A computer modeling approach to combat antibiotic resistance by simulating drug interactions and effects.
As antibiotic resistance continues to rise, researchers have created advanced computer models that could enable disease-fighting drugs to target specific bacteria in precise areas of the body with laser-like accuracy (1✔ ✔Trusted Source
Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens
Go to source). As it stands, antibiotics kill bacteria indiscriminately. Because the drugs are used so widely, increasing numbers of dangerous bugs are growing resistant, threatening one of modern medicine’s most important weapons against disease.
‘Exciting news in the fight against #antibioticresistance! #Computer_models reveal unique properties of stomach bacteria, paving the way for targeted #antibiotics.’
UVA's Novel Approach to Combatting Antibiotic Resistance
UVA’s new approach, on the other hand, would dramatically limit how often bacteria are exposed to antibiotics, reducing the chance they could become resistant to antibiotics. Further, the approach would represent a significant step forward for precision medicine, allowing doctors to better tailor treatments to individual patients’ needs. Instead of taking an antibiotic that kills bacteria regardless of whether helpful or harmful, patients could be given antibiotics that target specific bacteria causing a specific problem in a specific area of the body.“Many biomedical challenges are incredibly complex, and computer models are emerging as a powerful tool for tackling such problems,” said researcher Jason Papin, PhD, of UVA’s Department of Biomedical Engineering. “We’re hopeful that these computer models of the molecular networks in bacteria will help us develop new strategies to treat infections.”
UVA’s new approach was made possible by a herculean effort by Papin, PhD student Emma Glass and their collaborators. Working with Andrew Warren, PhD, of UVA’s Biocomplexity Institute, the researchers in Papin’s lab developed sophisticated computer models of every human bacterial pathogen with sufficient genetic information available.
Glass then analyzed all those models and identified shared traits among the bacteria. This analysis yielded the discovery that bacteria in certain parts of the body, such as the stomach, tended to share metabolic properties. Basically, where they live shapes how they function.
The shared similarities among the microbes in different locales could be the Achilles’ heel for harmful bacteria in our bodies. With further research, doctors may be able to target specific types of bacteria in specific areas, reducing the need for broad-spectrum antibiotics.
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“We still have much to do to test these ideas for other bacteria and types of infections,” Papin said. “but this work shows the incredible promise of data science and computer modeling for tackling some of the most important problems in biomedical research.”
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- Niche-specific metabolic phenotypes can be used to identify antimicrobial targets in pathogens - (https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3002907)
Source-Eurekalert