ArticleDatabase : the journal of biological databases and curation2014
TuberQ: a Mycobacterium tuberculosis protein druggability database.
Article in Database : the journal of biological databases and curation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 41 citations in OpenAlex.
- The applications of deep learning algorithms on in silico druggable proteins identification.Journal of advanced research · 2022Article
- Article
- Protein Integrated Network Analysis to Reveal Potential Drug Targets Against Extended Drug-Resistant Mycobacterium tuberculosis XDR1219.Molecular biotechnology · 2021Article
- Identification of Potential Kinase Inhibitors within the PI3K/AKT Pathway ofBiomolecules · 2021Article
- From Genome to Drugs: New Approaches in Antimicrobial Discovery.Frontiers in pharmacology · 2021Review
- Mycobacterial drug discovery.RSC medicinal chemistry · 2020Review
- Genomics, Computational Biology and Drug Discovery for Mycobacterial Infections: Fighting the Emergence of Resistance.Frontiers in genetics · 2020Review
- MycoResistance: a curated resource of drug resistance molecules in Mycobacteria.Database : the journal of biological databases and curation · 2019Article
- Sequence-Derived Markers of Drug Targets and Potentially Druggable Human Proteins.Frontiers in genetics · 2019Article
- Quantifying Gene Essentiality Based on the Context of Cellular Components.Frontiers in genetics · 2019Article
- An integrative, multi-omics approach towards the prioritization of Klebsiella pneumoniae drug targets.Scientific reports · 2018Article
- Target-Pathogen: a structural bioinformatic approach to prioritize drug targets in pathogens.Nucleic acids research · 2018Article
- Fluoromycobacteriophages Can Detect ViableFrontiers in microbiology · 2018Article
- The Druggable Pocketome ofFrontiers in genetics · 2018Article
- Bioinformatics in translational drug discovery.Bioscience reports · 2017Review
- Decoding the similarities and differences among mycobacterial species.PLoS neglected tropical diseases · 2017Article
- Data Intensive Genome Level Analysis for Identifying Novel, Non-Toxic Drug Targets for Multi Drug Resistant Mycobacterium tuberculosis.Scientific reports · 2017Article
- An integrated structural proteomics approach along the druggable genome of Corynebacterium pseudotuberculosis species for putative druggable targets.BMC genomics · 2015Article
- The future for early-stage tuberculosis drug discovery.Future microbiology · 2015Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In 2012 an estimated 8.6 million people developed tuberculosis (TB) and 1.3 million died from the disease [including 320 000 deaths among human immunodeficiency virus (HIV)-positive people]. There is an urgent need for new anti-TB drugs owing to the following: the fact that current treatments have severe side effects, the increasing emergence of multidrug-resistant strains of Mycobacterium tuberculosis (Mtb), the negative drug-drug interactions with certain HIV (or other disease) treatments and the ineffectiveness against dormant Mtb. In this context we present here the TuberQ database, a novel resource for all researchers working in the field of drug development in TB. The main feature of TuberQ is to provide a druggability analysis of Mtb proteins in a consistent and effective manner, contributing to a better selection of potential drug targets for screening campaigns and the analysis of targets for structure-based drug design projects. The structural druggability analysis is combined with features related to the characteristics of putative inhibitor binding pockets and with functional and biological data of proteins. The structural analysis is performed on all available unique Mtb structures and high-quality structural homology-based models. This information is shown in an interactive manner, depicting the protein structure, the pockets and the associated characteristics for each protein. TuberQ also provides information about gene essentiality information, as determined from whole cell-based knockout experiments, and expression information obtained from microarray experiments done in different stress-related conditions. We hope that TuberQ will be a powerful tool for researchers working in TB and eventually will lead to the identification of novel putative targets and progresses in therapeutic activities. Database URL: http://tuberq.proteinq.com.ar/
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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.