Evidence map›Paper›PMID 36866608›Full record

ArticleEssays in biochemistry2023

Protein-RNA interactions: from mass spectrometry to drug discovery.

Benjamin Steinmetz, Izabela Smok, Maria Bikaki, Alexander Leitner

Open access · hybridAbstract read
In one paragraph

Article in Essays in biochemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

9 citing papers in PubMed, 9 citations in OpenAlex.

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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.

Benjamin Steinmetz *Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, 8093 Zurich, Switzerland.
Izabela Smok *Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, 8093 Zurich, Switzerland.
Maria BikakiDepartment of Biology, Institute of Molecular Systems Biology, ETH Zürich, 8093 Zurich, Switzerland.
Alexander Leitner *Department of Biology, Institute of Molecular Systems Biology, ETH Zürich, 8093 Zurich, Switzerland.ORCID 0000-0003-4126-0725
ETH Zurich · CHUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteins and RNAs are fundamental parts of biological systems, and their interactions affect many essential cellular processes. Therefore, it is crucial to understand at a molecular and at a systems level how proteins and RNAs form complexes and mutually affect their functions. In the present mini-review, we will first provide an overview of different mass spectrometry (MS)-based methods to study the RNA-binding proteome (RBPome), most of which are based on photochemical cross-linking. As we will show, some of these methods are also able to provide higher-resolution information about binding sites, which are important for the structural characterisation of protein-RNA interactions. In addition, classical structural biology techniques such as nuclear magnetic resonance (NMR) spectroscopy and biophysical methods such as electron paramagnetic resonance (EPR) spectroscopy and fluorescence-based methods contribute to a detailed understanding of the interactions between these two classes of biomolecules. We will discuss the relevance of such interactions in the context of the formation of membrane-less organelles (MLOs) by liquid-liquid phase separation (LLPS) processes and their emerging importance as targets for drug discovery.

Indexed as

ProteinsRNADrug DiscoveryMagnetic Resonance SpectroscopyMass SpectrometryProteinsRNAcross-linkingmass spectrometryprotein-RNA complexesprotein-RNA interactions

Identifiers

PMID36866608
PMCPMC10070478
OpenAlexW4323037614

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.