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Supercomputer simulations help develop new approach to fight antibiotic resistance

Supercomputer simulations help develop new approach to fight antibiotic resistance

Supercomputer simulations at the Department of Energy’s Oak Ridge National Laboratory have played a key role in discovering a new class of drug candidates that hold promise to combat antibiotic resistance. In a study led by the University of Oklahoma with ORNL, the University of Tennessee and Saint Louis University, lab experiments were combined with supercomputer modeling to identify molecules that boost antibiotics’ effect on disease-causing bacteria.

The researchers found four new chemicals that seek out and disrupt bacterial proteins called “efflux pumps,” known to be a major cause of antibiotic resistance. Although some antibiotics can permeate the protective barriers surrounding bacterial cells, many bacteria have evolved efflux pumps that expel antibiotics back out of the cell and render the medications ineffective.

The team focused on one efflux pump protein, known as AcrA, which connects two other proteins in a tunnel shape through the bacterial cell envelope. Disrupting this centrally positioned protein could “throw a wrench” into the middle of the efflux pump and mechanically break it, unlike drug design strategies that try to inhibit overall biochemical processes.

“As a first in this field, we proposed the approach of essentially ‘screwing up’ the efflux pump’s protein assembly, and this led to the discovery of molecules with a new type of antibacterial activity,” said co-author Jeremy Smith, who serves as a UT-ORNL Governor’s Chair and director of the UT-ORNL Center for Molecular Biophysics. “In contrast to previous approaches, our new mechanism uses mechanics to revive existing antibiotics’ ability to fight infection.” Details of the study were published in ACS Infectious Diseases.

Through laboratory experiments done in tandem with extensive protein simulations run on ORNL’s Titan supercomputer, they scanned large numbers of chemicals to predict and select which would be the most effective in preventing AcrA proteins from assembling properly.

Read more @ www.apintuslabs.com

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