Evidence map›Paper›PMID 30200318›Full record

ArticleInternational journal of molecular sciences2018

Structural Prediction of the Dimeric Form of the Mammalian Translocator Membrane Protein TSPO: A Key Target for Brain Diagnostics.

Juan Zeng, Riccardo Guareschi, Mangesh Damre, Ruyin Cao, Achim Kless, Bernd Neumaier, Andreas Bauer, Alejandro Giorgetti, Paolo Carloni, Giulia Rossetti

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 18 citations in OpenAlex.

  1. TSPO protein binding partners in bacteria, animals, and plants.Journal of bioenergetics and biomembranes · 2021
    Review
  2. The Interplay of Cholesterol and Ligand Binding inMolecules (Basel, Switzerland) · 2021
    Article
  3. Article
  4. Article
  5. Review
  6. Applications of water molecules for analysis of macromolecule properties.Computational and structural biotechnology journal · 2020
    Review
  7. 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

10 authors at 3 institutions in 3 countries.

Juan ZengInstitute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany. j.zeng@fz-juelich.de.ORCID 0000-0001-8227-0415
Riccardo GuareschiInstitute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany. r.guareschi@fz-juelich.de.
Mangesh DamreDepartment of Biotechnology, University of Verona, Strada Le Grazie 15, 37134 Verona, Italy. mangeshdamre007@gmail.com.ORCID 0000-0002-4371-3815
Ruyin CaoInstitute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany. caobb0214@gmail.com.
Achim KlessGrünenthal Innovation, Translational Science & Intelligence, Grünenthal GmbH, 52078 Aachen, Germany. Achim.Kless@grunenthal.com.ORCID 0000-0001-8301-5934
Bernd NeumaierInstitute for Neuroscience and Medicine (INM)-5, Forschungszentrum Jülich, 52428 Jülich, Germany. b.neumaier@fz-juelich.de.ORCID 0000-0001-5425-3116
Andreas BauerInstitute for Neuroscience and Medicine (INM)-2, Forschungszentrum Jülich, 52428 Jülich, Germany. an.bauer@fz-juelich.de.
Alejandro GiorgettiInstitute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany. alejandro.giorgetti@univr.it.
Paolo CarloniInstitute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany. p.carloni@fz-juelich.de.
Giulia RossettiInstitute for Advanced Simulations (IAS)-5/Institute for Neuroscience and Medicine (INM)-9, Forschungszentrum Jülich, 52428 Jülich, Germany. g.rossetti@fz-juelich.de.ORCID 0000-0002-2032-4630
Forschungszentrum Jülich · DEUniversity of Verona · ITGrünenthal Group (Germany) · DE

Funding

Nordrhein-Westfalen/Eurpean Union 2) National Natural Science Foundation of China 1) EFRE-0800988 2) 21603006
6 · The paper itself

Abstract

Positron emission tomography (PET) radioligands targeting the human translocator membrane protein (TSPO) are broadly used for the investigations of neuroinflammatory conditions associated with neurological disorders. Structural information on the mammalian protein homodimers-the suggested functional state of the protein-is limited to a solid-state nuclear magnetic resonance (NMR) study and to a model based on the previously-deposited solution NMR structure of the monomeric mouse protein. Computational studies performed here suggest that the NMR-solved structure in the presence of detergents is not prone to dimer formation and is furthermore unstable in its native membrane environment. We, therefore, propose a new model of the functionally-relevant dimeric form of the mouse protein, based on a prokaryotic homologue. The model, fully consistent with solid-state NMR data, is very different from the previous predictions. Hence, it provides, for the first time, structural insights into this pharmaceutically-important target which are fully consistent with experimental data.

Indexed as

Molecular Docking SimulationProtein MultimerizationAnimalsBinding SitesCholesterolLigandsPositron-Emission TomographyProtein BindingReceptors, GABABzrp protein, mouseCholesterolLigandsReceptors, GABAbrain inflammationdockinghomology modelingmolecular dynamicsoligomerizationPETradioligandsTSPO

Identifiers

PMID30200318
PMCPMC6165245
OpenAlexW2889430150

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.