@article{94631,
  keywords = {antimycobacterials, emergence of resistance, leprosy, prediction of mutations, tuberculosis},
  author = {Munir A and Vedithi S and Chaplin A and Blundell T},
  title = {Genomics, Computational Biology and Drug Discovery for Mycobacterial Infections: Fighting the Emergence of Resistance.},
  abstract = {<p>Tuberculosis (TB) and leprosy are mycobacterial infections caused by  and  respectively. These diseases continue to be endemic in developing countries where the cost of new medicines presents major challenges. The situation is further exacerbated by the emergence of resistance to many front-line antibiotics. A priority now is to design new antimycobacterials that are not only effective in combatting the diseases but are also less likely to give rise to resistance. In both these respects understanding the structure of drug targets in  and  is crucial. In this review we describe structure-guided approaches to understanding the impacts of mutations that give rise to antimycobacterial resistance and the use of this information in the design of new medicines.</p>},
  year = {2020},
  journal = {Frontiers in genetics},
  volume = {11},
  pages = {965},
  month = {01/2020},
  issn = {1664-8021},
  url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498718/pdf/fgene-11-00965.pdf},
  doi = {10.3389/fgene.2020.00965},
  language = {eng},
}