Bioinformatic Analysis of HIV-1 Entry and Pathogenesis

Title:Bioinformatic Analysis of HIV-1 Entry and Pathogenesis

Volume: 12 Issue: 2

Author(s): Benjamas Aiamkitsumrit, Will Dampier, Gregory Antell, Nina Rivera, Julio Martin-Garcia, Vanessa Pirrone, Michael R. Nonnemacher and Brian Wigdahl

Affiliation:

Keywords: CCR5, coreceptor, CXCR4, HIV, mutual information, PSSM.

Abstract: The evolution of human immunodeficiency virus type 1 (HIV-1) with respect to co-receptor utilization has been shown to be relevant to HIV-1 pathogenesis and disease. The CCR5-utilizing (R5) virus has been shown to be important in the very early stages of transmission and highly prevalent during asymptomatic infection and chronic disease. In addition, the R5 virus has been proposed to be involved in neuroinvasion and central nervous system (CNS) disease. In contrast, the CXCR4-utilizing (X4) virus is more prevalent during the course of disease progression and concurrent with the loss of CD4⁺ T cells. The dual-tropic virus is able to utilize both co-receptors (CXCR4 and CCR5) and has been thought to represent an intermediate transitional virus that possesses properties of both X4 and R5 viruses that can be encountered at many stages of disease. The use of computational tools and bioinformatic approaches in the prediction of HIV-1 co-receptor usage has been growing in importance with respect to understanding HIV-1 pathogenesis and disease, developing diagnostic tools, and improving the efficacy of therapeutic strategies focused on blocking viral entry. Current strategies have enhanced the sensitivity, specificity, and reproducibility relative to the prediction of co-receptor use; however, these technologies need to be improved with respect to their efficient and accurate use across the HIV-1 subtypes. The most effective approach may center on the combined use of different algorithms involving sequences within and outside of the env-V3 loop. This review focuses on the HIV-1 entry process and on co-receptor utilization, including bioinformatic tools utilized in the prediction of co-receptor usage. It also provides novel preliminary analyses for enabling identification of linkages between amino acids in V3 with other components of the HIV-1 genome and demonstrates that these linkages are different between X4 and R5 viruses.

Cite this article as:

Aiamkitsumrit Benjamas, Dampier Will, Antell Gregory, Rivera Nina, Martin-Garcia Julio, Pirrone Vanessa, Nonnemacher R. Michael and Wigdahl Brian, Bioinformatic Analysis of HIV-1 Entry and Pathogenesis, Current HIV Research 2014; 12 (2) . https://dx.doi.org/10.2174/1570162X12666140526121746