Evidence map›Paper›PMID 36032402›Full record

ArticleBiochemistry and biophysics reports2022

Development of a novel pharmacophore model to screen specific inhibitors for the serine-threonine protein phosphatase calcineurin.

Abhisek Mukherjee, Karina Cuanalo-Contreras, Abha Sood, Claudio Soto

Abstract read
In one paragraph

Article in Biochemistry and biophysics reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Abhisek MukherjeeMitchell Center for Alzheimer's Disease and Related Brain Disorders, Department of Neurology, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX, 77030, USA.
Karina Cuanalo-ContrerasMitchell Center for Alzheimer's Disease and Related Brain Disorders, Department of Neurology, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX, 77030, USA.
Abha SoodThe Department of Chemistry and Biochemistry, Georgia Southern University, USA.
Claudio SotoMitchell Center for Alzheimer's Disease and Related Brain Disorders, Department of Neurology, McGovern Medical School, University of Texas Health Science at Houston, Houston, TX, 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Calcineurin (CaN) is a calcium/calmodulin-dependent serine/threonine phosphatase with a crucial role in cellular homeostasis. It is also the target of the Food and Drug Administration (FDA) approved immunosuppressant drugs FK506 and cyclosporine A. Recent work from our group and others indicated that an uncontrolled increase in CaN activity causes synaptic dysfunction and neuronal death in various models of neurodegenerative diseases associated with calcium dysregulation. Furthermore, pharmacological normalization of CaN activity can prevent disease progression in animal models. However, none of the FDA-approved CaN inhibitors bind CaN directly, leading to adverse side effects. The development of direct CaN inhibitors is required to reduce off-target effects, but its highly conserved active site and similar mechanism of action with other protein serine/threonine phosphatases impose a significant challenge. In this work, we developed a novel pharmacophore model to screen for CaN-specific inhibitors. Then, we performed a virtual screen for molecules having the pharmacophore model. We also show that the molecules identified in this screen can inhibit CaN with a low micromolar IC

Identifiers

PMID36032402
PMCPMC9398911

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.