These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
196 related articles for article (PubMed ID: 20835433)
1. Analysis and hit filtering of a very large library of compounds screened against Mycobacterium tuberculosis. Ekins S; Kaneko T; Lipinski CA; Bradford J; Dole K; Spektor A; Gregory K; Blondeau D; Ernst S; Yang J; Goncharoff N; Hohman MM; Bunin BA Mol Biosyst; 2010 Nov; 6(11):2316-2324. PubMed ID: 20835433 [TBL] [Abstract][Full Text] [Related]
2. Validating new tuberculosis computational models with public whole cell screening aerobic activity datasets. Ekins S; Freundlich JS Pharm Res; 2011 Aug; 28(8):1859-69. PubMed ID: 21547522 [TBL] [Abstract][Full Text] [Related]
3. Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery. Ekins S; Madrid PB; Sarker M; Li SG; Mittal N; Kumar P; Wang X; Stratton TP; Zimmerman M; Talcott C; Bourbon P; Travers M; Yadav M; Freundlich JS PLoS One; 2015; 10(10):e0141076. PubMed ID: 26517557 [TBL] [Abstract][Full Text] [Related]
4. Combining computational methods for hit to lead optimization in Mycobacterium tuberculosis drug discovery. Ekins S; Freundlich JS; Hobrath JV; Lucile White E; Reynolds RC Pharm Res; 2014 Feb; 31(2):414-35. PubMed ID: 24132686 [TBL] [Abstract][Full Text] [Related]
5. Enhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian models. Ekins S; Reynolds RC; Franzblau SG; Wan B; Freundlich JS; Bunin BA PLoS One; 2013; 8(5):e63240. PubMed ID: 23667592 [TBL] [Abstract][Full Text] [Related]
6. Combining cheminformatics methods and pathway analysis to identify molecules with whole-cell activity against Mycobacterium tuberculosis. Sarker M; Talcott C; Madrid P; Chopra S; Bunin BA; Lamichhane G; Freundlich JS; Ekins S Pharm Res; 2012 Aug; 29(8):2115-27. PubMed ID: 22477069 [TBL] [Abstract][Full Text] [Related]
7. [Development of antituberculous drugs: current status and future prospects]. Tomioka H; Namba K Kekkaku; 2006 Dec; 81(12):753-74. PubMed ID: 17240921 [TBL] [Abstract][Full Text] [Related]
8. Bayesian models for screening and TB Mobile for target inference with Mycobacterium tuberculosis. Ekins S; Casey AC; Roberts D; Parish T; Bunin BA Tuberculosis (Edinb); 2014 Mar; 94(2):162-9. PubMed ID: 24440548 [TBL] [Abstract][Full Text] [Related]
9. A collaborative database and computational models for tuberculosis drug discovery. Ekins S; Bradford J; Dole K; Spektor A; Gregory K; Blondeau D; Hohman M; Bunin BA Mol Biosyst; 2010 May; 6(5):840-51. PubMed ID: 20567770 [TBL] [Abstract][Full Text] [Related]
10. Hit discovery of Mycobacterium tuberculosis inosine 5'-monophosphate dehydrogenase, GuaB2, inhibitors. Sahu NU; Singh V; Ferraris DM; Rizzi M; Kharkar PS Bioorg Med Chem Lett; 2018 Jun; 28(10):1714-1718. PubMed ID: 29699922 [TBL] [Abstract][Full Text] [Related]
11. Modeling the permeability of drug-like molecules through the cell wall of Mycobacterium tuberculosis: an analogue based approach. Janardhan S; Ram Vivek M; Narahari Sastry G Mol Biosyst; 2016 Oct; 12(11):3377-3384. PubMed ID: 27604290 [TBL] [Abstract][Full Text] [Related]
12. Identification of small molecular inhibitors for efflux protein Rv2688c of Mycobacterium tuberculosis. Vadija R; Mustyala KK; Malkhed V; Dulapalli R; Veeravarapu H; Malikanti R; Vuruputuri U Biotechnol Appl Biochem; 2018 Jul; 65(4):608-621. PubMed ID: 29377374 [TBL] [Abstract][Full Text] [Related]