Evidence map›Paper›PMID 29759983›Full record

ArticleMolecular systems biology2018

High-throughput discovery of functional disordered regions: investigation of transactivation domains.

Charles Nj Ravarani, Tamara Y Erkina, Greet De Baets, Daniel C Dudman, Alexandre M Erkine, M Madan Babu

Open access · goldAbstract read
In one paragraph

Article in Molecular systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed
6.8field-weighted citation impact, top 2% 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

73 citing papers in PubMed, 188 citations in OpenAlex.

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13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Charles Nj RavaraniMRC Laboratory of Molecular Biology, Cambridge, UK ravarani@mrc-lmb.cam.ac.uk aerkine@butler.edu madanm@mrc-lmb.cam.ac.uk.ORCID 0000-0003-0952-3396
Tamara Y ErkinaButler University, Indianapolis, IN, USA.
Greet De BaetsMRC Laboratory of Molecular Biology, Cambridge, UK.
Daniel C DudmanButler University, Indianapolis, IN, USA.
Alexandre M ErkineButler University, Indianapolis, IN, USA ravarani@mrc-lmb.cam.ac.uk aerkine@butler.edu madanm@mrc-lmb.cam.ac.uk.ORCID 0000-0002-1880-4854
M Madan BabuMRC Laboratory of Molecular Biology, Cambridge, UK ravarani@mrc-lmb.cam.ac.uk aerkine@butler.edu madanm@mrc-lmb.cam.ac.uk.ORCID 0000-0003-0556-6196
Butler University · USMRC Laboratory of Molecular Biology · GB

Funding

Medical Research Council MC_U105185859
6 · The paper itself

Abstract

Over 40% of proteins in any eukaryotic genome encode intrinsically disordered regions (IDRs) that do not adopt defined tertiary structures. Certain IDRs perform critical functions, but discovering them is non-trivial as the biological context determines their function. We present IDR-Screen, a framework to discover functional IDRs in a high-throughput manner by simultaneously assaying large numbers of DNA sequences that code for short disordered sequences. Functionality-conferring patterns in their protein sequence are inferred through statistical learning. Using yeast HSF1 transcription factor-based assay, we discovered IDRs that function as transactivation domains (TADs) by screening a random sequence library and a designed library consisting of variants of 13 diverse TADs. Using machine learning, we find that segments devoid of positively charged residues but with redundant short sequence patterns of negatively charged and aromatic residues are a generic feature for TAD functionality. We anticipate that investigating defined sequence libraries using IDR-Screen for specific functions can facilitate discovering novel and functional regions of the disordered proteome as well as understand the impact of natural and disease variants in disordered segments.

Indexed as

Transcriptional ActivationCloning, MolecularDNA-Binding ProteinsGene LibraryHeat-Shock ProteinsHigh-Throughput Nucleotide SequencingMachine LearningProteomeSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSequence Analysis, DNATranscription FactorsDNA-Binding ProteinsHeat-Shock ProteinsHSF1 protein, S cerevisiaeProteomeSaccharomyces cerevisiae ProteinsTranscription Factorshigh‐throughput screenintrinsically disordered proteinmachine learningmutational scanningtransactivation domain

Identifiers

PMID29759983
PMCPMC5949888
OpenAlexW2803006006

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.