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New Targets For the Control of Hiv Are Predicted ­sing a Novel Computational Analysis

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T. M. Murali

T. M. Murali

Credit: Courtesy of Virginia Tech

Virginia Tech researchers have developed a computational approach that can predict several human proteins that the human immunodeficiency virus (HIV) requires to replicate itself.

The researchers, who were led by T. M. Murali, Brett Tyler, and Michael G. Katze, say their work constitutes "a powerful resource for experimentalists who desire to discover new targets for human proteins that can control the spread of HIV."

Earlier studies silenced almost every human gene in order to discover HIV dependency factors (HDFs), which are genes that are necessary for HIV to survive and replicate. However, the studies found that only a few HDFs were common in two or more of the experiments. "Inspired by these observations, we hypothesized that we could predict new HDFs by exploiting the proximity between HDFs within networks of interactions between human proteins," Murali says.

The researchers used SinkSource, a Virginia Tech-developed algorithm that is able to determine which HDFs were likely to be linked to HIV. "Our results suggest that many HDFs are yet to be discovered and that they have potential value as prognostic markers to determine pathological outcome and the likelihood of Acquired Immune Deficiency Syndrome development," the researchers say.

From Virginia Tech News
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Abstracts Copyright © 2011 Information Inc. External Link, Bethesda, Maryland, USA 



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