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Logo of bmcbiophysBioMed CentralBiomed Central Web Sitesearchsubmit a manuscriptregisterthis articleBMC BiophysicsJournal Front Page
 
BMC Biophys. 2012; 5: 3.
Published online Feb 7, 2012. doi:  10.1186/2046-1682-5-3
PMCID: PMC3295656
Clustering of HIV-1 Subtypes Based on gp120 V3 Loop electrostatic properties
Aliana López de Victoria,1 Chris A Kieslich,1 Apostolos K Rizos,2 Elias Krambovitis,3 and Dimitrios Morikiscorresponding author1
1Department of Bioengineering, University of California, Riverside 92521, USA
2Department of Chemistry, University of Crete and Foundation for Research and Technology-Hellas, FORTH-IESL, GR-71003, Heraklion, Crete, Greece
3Department of Veterinary Medicine, University of Thessaly, Karditsa, Greece
corresponding authorCorresponding author.
Aliana López de Victoria: alope019/at/ucr.edu; Chris A Kieslich: ckies001/at/ucr.edu; Apostolos K Rizos: rizos/at/chemistry.uoc.gr; Elias Krambovitis: krambovitis/at/vet.uth.gr; Dimitrios Morikis: dmorikis/at/engr.ucr.edu
Received July 13, 2011; Accepted February 7, 2012.
Abstract
Background
The V3 loop of the glycoprotein gp120 of HIV-1 plays an important role in viral entry into cells by utilizing as coreceptor CCR5 or CXCR4, and is implicated in the phenotypic tropisms of HIV viruses. It has been hypothesized that the interaction between the V3 loop and CCR5 or CXCR4 is mediated by electrostatics. We have performed hierarchical clustering analysis of the spatial distributions of electrostatic potentials and charges of V3 loop structures containing consensus sequences of HIV-1 subtypes.
Results
Although the majority of consensus sequences have a net charge of +3, the spatial distribution of their electrostatic potentials and charges may be a discriminating factor for binding and infectivity. This is demonstrated by the formation of several small subclusters, within major clusters, which indicates common origin but distinct spatial details of electrostatic properties. Some of this information may be present, in a coarse manner, in clustering of sequences, but the spatial details are largely lost. We show the effect of ionic strength on clustering of electrostatic potentials, information that is not present in clustering of charges or sequences. We also make correlations between clustering of electrostatic potentials and net charge, coreceptor selectivity, global prevalence, and geographic distribution. Finally, we interpret coreceptor selectivity based on the N6X7T8|S8X9 sequence glycosylation motif, the specific positive charge location according to the 11/24/25 rule, and the overall charge and electrostatic potential distribution.
Conclusions
We propose that in addition to the sequence and the net charge of the V3 loop of each subtype, the spatial distributions of electrostatic potentials and charges may also be important factors for receptor recognition and binding and subsequent viral entry into cells. This implies that the overall electrostatic potential is responsible for long-range recognition of the V3 loop with coreceptors CCR5/CXCR4, whereas the charge distribution contributes to the specific short-range interactions responsible for the formation of the bound complex. We also propose a scheme for coreceptor selectivity based on the sequence glycosylation motif, the 11/24/25 rule, and net charge.
Keywords: HIV-1, protein-receptor interactions, Poisson-Boltzmann electrostatics, electrostatic similarity distance, electrostatic clustering
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