Evidence map›Paper›PMID 22102165›Full record

ArticleJournal of molecular modeling2012

Homology modeling and docking analyses of M. leprae Mur ligases reveals the common binding residues for structure based drug designing to eradicate leprosy.

Anusuya Shanmugam, Jeyakumar Natarajan

Abstract read
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In one paragraph

Article in Journal of molecular modeling, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
1 · What the graph read from it

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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Crystallization and preliminary X-ray analysis of a UDP-MurNAc-tripeptide D-alanyl-D-alanine-adding enzyme (PaMurF) from Pseudomonas aeruginosa.Acta crystallographica. Section F, Structural biology and crystallization communications · 2013
    Article
4 · The record

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5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Anusuya ShanmugamDepartment of Bioinformatics, VMKV Engineering College, Vinayaka Missions University, Salem, India.
Jeyakumar Natarajan
Bharathiar University · INVinayaka Missions University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multi drug resistance capacity for Mycobacterium leprae (MDR-Mle) demands the profound need for developing new anti-leprosy drugs. Since most of the drugs target a single enzyme, mutation in the active site renders the antibiotic ineffective. However, structural and mechanistic information on essential bacterial enzymes in a pathway could lead to the development of antibiotics that targets multiple enzymes. Peptidoglycan is an important component of the cell wall of M. leprae. The biosynthesis of bacterial peptidoglycan represents important targets for the development of new antibacterial drugs. Biosynthesis of peptidoglycan is a multi-step process that involves four key Mur ligase enzymes: MurC (EC:6.3.2.8), MurD (EC:6.3.2.9), MurE (EC:6.3.2.13) and MurF (EC:6.3.2.10). Hence in our work, we modeled the three-dimensional structure of the above Mur ligases using homology modeling method and analyzed its common binding features. The residues playing an important role in the catalytic activity of each of the Mur enzymes were predicted by docking these Mur ligases with their substrates and ATP. The conserved sequence motifs significant for ATP binding were predicted as the probable residues for structure based drug designing. Overall, the study was successful in listing significant and common binding residues of Mur enzymes in peptidoglycan pathway for multi targeted therapy.

Indexed as

Adenosine TriphosphateAmino Acid MotifsAmino Acid SequenceBacterial ProteinsCatalytic DomainConserved SequenceDrug DesignGlutamic AcidGlycineHistidineHumansHydrogen BondingLeprosyModels, MolecularMolecular Sequence DataMycobacterium lepraeAdenosine TriphosphateBacterial ProteinsGlutamic AcidGlycineHistidinePeptide SynthasesUDP-N-acetylmuramoylalanine-D-glutamate ligase

Identifiers

PMID22102165
OpenAlexW2001590171

What OpenQuestion holds

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Registered trials

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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.