Min, Ong Si
(2013)
Prediction of co-receptor binding of HIV-1 virus of
Kelantan based on sequence analysis of V3 loop
structure.
Project Report.
Universiti Sains Malaysia.
(Submitted)
Abstract
The V3 loop of human immunodeficiency virus type 1 (HIV-1) is critical for coreceptor
binding and it is the main determinant of which cellular co-receptor is used,
CCR5 or CXCR4. The virus uses this V3 loop for cell entry. It is also the
determinant for syncytium formation, virus infectivity and antibody neutralization.
Accurate prediction of the co-receptor used by the virus in the patient is important as
it allows personalized selection of effective drugs and prognosis of disease
progression. This study aims to determine the sequence variation of V3 loop
structure and predict the co-receptor used by HIV-1 viruses from Kelantan isolate
using bioinformatics tools to monitor the disease progression of the patients. It is also
aims to determine the origin of HIV-1 viruses from Kelantan by constructing a
phylogenetic tree based on V3 region of the virus. In this study, the V3 loop of thirty
HIV-1 viruses from Kelantan was successfully amplified and these amplicons were
sequenced and aligned using Bioedit software. The tip motif of the HIV-1 virus was
determined by translating the nucleotide to amino acid sequence. The co-receptor
used by the virus was predicted using two bioinformatics tool, Geno2pheno (Max
Planck Institut Informatik) and Profile-based String Kernel Software (Corbeil
Research Group). The results reveal that among the thirty samples; twenty-nine
samples were using CCR5 as co-receptor with tip motif GPGQVFYRTGDETGD1 while only one virus that utilized CXCR4 asco-receptor with tip motif of
GPGQVFYRTGDITGDIL. Based on phylogenetic and BLAST results, 30 viruses
were identified as Circulating Recombinant Forms (CRFs) virus with 10 samples
were classified into CRF01AE and 20 were the new recombinant of AE/B subtype The HIV-1 viruses were closely related to the published HIV-1 viruses from Thailand, Singapore and Malaysia itself. The bioinformatics tools could be suggested as preliminary prediction of co-receptor used by HIV-1 virus for prognosis of disease progression.
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