Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection.

ABSTRACT:

Background

Leishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease.

Results

We have predicted the protein interaction network of Leishmania major by using three validated methods: PSIMAP, PEIMAP, and iPfam. Combining the results from these methods, we calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions. We were able to predict the bi

SUBMITTER: Florez AF 

PROVIDER: S-EPMC2956735 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature