Evidence map›Paper›PMID 25676821›Full record

ArticleJournal of computer-aided molecular design2015

Covalent docking of selected boron-based serine beta-lactamase inhibitors.

Jacopo Sgrignani, Beatrice Novati, Giorgio Colombo, Giovanni Grazioso

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In one paragraph

Article in Journal of computer-aided molecular design, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 25% 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

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Docking Screens for Novel Ligands Conferring New Biology.Journal of medicinal chemistry · 2016
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Jacopo SgrignaniICRM-CNR, Via Mario Bianco 9, 20131, Milan, Italy.
Beatrice Novati
Giorgio Colombo
Giovanni Grazioso
Institute of Chemistry of Molecular Recognition · ITUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AmpC β-lactamase is a hydrolytic enzyme conferring resistance to β-lactam antibiotics in multiple Gram-negative bacteria. Therefore, identification of non-β-lactam compounds able to inhibit the enzyme is crucial for the development of novel antibacterial therapies. In general, AmpC inhibitors have to engage the highly solvent-exposed catalytic site of the enzyme. Therefore, understanding the implications of ligand-protein induced-fit and water-mediated interactions behind the inhibitor-enzyme recognition process is fundamental for undertaking structure-based drug design process. Here, we focus on boronic acids, a promising class of beta-lactamase covalent inhibitors. First, we optimized a docking protocol able to reproduce the experimentally determined binding mode of AmpC inhibitors bearing a boronic group. This goal was pursued (1) performing rigid and flexible docking calculations aiming to establish the role of the side chain conformations; and (2) investigating the role of specific water molecules in shaping the enzyme active site and mediating ligand protein interactions. Our calculations showed that some water molecules, conserved in the majority of the considered X-ray structures, are needed to correctly predict the binding pose of known covalent AmpC inhibitors. On this basis, we formalized our findings in a docking and scoring protocol that could be useful for the structure-based design of new boronic acid AmpC inhibitors.

Indexed as

Molecular Docking Simulationbeta-Lactamase Inhibitorsbeta-LactamasesBoronHumansMolecular StructureSerinebeta-Lactamase Inhibitorsbeta-LactamasesBoronSerine

Identifiers

PMID25676821
OpenAlexW2069946470

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.