Computational modeling of drug-resistant bacteria. Final report

Technical Report · Thu Mar 12 00:00:00 EDT 2015

DOI:https://doi.org/10.2172/1172320· OSTI ID:1172320

MacDougall, Preston ^[1]

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1. Middle Tennessee State Univ., Murfreesboro, TN (United States)

Initial proposal summary: The evolution of antibiotic-resistant mutants among bacteria (superbugs) is a persistent and growing threat to public health. In many ways, we are engaged in a war with these microorganisms, where the corresponding arms race involves chemical weapons and biological targets. Just as advances in microelectronics, imaging technology and feature recognition software have turned conventional munitions into smart bombs, the long-term objectives of this proposal are to develop highly effective antibiotics using next-generation biomolecular modeling capabilities in tandem with novel subatomic feature detection software. Using model compounds and targets, our design methodology will be validated with correspondingly ultra-high resolution structure-determination methods at premier DOE facilities (single-crystal X-ray diffraction at Argonne National Laboratory, and neutron diffraction at Oak Ridge National Laboratory). The objectives and accomplishments are summarized.

• Research Organization: Middle Tennessee State Univ., Murfreesboro, TN (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER)
• DOE Contract Number: SC0005094
• OSTI ID: 1172320
• Report Number(s): DOE-MTSU-5094-10; TRN: US1500038
• Country of Publication: United States
• Language: English

Related Subjects

60 APPLIED LIFE SCIENCES
74 ATOMIC AND MOLECULAR PHYSICS
97 MATHEMATICS AND COMPUTING
MUTANTS
BACTERIA
BIOLOGICAL EVOLUTION
PUBLIC HEALTH
ANTIBIOTICS
DESIGN
ANL
ORNL
Computerized Simulation
DETECTION
COMPUTER CODES
SPATIAL RESOLUTION
NEUTRON DIFFRACTION
X-RAY DIFFRACTION
MONOCRYSTALS
molecular modeling
charge density analysis
X-ray diffraction
molecular visualization
drug design