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Pros and cons of the tuberculosis drugome approach--an empirical analysis.
Chen, Feng-Chi; Liao, Yu-Chieh; Huang, Jie-Mao; Lin, Chieh-Hua; Chen, Yih-Yuan; Dou, Horng-Yunn; Hsiung, Chao Agnes.
Affiliation
  • Chen FC; Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan; Department of Life Sciences, National Chiao-Tung University, Hsinchu, Taiwan; Department of Dentistry, China Medical University, Taichung, Taiwan
  • Liao YC; Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
  • Huang JM; Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
  • Lin CH; Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan; Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan.
  • Chen YY; National Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
  • Dou HY; National Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
  • Hsiung CA; Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County, Taiwan.
PLoS One ; 9(6): e100829, 2014.
Article in En | MEDLINE | ID: mdl-24971632
ABSTRACT
Drug-resistant Mycobacterium tuberculosis (MTB), the causative pathogen of tuberculosis (TB), has become a serious threat to global public health. Yet the development of novel drugs against MTB has been lagging. One potentially powerful approach to drug development is computation-aided repositioning of current drugs. However, the effectiveness of this approach has rarely been examined. Here we select the "TB drugome" approach--a protein structure-based method for drug repositioning for tuberculosis treatment--to (1) experimentally validate the efficacy of the identified drug candidates for inhibiting MTB growth, and (2) computationally examine how consistently drug candidates are prioritized, considering changes in input data. Twenty three drugs in the TB drugome were tested. Of them, only two drugs (tamoxifen and 4-hydroxytamoxifen) effectively suppressed MTB growth at relatively high concentrations. Both drugs significantly enhanced the inhibitory effects of three first-line anti-TB drugs (rifampin, isoniazid, and ethambutol). However, tamoxifen is not a top-listed drug in the TB drugome, and 4-hydroxytamoxifen is not approved for use in humans. Computational re-examination of the TB drugome indicated that the rankings were subject to technical and data-related biases. Thus, although our results support the effectiveness of the TB drugome approach for identifying drugs that can potentially be repositioned for stand-alone applications or for combination treatments for TB, the approach requires further refinements via incorporation of additional biological information. Our findings can also be extended to other structure-based drug repositioning methods.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Mycobacterium tuberculosis / Antitubercular Agents Type of study: Prognostic_studies Limits: Humans Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2014 Document type: Article Affiliation country: Taiwan

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Mycobacterium tuberculosis / Antitubercular Agents Type of study: Prognostic_studies Limits: Humans Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2014 Document type: Article Affiliation country: Taiwan