Evidence map›Paper›PMID 35578204›Full record

ArticleBMC biology2022

Optimization of the antimicrobial peptide Bac7 by deep mutational scanning.

Philipp Koch, Steven Schmitt, Alexander Heynisch, Anja Gumpinger, Irene Wüthrich, Marina Gysin, Dimitri Shcherbakov, Sven N Hobbie, Sven Panke, Martin Held

Open access · goldAbstract read
In one paragraph

Article in BMC biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

16 citing papers in PubMed, 34 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

10 authors at 2 institutions in 1 country.

Philipp Koch *Bioprocess Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Steven Schmitt *Bioprocess Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Alexander HeynischBioprocess Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Anja GumpingerMachine Learning and Computational Biology, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Irene WüthrichBioprocess Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Marina GysinInstitute of Medical Microbiology, University of Zurich, Zurich, Switzerland.
Dimitri ShcherbakovInstitute of Medical Microbiology, University of Zurich, Zurich, Switzerland.
Sven N HobbieInstitute of Medical Microbiology, University of Zurich, Zurich, Switzerland.
Sven PankeBioprocess Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Martin HeldBioprocess Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland. martin.held@bsse.ethz.ch.ORCID 0000-0002-5952-5659
ETH Zurich · CHUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntracellularly active antimicrobial peptides are promising candidates for the development of antibiotics for human applications. However, drug development using peptides is challenging as, owing to their large size, an enormous sequence space is spanned. We built a high-throughput platform that incorporates rapid investigation of the sequence-activity relationship of peptides and enables rational optimization of their antimicrobial activity. The platform is based on deep mutational scanning of DNA-encoded peptides and employs highly parallelized bacterial self-screening coupled to next-generation sequencing as a readout for their antimicrobial activity. As a target, we used Bac7

resultsUsing the platform, we simultaneously determined the antimicrobial activity of >600,000 Bac7

conclusionWe demonstrated that the presented platform can be used to establish the sequence-activity relationship of antimicrobial peptides, and showed its usefulness for hit-to-lead identification and optimization of antimicrobial drug candidates.

Indexed as

Anti-Infective AgentsEscherichia coliAnimalsAnti-Bacterial AgentsAntimicrobial Cationic PeptidesAntimicrobial PeptidesHumansMiceMicrobial Sensitivity TestsPeptides, CyclicProlineAnti-Bacterial AgentsAnti-Infective AgentsAntimicrobial Cationic PeptidesAntimicrobial PeptidesbactenecinPeptides, CyclicProlineAntibioticsAntimicrobial peptidesAntimicrobial resistanceAntimicrobialsDeep mutational scanningDrug discoveryHigh-throughput screeningProline-rich antimicrobial peptidesProtein synthesis inhibitorSequence-activity relationship

Identifiers

PMID35578204
PMCPMC9112550
OpenAlexW4280615473

What OpenQuestion holds

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LicenceCC BY
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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.