ArticleBMC genomics2019
Investigating function roles of hypothetical proteins encoded by the Mycobacterium tuberculosis H37Rv genome.
Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
37 citing papers in PubMed, 75 citations in OpenAlex.
- Recent Characterization of Key Proteins to Combat Tuberculosis.Advances in experimental medicine and biology · 2026Review
- Innate immune recognition ofCell surface (Amsterdam, Netherlands) · 2025Review
- Genome-Wide Identification of Novel miRNAs and Infection-Related Proteins inPathogens (Basel, Switzerland) · 2025Article
- Candidate transmission survival genome ofProceedings of the National Academy of Sciences of the United States of America · 2025Article
- Global epidemiology of Mycobacterium tuberculosis lineage 4 insights from Ecuadorian genomic data.Scientific reports · 2025Article
- Comparative Transcriptomics Reveal Differential Expression of Coding and Non-Coding RNAs in Clinical Strains ofInternational journal of molecular sciences · 2024Article
- sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms.BMC genomics · 2024Article
- Potential involvement of beta-lactamase homologous proteins in resistance to beta-lactam antibiotics in gram-negative bacteria of the ESKAPEE group.BMC genomics · 2024Article
- Identification of novel single nucleotide variants in the drug resistance mechanism of Mycobacterium tuberculosis isolates by whole-genome analysis.BMC genomics · 2024Article
- Computational Approaches for the Structure-Based Identification of Novel Inhibitors Targeting Nucleoid-Associated Proteins in Mycobacterium Tuberculosis.Molecular biotechnology · 2024Article
- Biochemical and structural characterization reveals Rv3400 codes for β-phosphoglucomutase in Mycobacterium tuberculosis.Protein science : a publication of the Protein Society · 2024Article
- Genome mining ofFrontiers in microbiology · 2024Article
- In silico analysis of a novel hypothetical protein (YP_498675.1) from Staphylococcus aureus unravels the protein of tryptophan synthase beta superfamily (Try-synth-beta_ II).Journal, genetic engineering & biotechnology · 2023Article
- Synthesis and Biological Activity of Piperidinothiosemicarbazones Derived from Aminoazinecarbonitriles.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Design of a Multi-Epitope Vaccine against Tuberculosis fromMicroorganisms · 2023Article
- Pathogen-associated gene discovery workflows for novel antivirulence therapeutic development.EBioMedicine · 2023Review
- In Silico Functional Characterization of a Hypothetical Protein FromBioinformatics and biology insights · 2023Article
- Comparative genomics of drug-resistant strains of Mycobacterium tuberculosis in Ecuador.BMC genomics · 2022Article
- Investigating a putative transcriptional regulatory protein encoded by Rv1719 gene of Mycobacterium tuberculosis.The protein journal · 2022Article
- In silico and in vitro study of Mycobacterium tuberculosis H37Rv uncharacterized protein (RipD): an insight on tuberculosis therapeutics.Journal of molecular modeling · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundMycobacterium tuberculosis (MTB) is a common bacterium causing tuberculosis and remains a major pathogen for mortality. Although the MTB genome has been extensively explored for two decades, the functions of 27% (1051/3906) of encoded proteins have yet to be determined and these proteins are annotated as hypothetical proteins.
methodsWe assigned functions to these hypothetical proteins using SSEalign, a newly designed algorithm utilizing structural information. A set of rigorous criteria was applied to these annotations in order to examine whether they were supported by each parameter. Virulence factors and potential drug targets were also screened among the annotated proteins.
resultsFor 78% (823/1051) of the hypothetical proteins, we could identify homologs in Escherichia coli and Salmonella typhimurium by using SSEalign. Functional classification analysis indicated that 62.2% (512/823) of these annotated proteins were enzymes with catalytic activities and most of these annotations were supported by at least two other independent parameters. A relatively high proportion of transporter was identified in MTB genome, indicating the potential frequent transportation of frequent absorbing essential metabolites and excreting toxic materials in MTB. Twelve virulence factors and ten vaccine candidates were identified within these MTB hypothetical proteins, including two genes (rpoS and pspA) related to stress response to the host immune system. Furthermore, we have identified six novel drug target candidates among our annotated proteins, including Rv0817 and Rv2927c, which could be used for treating MTB infection.
conclusionsOur annotation of the MTB hypothetical proteins will probably serve as a useful dataset for future MTB studies.
Indexed as
Identifiers
What OpenQuestion holds
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.