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Could Antibiotic Resistance Be Outsmarted by a Computational Approach?

ACCORDING to a new study, antibiotic resistance could be tackled by a supercomputer technology, which has demonstrated a spectacular ability to keep up with disease evolution. The novel research was carried out by an international team, who used a multi-pronged computer-guided strategy to create an advanced antibiotic from a previous antibiotic that was outsmarted by bacterial strains.  

Approximately 700,000 people die each year due to antibiotic resistant bacteria, a statistic that is estimated to rise to millions if the issue is not resolved. Furthermore, the lack of effective antibiotics could lead to life expectancy plummeting by 20 years. Researchers have worked, for many years now, to create new antibiotics that fight a disease quicker than it is able to advance to an antibiotic resistant state. Drug design innovations have used computers for decades; however, this is the first study that has created a new antibiotic using a multi-pronged computer guided strategy.  

In the opinion of Gerhard Koenig, Computational Chemist, University of Portsmouth, UK, and co-lead in the study, antibiotic resistance is a great threat to human health. Therefore, creating new strategies to tackle the resistant bacteria is of the utmost importance. The research team used an already existing antibiotic, which was unsuccessful in eliminating new bacterial strains, and redesigned it to overcome bacterial resistance mechanisms. The redesigned drug, which is yet to be evaluated in clinical trials, was found to be 56-times more active than erythromycin and clarithromycin, two antibiotics on the World Health Organization’s (WHO’s) list of essential medicines for tested bacterial strains. 

Furthermore, the researchers simulated the novel antibiotic for solubility, penetrability, and effectiveness of blocking bacterial protein production. One of the top supercomputers in Europe was used to develop this research in several weeks; however, it is important to note that the team worked for several years to establish that this approach was accurate. In conclusion, Koenig said: “Using a computational approach makes the development of new antibiotic derivatives faster and cheaper and predicting whether a chemical compound is going to be active before it is synthesised also avoids chemical waste.”