Predicting superbugs' countermoves to new drugs -- MEDICA Trade Fair

Predicting superbugs' countermoves to new drugs

Photo: Petri dish with bacteria inside

Researchers have used a computer program called OSPREY to predict how MRSA will adapt to a new experimental drug ahead of time, before the drug is tested on patients; © Andreas Teske

With drug-resistant bacteria on the rise, even common infections that were easily controlled for decades - such as pneumonia or urinary tract infections - are proving trickier to treat with standard antibiotics. New drugs are desperately needed, but so are ways to maximize the effective lifespan of these drugs.

To accomplish that, Duke University researchers used software they developed to predict a constantly-evolving infectious bacterium's countermoves to one of these new drugs ahead of time, before the drug is even tested on patients.

In a study appearing in the journal Proceedings of the National Academy of Sciences, the team used their program to identify the genetic changes that will allow methicillin-resistant Staphylococcus aureus, or MRSA, to develop resistance to a class of new experimental drugs that show promise against the deadly bug.

When the researchers treated live bacteria with the new drug, two of the genetic changes actually arose, just as their algorithm predicted.

"This gives us a window into the future to see what bacteria will do to evade drugs that we design before a drug is deployed," said co-author Bruce Donald, a professor of computer science and biochemistry at Duke.

Developing pre-emptive strategies while the drugs are still in the design phase will give scientists a head start on the next line of compounds that will be effective despite the germ's resistance mutations.

"If we can somehow predict how bacteria might respond to a particular drug ahead of time, we can change the drug, or plan for the next one, or rule out therapies that are unlikely to remain effective for long", said Duke graduate student Pablo Gainza-Cirauqui, who co-authored the paper.

"With a new drug, there is always the possibility that the organism will develop different mutations that had never been seen before. This is what really worries physicians."

To overcome this problem, a research team led by Donald at Duke and Amy Anderson at the University of Connecticut used a protein design algorithm they developed, called OSPREY, to identify DNA sequence changes in the bacteria that would enable the resulting protein to block the drug from binding, while still performing its normal work within the cell.

The team focused on a new class of experimental drugs that work by binding and inhibiting a bacterial enzyme called dihydrofolate reductase (DHFR), which plays an essential role in building DNA and other processes. The drugs, called propargyl-linked antifolates, show promise as a treatment for MRSA infections but have yet to be tested in humans.

"We wanted to find out what countermoves the bacteria are likely to employ against these novel compounds. Will they be the same old mutations we've seen before, or might the bacteria do new things instead?", Donald said.

Their computational approach could be especially useful for forecasting drug resistance mutations in other diseases, such as cancer, HIV and influenza, where raising resistant cells or strains in the lab is more difficult to do than with bacteria, the researchers say.
The software they developed, called OSPREY, is open-source and freely available for any researcher to use.; Source: Duke University