ReviewTrends in microbiology2011
Computational databases, pathway and cheminformatics tools for tuberculosis drug discovery.
Review in Trends in microbiology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed.
- Drug Discovery forInternational journal of molecular sciences · 2021Review
- Structure-aided optimization of non-nucleoside M. tuberculosis thymidylate kinase inhibitors.European journal of medicinal chemistry · 2021Article
- Anti-tubercular profile of new selenium-menadione conjugates against Mycobacterium tuberculosis H37Rv (ATCC 27294) strain and multidrug-resistant clinical isolates.European journal of medicinal chemistry · 2021Article
- Pangenome Analysis ofAntibiotics (Basel, Switzerland) · 2020Article
- Molecule Property Analyses of Active Compounds forJournal of medicinal chemistry · 2020Review
- Review
- Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era.Frontiers in microbiology · 2020Review
- Handling the Hurdles on the Way to Anti-tuberculosis Drug Development.Frontiers in chemistry · 2020Review
- Designing novel possible kinase inhibitor derivatives as therapeutics against Mycobacterium tuberculosis: An in silico study.Scientific reports · 2019Article
- Review
- Spectrophores as one-dimensional descriptors calculated from three-dimensional atomic properties: applications ranging from scaffold hopping to multi-target virtual screening.Journal of cheminformatics · 2018Article
- Challenging the Drug-Likeness Dogma for New Drug Discovery in Tuberculosis.Frontiers in microbiology · 2018Review
- Addressing the Metabolic Stability of Antituberculars through Machine Learning.ACS medicinal chemistry letters · 2017Article
- A genome-wide structure-based survey of nucleotide binding proteins in M. tuberculosis.Scientific reports · 2017Article
- Collaborative drug discovery for More Medicines for Tuberculosis (MM4TB).Drug discovery today · 2017Review
- Predictive modeling targets thymidylate synthase ThyX in Mycobacterium tuberculosis.Scientific reports · 2016Article
- Activity of lipophilic and hydrophilic drugs against dormant and replicating Mycobacterium tuberculosis.The Journal of antibiotics · 2015Article
- Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.PloS one · 2015Article
- In-silico Metabolome Target Analysis Towards PanC-based Antimycobacterial Agent Discovery.Iranian journal of pharmaceutical research : IJPR · 2015Article
- BioPhytMol: a drug discovery community resource on anti-mycobacterial phytomolecules and plant extracts.Journal of cheminformatics · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.