Evidence map›Paper›PMID 35762712›Full record

ArticleProtein science : a publication of the Protein Society2022

Structural and functional determinants inferred from deep mutational scans.

Priyanka Bajaj, Kavyashree Manjunath, Raghavan Varadarajan

Open access · bronzeAbstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2022. 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
1.9field-weighted citation impact, top 14% 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

5 citing papers in PubMed, 10 citations in OpenAlex.

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  5. Structural and functional determinants inferred from deep mutational scans.Protein science : a publication of the Protein Society · 2022
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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

3 authors at 2 institutions in 1 country.

Priyanka BajajMolecular Biophysics Unit, Indian Institute of Science, Bangalore, India.ORCID 0000-0001-8474-6149
Kavyashree ManjunathCentre for Chemical Biology and Therapeutics, Institute for Stem Cell Science and Regenerative Medicine, Bangalore, India.
Raghavan VaradarajanMolecular Biophysics Unit, Indian Institute of Science, Bangalore, India.
Indian Institute of Science Bangalore · INInstitute for Stem Cell Biology and Regenerative Medicine · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutations that affect protein binding to a cognate partner primarily occur either at buried residues or at exposed residues directly involved in partner binding. Distinguishing between these two categories based solely on mutational phenotypes is challenging. The bacterial toxin CcdB kills cells by binding to DNA Gyrase. Cell death is prevented by binding to its cognate antitoxin CcdA, at an extended interface that partially overlaps with the GyrA binding site. Using the CcdAB toxin-antitoxin (TA) system as a model, a comprehensive site-saturation mutagenesis library of CcdB was generated in its native operonic context. The mutational sensitivity of each mutant was estimated by evaluating the relative abundance of each mutant in two strains, one resistant and the other sensitive to the toxic activity of the CcdB toxin, through deep sequencing. The ability to bind CcdA was inferred through a RelE reporter gene assay, since the CcdAB complex binds to its own promoter, repressing transcription. By analyzing mutant phenotypes in the CcdB-sensitive, CcdB-resistant, and RelE reporter strains, it was possible to assign residues to buried, CcdA interacting or GyrA interacting sites. A few mutants were individually constructed, expressed, and biophysically characterized to validate molecular mechanisms responsible for the observed phenotypes. Residues inferred to be important for antitoxin binding, are also likely to be important for rejuvenating CcdB from the CcdB-Gyrase complex. Therefore, even in the absence of structural information, when coupled to appropriate genetic screens, such high-throughput strategies can be deployed for predicting structural and functional determinants of proteins.

Indexed as

AntitoxinsBacterial ProteinsDNA GyraseEscherichia coliMutationAntitoxinsBacterial ProteinsDNA Gyraseactive-sitefitnessgene regulationprotein structure predictionresidue burial

Identifiers

PMID35762712
PMCPMC9202547
OpenAlexW4282981982

What Socratic holds

Textmetadata
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 Socratic graph.