Nickle DC, Rolland M, Jensen MA, Pond SLK, Deng W, et al. (2007) Coping with viral diversity in HIV vaccine design. PLoS Comput Biol 3(4): e75. doi:10.1371/journal.pcbi.0030075
Disclaimer
This press release refers to an upcoming article in PLoS Computational Biology. The release is provided by journal staff. Any opinions expressed in this release or article are the personal views of the journal staff and/or article contributors, and do not necessarily represent the views or policies of PLoS. PLoS expressly disclaims any and all warranties and liability in connection with the information found in the releases and articles and your use of such information.
About PLoS Computational Biology
PLoS Computational Biology (www.ploscompbiol.org) features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained by the authors. The Public Library of Science uses the Creative Commons Attribution License.
About the Public Library of Science
The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical literature a freely available public resource. For more information, visit http://www.plos.org
Journal
PLoS Computational Biology