Evidence map›Paper›PMID 31854205›Full record

ArticleJournal of enzyme inhibition and medicinal chemistry2020

Development of a cheminformatics platform for selectivity analyses of carbonic anhydrase inhibitors.

Giulio Poli, Salvatore Galati, Adriano Martinelli, Claudiu T Supuran, Tiziano Tuccinardi

Abstract read
In one paragraph

Article in Journal of enzyme inhibition and medicinal chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. New isoxazolidinyl-basedJournal of enzyme inhibition and medicinal chemistry · 2023
    Article
  2. Multiple machine learning methods aided virtual screening of NaJournal of cellular and molecular medicine · 2023
    Article
  3. Article
  4. Article
  5. Article
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

5 authors.

Giulio PoliDepartment of Pharmacy, University of Pisa, Pisa, Italy.
Salvatore GalatiDepartment of Pharmacy, University of Pisa, Pisa, Italy.
Adriano MartinelliDepartment of Pharmacy, University of Pisa, Pisa, Italy.
Claudiu T SupuranNEUROFARBA Department, Sezione di Scienze Farmaceutiche, Università degli Studi di Firenze, Florence, Italy.ORCID http://orcid.org/0000-0003-4262-0323
Tiziano TuccinardiDepartment of Pharmacy, University of Pisa, Pisa, Italy.ORCID http://orcid.org/0000-0002-6205-4069

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The selectivity for a specific human Carbonic Anhydrase (hCA) isoform is an important property a hCA inhibitor (CAI) should be endowed with, in order to constitute a valuable therapeutic tool for the treatment of a desired pathology. In this context, we developed a chemoinformatic platform that allows the analysis of the structure and selectivity profile of known CAIs reported in literature, with the aim of identifying structural motifs connected to ligand selectivity, thus providing useful guidelines for the design of novel ligands selective for the desired hCA isoform. The platform is able to perform ultrafast structure and selectivity analyses through ligand fingerprint similarity, with no need of structural information about the target receptor and ligands' binding mode. It is easily accessible to the non-expert user through the implementation of a KNIME Analytic Platform workflow and could be extended to analyze the selectivity profile of known ligands of different target proteins.

Indexed as

CheminformaticsCarbonic Anhydrase InhibitorsCarbonic AnhydrasesCluster AnalysisDose-Response Relationship, DrugHumansIsoenzymesLigandsMolecular StructureStructure-Activity RelationshipCarbonic Anhydrase InhibitorsCarbonic AnhydrasesIsoenzymesLigandsCarbonic anhydraseclusteringfingerprintselectivity

Identifiers

PMID31854205
PMCPMC6968703

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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.