ArticlePLoS computational biology2010
The Mycobacterium tuberculosis drugome and its polypharmacological implications.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
52 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Repurposing drugs for treatment of tuberculosis: a role for non-steroidal anti-inflammatory drugs.British medical bulletin · 2016Pooled it
- Probabilistic identification of bacterial essential genes via insertion density using TraDIS data with Tn5 libraries.Bioinformatics (Oxford, England) · 2021Article
- Targeting the actin nucleation promoting factor WASp provides a therapeutic approach for hematopoietic malignancies.Nature communications · 2021Article
- Label-Free Comparative Proteomics of Differentially ExpressedPathogens (Basel, Switzerland) · 2021Article
- Mycobacterial drug discovery.RSC medicinal chemistry · 2020Review
- A Multi-Pronged Computational Pipeline for Prioritizing Drug Target Strategies for Latent Tuberculosis.Frontiers in chemistry · 2020Article
- Article
- RepTB: a gene ontology based drug repurposing approach for tuberculosis.Journal of cheminformatics · 2018Article
- Three-dimensional models of Mycobacterium tuberculosis proteins Rv1555, Rv1554 and their docking analyses with sildenafil, tadalafil, vardenafil drugs, suggest interference with quinol binding likely to affect protein's function.BMC structural biology · 2018Article
- The Druggable Pocketome ofFrontiers in genetics · 2018Article
- Structure based drug discovery for designing leads for the non-toxic metabolic targets in multi drug resistant Mycobacterium tuberculosis.Journal of translational medicine · 2017Article
- Decoding the similarities and differences among mycobacterial species.PLoS neglected tropical diseases · 2017Article
- Reproducibility of computational workflows is automated using continuous analysis.Nature biotechnology · 2017Article
- Collaborative drug discovery for More Medicines for Tuberculosis (MM4TB).Drug discovery today · 2017Review
- Harnessing Big Data for Systems Pharmacology.Annual review of pharmacology and toxicology · 2017Review
- Targeting DNA Replication and Repair for the Development of Novel Therapeutics against Tuberculosis.Frontiers in molecular biosciences · 2017Review
- TIBLE: a web-based, freely accessible resource for small-molecule binding data for mycobacterial species.Database : the journal of biological databases and curation · 2017Article
- Bioinformatics and Drug Discovery.Current topics in medicinal chemistry · 2017Review
- Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.Scientific reports · 2016Article
- Delineation of Polypharmacology across the Human Structural Kinome Using a Functional Site Interaction Fingerprint Approach.Journal of medicinal chemistry · 2016Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
We report a computational approach that integrates structural bioinformatics, molecular modelling and systems biology to construct a drug-target network on a structural proteome-wide scale. The approach has been applied to the genome of Mycobacterium tuberculosis (M.tb), the causative agent of one of today's most widely spread infectious diseases. The resulting drug-target interaction network for all structurally characterized approved drugs bound to putative M.tb receptors, we refer to as the 'TB-drugome'. The TB-drugome reveals that approximately one-third of the drugs examined have the potential to be repositioned to treat tuberculosis and that many currently unexploited M.tb receptors may be chemically druggable and could serve as novel anti-tubercular targets. Furthermore, a detailed analysis of the TB-drugome has shed new light on the controversial issues surrounding drug-target networks [1]-[3]. Indeed, our results support the idea that drug-target networks are inherently modular, and further that any observed randomness is mainly caused by biased target coverage. The TB-drugome (http://funsite.sdsc.edu/drugome/TB) has the potential to be a valuable resource in the development of safe and efficient anti-tubercular drugs. More generally the methodology may be applied to other pathogens of interest with results improving as more of their structural proteomes are determined through the continued efforts of structural biology/genomics.
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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.