Plague Research Today is a free monthly online journal that collates and summarizes the latest research about Plague, including details on bubonic plague, yersinia pestis, infection, types, treatment.

Targeting plague virulence factors: a combined machine learning method and multiple conformational virtual screening for the discovery of yersinia protein kinase a inhibitors.

Hu X, Prehna G, Stebbins CE

Laboratory of Structural Microbiology, The Rockefeller University, New York, New York 10021, USA.

Yersinia spp. is currently an antibiotic resistance concern and a re-emerging disease. The essential virulence factor Yersinia protein kinase A (YpkA) contains a Ser/Thr kinase domain whose activity modulates pathogenicity. Here, we present an approach integrating a machine learning method, homology modeling, and multiple conformational high-throughput docking for the discovery of YpkA inhibitors. These first reported inhibitors of YpkA may facilitate studies of the pathogenic mechanism of YpkA and serve as a starting point for development of anti-plague drugs.

Published 16 August 2007 in J Med Chem, 50(17): 3980-3.
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