Identification of Inhibitors of Fatty Acid Synthesis Enzymes in Mycobacterium Smegmatis
Digital Object Identifier (DOI)
Journal of Computational Science Education
Antibiotic-resistant strains of Mycobacterium tuberculosis have rendered some of the current treatments for tuberculosis ineffective, creating a need for new treatments. Today, the most efficient way to find new drugs to treat tuberculosis and other diseases is to use virtual screening to quickly consider millions of potential drug candidates and filter out all but the ones most likely to inhibit the disease. These top hits can then be tested in a traditional wet lab to determine their potential effectiveness. Using supercomputers, we screened over 4 million potential drug molecules against each of two enzymes that are critical to the survival of Mycobacterium tuberculosis. During this process, we determined the top candidate molecules to test in the wet lab.
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Priest, Alexander, E. Davis Oldham, Lynn Lewis, and David Toth. 2015. “Identification of Inhibitors of Fatty Acid Synthesis Enzymes in Mycobacterium Smegmatis.” The Journal of Computational Science Education 6 (1): 25–31. https://doi.org/10.22369/issn.2153-4136/6/1/3.
This article is openly available on the website of the Journal of Computational Science Education.
The Journal of Computational Science Education (JOCSE) promotes the use of computation in education through disseminating unique uses of computation in the classroom as well as research findings in computational science education, with submissions from both professionals and students.