Literature DB >> 21129975

Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery.

Sean Ekins1, Joel S Freundlich, Inhee Choi, Malabika Sarker, Carolyn Talcott.   

Abstract

We are witnessing the growing menace of both increasing cases of drug-sensitive and drug-resistant Mycobacterium tuberculosis strains and the challenge to produce the first new tuberculosis (TB) drug in well over 40 years. The TB community, having invested in extensive high-throughput screening efforts, is faced with the question of how to optimally leverage these data to move from a hit to a lead to a clinical candidate and potentially, a new drug. Complementing this approach, yet conducted on a much smaller scale, cheminformatic techniques have been leveraged and are examined in this review. We suggest that these computational approaches should be optimally integrated within a workflow with experimental approaches to accelerate TB drug discovery.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 21129975      PMCID: PMC3034835          DOI: 10.1016/j.tim.2010.10.005

Source DB:  PubMed          Journal:  Trends Microbiol        ISSN: 0966-842X            Impact factor:   17.079


  96 in total

1.  Pathway logic modeling of protein functional domains in signal transduction.

Authors:  C Talcott; S Eker; M Knapp; P Lincoln; K Laderoute
Journal:  Pac Symp Biocomput       Date:  2004

2.  Analysis of the calculated physicochemical properties of respiratory drugs: can we design for inhaled drugs yet?

Authors:  Timothy J Ritchie; Christopher N Luscombe; Simon J F Macdonald
Journal:  J Chem Inf Model       Date:  2009-04       Impact factor: 4.956

3.  Structure-based design of DevR inhibitor active against nonreplicating Mycobacterium tuberculosis.

Authors:  Rajesh Kumar Gupta; Tejender S Thakur; Gautam R Desiraju; Jaya Sivaswami Tyagi
Journal:  J Med Chem       Date:  2009-10-22       Impact factor: 7.446

4.  3D-Pharmacophore mapping of thymidine-based inhibitors of TMPK as potential antituberculosis agents.

Authors:  Carolina Horta Andrade; Kerly F M Pasqualoto; Elizabeth I Ferreira; Anton J Hopfinger
Journal:  J Comput Aided Mol Des       Date:  2010-03-10       Impact factor: 3.686

5.  Antimycobacterial agents. Novel diarylpyrrole derivatives of BM212 endowed with high activity toward Mycobacterium tuberculosis and low cytotoxicity.

Authors:  Mariangela Biava; Giulio Cesare Porretta; Giovanna Poce; Sibilla Supino; Delia Deidda; Raffaello Pompei; Paola Molicotti; Fabrizio Manetti; Maurizio Botta
Journal:  J Med Chem       Date:  2006-08-10       Impact factor: 7.446

6.  A collaborative database and computational models for tuberculosis drug discovery.

Authors:  Sean Ekins; Justin Bradford; Krishna Dole; Anna Spektor; Kellan Gregory; David Blondeau; Moses Hohman; Barry A Bunin
Journal:  Mol Biosyst       Date:  2010-02-09

7.  QSAR modeling of a set of pyrazinoate esters as antituberculosis prodrugs.

Authors:  João P S Fernandes; Kerly F M Pasqualoto; Veni M A Felli; Elizabeth I Ferreira; Carlos A Brandt
Journal:  Arch Pharm (Weinheim)       Date:  2010-02       Impact factor: 3.751

Review 8.  Genomic-scale prioritization of drug targets: the TDR Targets database.

Authors:  Fernán Agüero; Bissan Al-Lazikani; Martin Aslett; Matthew Berriman; Frederick S Buckner; Robert K Campbell; Santiago Carmona; Ian M Carruthers; A W Edith Chan; Feng Chen; Gregory J Crowther; Maria A Doyle; Christiane Hertz-Fowler; Andrew L Hopkins; Gregg McAllister; Solomon Nwaka; John P Overington; Arnab Pain; Gaia V Paolini; Ursula Pieper; Stuart A Ralph; Aaron Riechers; David S Roos; Andrej Sali; Dhanasekaran Shanmugam; Takashi Suzuki; Wesley C Van Voorhis; Christophe L M J Verlinde
Journal:  Nat Rev Drug Discov       Date:  2008-10-17       Impact factor: 84.694

9.  Synthetic EthR inhibitors boost antituberculous activity of ethionamide.

Authors:  Nicolas Willand; Bertrand Dirié; Xavier Carette; Pablo Bifani; Amit Singhal; Matthieu Desroses; Florence Leroux; Eve Willery; Vanessa Mathys; Rebecca Déprez-Poulain; Guy Delcroix; Frédéric Frénois; Marc Aumercier; Camille Locht; Vincent Villeret; Benoit Déprez; Alain R Baulard
Journal:  Nat Med       Date:  2009-05-03       Impact factor: 53.440

10.  Prioritizing genomic drug targets in pathogens: application to Mycobacterium tuberculosis.

Authors:  Samiul Hasan; Sabine Daugelat; P S Srinivasa Rao; Mark Schreiber
Journal:  PLoS Comput Biol       Date:  2006-06-09       Impact factor: 4.475

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  35 in total

1.  Computational models for neglected diseases: gaps and opportunities.

Authors:  Elizabeth L Ponder; Joel S Freundlich; Malabika Sarker; Sean Ekins
Journal:  Pharm Res       Date:  2013-08-30       Impact factor: 4.200

2.  Activity of lipophilic and hydrophilic drugs against dormant and replicating Mycobacterium tuberculosis.

Authors:  Giovanni Piccaro; Giovanna Poce; Mariangela Biava; Federico Giannoni; Lanfranco Fattorini
Journal:  J Antibiot (Tokyo)       Date:  2015-05-06       Impact factor: 2.649

3.  Combining cheminformatics methods and pathway analysis to identify molecules with whole-cell activity against Mycobacterium tuberculosis.

Authors:  Malabika Sarker; Carolyn Talcott; Peter Madrid; Sidharth Chopra; Barry A Bunin; Gyanu Lamichhane; Joel S Freundlich; Sean Ekins
Journal:  Pharm Res       Date:  2012-04-04       Impact factor: 4.200

4.  Bayesian models for screening and TB Mobile for target inference with Mycobacterium tuberculosis.

Authors:  Sean Ekins; Allen C Casey; David Roberts; Tanya Parish; Barry A Bunin
Journal:  Tuberculosis (Edinb)       Date:  2013-12-19       Impact factor: 3.131

Review 5.  Molecule Property Analyses of Active Compounds for Mycobacterium tuberculosis.

Authors:  Vadim Makarov; Elena Salina; Robert C Reynolds; Phyo Phyo Kyaw Zin; Sean Ekins
Journal:  J Med Chem       Date:  2020-04-20       Impact factor: 7.446

6.  Addressing the Metabolic Stability of Antituberculars through Machine Learning.

Authors:  Thomas P Stratton; Alexander L Perryman; Catherine Vilchèze; Riccardo Russo; Shao-Gang Li; Jimmy S Patel; Eric Singleton; Sean Ekins; Nancy Connell; William R Jacobs; Joel S Freundlich
Journal:  ACS Med Chem Lett       Date:  2017-09-14       Impact factor: 4.345

Review 7.  Collaborative drug discovery for More Medicines for Tuberculosis (MM4TB).

Authors:  Sean Ekins; Anna Coulon Spektor; Alex M Clark; Krishna Dole; Barry A Bunin
Journal:  Drug Discov Today       Date:  2016-11-22       Impact factor: 7.851

Review 8.  Translating basic science insight into public health action for multidrug- and extensively drug-resistant tuberculosis.

Authors:  Nicholas D Walter; Michael Strong; Robert Belknap; Diane J Ordway; Charles L Daley; Edward D Chan
Journal:  Respirology       Date:  2012-07       Impact factor: 6.424

9.  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

10.  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

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