Computer simulations unlock the secrets of antibiotic resistance
Abstract
In a strategy to combat antibiotic resistant bacteria, theoretical biologists at Los Alamos National Laboratory are simulating how some microbes use protein structures to flush out the drugs before they kill the bacteria. At an atom level, the simulations show the efflux pumps in action, giving researchers a new tool for figuring out how to disable the pumps. That would allow some currently powerless antibiotics to once again cure a range of public health threats, including bronchitis, pink eye, ear infections, and sexually transmitted diseases.
- Authors:
- Publication Date:
- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1424382
- Resource Type:
- Multimedia
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING
Citation Formats
Gnanakaran, Gnana. Computer simulations unlock the secrets of antibiotic resistance. United States: N. p., 2018.
Web.
Gnanakaran, Gnana. Computer simulations unlock the secrets of antibiotic resistance. United States.
Gnanakaran, Gnana. Thu .
"Computer simulations unlock the secrets of antibiotic resistance". United States. https://www.osti.gov/servlets/purl/1424382.
@article{osti_1424382,
title = {Computer simulations unlock the secrets of antibiotic resistance},
author = {Gnanakaran, Gnana},
abstractNote = {In a strategy to combat antibiotic resistant bacteria, theoretical biologists at Los Alamos National Laboratory are simulating how some microbes use protein structures to flush out the drugs before they kill the bacteria. At an atom level, the simulations show the efflux pumps in action, giving researchers a new tool for figuring out how to disable the pumps. That would allow some currently powerless antibiotics to once again cure a range of public health threats, including bronchitis, pink eye, ear infections, and sexually transmitted diseases.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Mar 01 00:00:00 EST 2018},
month = {Thu Mar 01 00:00:00 EST 2018}
}