AEGiS-11IAC: Population-dependent prediction of CTL epitopes for HIV clades using a computer-driven algorithm.

11th International AIDS Conference


Vancouver, British Columbia — July 7-12, 1996

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Population-dependent prediction of CTL epitopes for HIV clades using a computer-driven algorithm.

Int Conf AIDS 1996 Jul 7-12; 11:211 (abstract no. Th.A.144)
Jesdale BM, Schafer JR, Santiago MLO, Granek JA, Roberts CGP, Koup RA, De Groot AS; TB/HIV Research Laboratory, International Health Institute, Brown University School of Medicine, Providence, RI. Fax: (401) 863-1243. E-mail: William_Jesdale@brown.edu.

OBJECTIVE: To predict CTL epitopes for selected world populations, using a computer algorithm to identify regions of HIV proteins that may be presented in the context of multiple MHC class I molecules.

METHODS: Sequences for the HIV-1 gp160 protein from clades A through E, including a common laboratory strain, BH10, were examined using a computer algorithm to identify regions of clustering of MHC binding motifs (Meister et al., 1995. Vaccine 13:581). The predicted epitopes were weighted by the prevalence of HLA alleles in the country of interest. Using allele frequencies for North American Caucasians (NAC), North American Blacks (NAB), Zaireans, W. Africans, and Chinese, the percent of each population covered by the predictions (% coverage) was estimated. (table: see text)

RESULTS: For example, predictions corresponding with published CTL epitopes for BH10 gp160 are shown. 4/11 predictions (some containing "well established epitopes" (x) described in the Los Alamos HIV database [LANL]) are predicted to cover greater than 2/3 of the class I alleles in all 5 populations studied.

CONCLUSIONS: Predicted CTL epitopes corresponding to published T cell epitopes for gp 160 of HIV strain BH10 may be presented in the context of many of the MHC class I alleles in selected world populations. Predictions for HIV-1 clades A through E that are selected to maximize MHC coverage for selected world populations and binding studies for the predicted epitopes will be presented. Using the EpiMer algorithm, searches for MHC-binding motif rich CTL epitopes for each HIV clade can be tailored to the MHC prevalence in the target population.

Keywords: AEGIS, HIV, Epitopes, HIV-1, Epitopes, T-Lymphocyte, HIV Antigens, Algorithms, Computers, Major Histocompatibility Complex, HIV Infections, HIV Envelope Protein gp160, HIV Envelope Protein gp120, HLA Antigens, Alleles, immunology, genetics, ICA11KWDaegis,hiv,epitopes,hiv-1,epitopes,t-lymphocyte,hivantigens,algorithms,computers,majorhistocompatibilitycomplex,hivinfections,hivenvelopeproteingp160,hivenvelopeproteingp120,hlaantigens,alleles,immunology,genetics,ica11

960707
ThA144

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