Human Immunodeficiency Virus 1 enters host cells through interaction of its V3 loop (which is partof the gp120 protein) with the host cell receptor CD4 and one of two co-receptors, namely CCR5or CXCR4. Entry inhibitors binding the CCR5 co-receptor can prevent viral entry.
As these drugsare only available for CCR5-using viruses, accurate prediction of this so-called co-receptor tropismis important in order to ensure an effective personalized therapy. With the development of nextgenerationsequencing technologies, it is now possible to sequence representative subpopulations ofthe viral quasispecies.
Results:
Here we present T-CUP 2.0, a model for predicting co-receptor tropism.
Based on our recently publishedT-CUP model, we developed a more accurate and even faster solution. Similarly to its predecessor,T-CUP 2.0 models co-receptor tropism using information of the electrostatic potential and hydrophobicityof V3-loops.
However, extracting this information from a simplified structural vacuummodelleads to more accurate and faster predictions. The area-under-the-ROC-curve (AUC) achievedwith T-CUP 2.0 on the training set is 0.968±0.005 in a leave-one-patient-out cross-validation.
Whenapplied to an independent dataset, T-CUP 2.0 has an improved prediction accuracy of around 3%when compared to the original T-CUP.
Conclusions:
We found that it is possible to model co-receptor tropism in HIV-1 based on a simplified structurebasedmodel of the V3 loop. In this way, genotypic prediction of co-receptor tropism is very accurate,fast and can be applied to large datasets derived from next-generation sequencing technologies.
Thereduced complexity of the electrostatic modeling makes T-CUP 2.0 independent from third-partysoftware, making it easy to install and use.
Author: Dominik HeiderJan Nikolaj DybowskiChristoph WilmsDaniel Hoffmann
Credits/Source: BioData Mining 2014, 7:14
Published on: 2014-08-02
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