Evidence map›Paper›PMID 25475113›Full record

ArticleDatabase : the journal of biological databases and curation2014

CBMAR: a comprehensive β-lactamase molecular annotation resource.

Abhishikha Srivastava, Neelja Singhal, Manisha Goel, Jugsharan Singh Virdi, Manish Kumar

Abstract read
In one paragraph

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 26 papers.

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26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. BacARscan: anBiology methods & protocols · 2022
    Article
  11. Investigating the OXA Variants of ESKAPE Pathogens.Antibiotics (Basel, Switzerland) · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Abhishikha SrivastavaDepartment of Biophysics and Department of Microbiology, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India.
Neelja SinghalDepartment of Biophysics and Department of Microbiology, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India.
Manisha GoelDepartment of Biophysics and Department of Microbiology, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India.
Jugsharan Singh VirdiDepartment of Biophysics and Department of Microbiology, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India.
Manish KumarDepartment of Biophysics and Department of Microbiology, University of Delhi South Campus, Benito Juarez Road, New Delhi 110021, India manish@south.du.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

β-Lactam antibiotics are among the most widely used antibiotics against microbial pathogens. However, enzymatic hydrolysis of these antibiotics by bacterial β-lactamases is increasingly compromising their efficiency. Although new generation β-lactam antibiotics have been developed to combat antibiotic resistance, β-lactamases have also evolved along with the new variants of the substrate. A strong selection pressure from the newer generation of β-lactam antibiotics has resulted in evolution of different families within each class of β-lactamase. To facilitate detailed characterization of different families of β-lactamases, we have created a database, CBMAR, which facilitates comprehensive molecular annotation and discovery of novel β-lactamases. As against the limited scope of other existing similar databases, CBMAR provides information useful for molecular and biochemical characterization of each family of β-lactamase. The basic architecture of CBMAR is based on Ambler classification, which divides β-lactamases as serine (Classes A, C and D) and metallo-β-lactamases (Class B). Each class is further divided into several families on the basis of their hydrolytic character. In CBMAR, each family is annotated with (i) sequence variability, (ii) antibiotic resistance profile, (iii) inhibitor susceptibility, (iv) active site, (v) family fingerprints, (vi) mutational profile, (vii) variants, (viii) gene location, (ix) phylogenetic tree and several other features. Each entry also has external links to the relevant protein/nucleotide sequence and structure databases. The database also supports sequence similarity searches using BLAST and assigns a new β-lactamase protein to its respective family on the basis of family-specific fingerprint. Database URL: http://14.139.227.92/mkumar/lactamasedb

Indexed as

Databases, ProteinMolecular Sequence AnnotationAmino Acid Sequencebeta-LactamasesInternetbeta-Lactamases

Identifiers

PMID25475113
PMCPMC4255060

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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.