Literature DB >> 10609550

Use of genomics and combinatorial chemistry in the development of new antimycobacterial drugs.

C E Barry1, R A Slayden, A E Sampson, R E Lee.   

Abstract

With the completion of the genome of Mycobacterium tuberculosis comes the promise of a new generation of potent drugs to combat the emerging epidemic of multiply drug-resistant isolates. Translating this genomic information into realistic assays, valid targets, and preclinical drug candidates represents the next great hope in tuberculosis control. We propose a paradigm for exploiting the genome to inform the development of novel antituberculars, utilizing the techniques of differential gene expression as monitored by DNA microarrays coupled with the emerging discipline of combinatorial chemistry. A comparison of currently used antituberculars with the properties of other pharmaceuticals suggests that such compounds will have a defined range of physiochemical properties. In general, we can expect the next generation of antituberculars to be small, relatively hydrophilic molecules that bind tightly to specific cellular targets. Many current antimycobacterials require some form of cellular activation (e.g. the activation of isoniazid by a catalase-peroxidase). Activation corresponds to the oxidative, reductive, or hydrolytic unmasking of reactive groups, which occurs with many current antimycobacterial prodrugs. Understanding the mechanisms involved in activation of current antimycobacterial therapeutics also may facilitate the development of alternative activation strategies or of analogs that require no such processes.

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Year:  2000        PMID: 10609550     DOI: 10.1016/s0006-2952(99)00253-1

Source DB:  PubMed          Journal:  Biochem Pharmacol        ISSN: 0006-2952            Impact factor:   5.858


  26 in total

1.  Targeting tuberculosis through a small focused library of 1,2,3-triazoles.

Authors:  Guillermo R Labadie; Agustina de la Iglesia; Héctor R Morbidoni
Journal:  Mol Divers       Date:  2011-06-02       Impact factor: 2.943

2.  Crystal structure of a putative methyltransferase from Mycobacterium tuberculosis: misannotation of a genome clarified by protein structural analysis.

Authors:  Jodie M Johnston; Vickery L Arcus; Craig J Morton; Michael W Parker; Edward N Baker
Journal:  J Bacteriol       Date:  2003-07       Impact factor: 3.490

3.  Structure-activity relationship of new anti-tuberculosis agents derived from oxazoline and oxazole benzyl esters.

Authors:  Garrett C Moraski; Mayland Chang; Adriel Villegas-Estrada; Scott G Franzblau; Ute Möllmann; Marvin J Miller
Journal:  Eur J Med Chem       Date:  2010-01-14       Impact factor: 6.514

4.  Interspecies pharmacokinetics and in vitro metabolism of SQ109.

Authors:  Lee Jia; Patricia E Noker; Lori Coward; Gregory S Gorman; Marina Protopopova; Joseph E Tomaszewski
Journal:  Br J Pharmacol       Date:  2006-03       Impact factor: 8.739

Review 5.  New drugs against tuberculosis: problems, progress, and evaluation of agents in clinical development.

Authors:  Jossy van den Boogaard; Gibson S Kibiki; Elton R Kisanga; Martin J Boeree; Rob E Aarnoutse
Journal:  Antimicrob Agents Chemother       Date:  2008-12-15       Impact factor: 5.191

6.  High-throughput screening for inhibitors of Mycobacterium tuberculosis H37Rv.

Authors:  Subramaniam Ananthan; Ellen R Faaleolea; Robert C Goldman; Judith V Hobrath; Cecil D Kwong; Barbara E Laughon; Joseph A Maddry; Alka Mehta; Lynn Rasmussen; Robert C Reynolds; John A Secrist; Nice Shindo; Dustin N Showe; Melinda I Sosa; William J Suling; E Lucile White
Journal:  Tuberculosis (Edinb)       Date:  2009-09-15       Impact factor: 3.131

7.  Unique mechanism of action of the thiourea drug isoxyl on Mycobacterium tuberculosis.

Authors:  Benjawan Phetsuksiri; Mary Jackson; Hataichanok Scherman; Michael McNeil; Gurdyal S Besra; Alain R Baulard; Richard A Slayden; Andrea E DeBarber; Clifton E Barry; Mark S Baird; Dean C Crick; Patrick J Brennan
Journal:  J Biol Chem       Date:  2003-10-14       Impact factor: 5.157

8.  Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.

Authors:  Sean Ekins; Robert C Reynolds; Hiyun Kim; Mi-Sun Koo; Marilyn Ekonomidis; Meliza Talaue; Steve D Paget; Lisa K Woolhiser; Anne J Lenaerts; Barry A Bunin; Nancy Connell; Joel S Freundlich
Journal:  Chem Biol       Date:  2013-03-21

9.  Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for Mycobacterium tuberculosis.

Authors:  Sean Ekins; Joel S Freundlich; Robert C Reynolds
Journal:  J Chem Inf Model       Date:  2014-07-17       Impact factor: 4.956

10.  High content screening identifies decaprenyl-phosphoribose 2' epimerase as a target for intracellular antimycobacterial inhibitors.

Authors:  Thierry Christophe; Mary Jackson; Hee Kyoung Jeon; Denis Fenistein; Monica Contreras-Dominguez; Jaeseung Kim; Auguste Genovesio; Jean-Philippe Carralot; Fanny Ewann; Eun Hye Kim; Sae Yeon Lee; Sunhee Kang; Min Jung Seo; Eun Jung Park; Henrieta Skovierová; Ha Pham; Giovanna Riccardi; Ji Youn Nam; Laurent Marsollier; Marie Kempf; Marie-Laure Joly-Guillou; Taegwon Oh; Won Kyung Shin; Zaesung No; Ulf Nehrbass; Roland Brosch; Stewart T Cole; Priscille Brodin
Journal:  PLoS Pathog       Date:  2009-10-30       Impact factor: 6.823

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