Machine learning techniques can be used to search for new drugs for one of the most insidious causes of stomach ulcers and other gastrointestinal problems, the bacteria known as Helicobacter pylori.

Ulcers are like open sores in the wall lining the stomach into which stomach acid can eat. These so-called peptic ulcers can be very painful and are a major risk factor for stomach cancer. In the late 1980s, Australian scientists demonstrated that the corkscrew-shaped H. pylori. This was the subject of the 2005 Nobel Prize for Medicine as it overturned decades of received wisdom regarding the nature of ulcers. It suggested that a multi-billion dollar drug industry based on acid inhibitors and other such agents was no longer needed as a course of antibiotics might suffice. This later proved to be the case in treating ulcers caused by H. pylori.

Unfortunately, bacteria quickly evolve resistance to antibiotics, so there is always a need to find new ones that can keep us one step ahead of the infectious pathogens. Now, work published in the International Journal of Bioinformatics Research and Applications, points the way to a new approach to finding antibiotics to treat conditions associated with H. pylori infection.

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