Evidence map›Paper›PMID 36798377›Full record

ArticlebioRxiv : the preprint server for biology2023

Massively parallel protein-protein interaction measurement by sequencing (MP3-seq) enables rapid screening of protein heterodimers.

Alexander Baryshev, Alyssa La Fleur, Benjamin Groves, Cirstyn Michel, David Baker, Ajasja Ljubetič, Georg Seelig

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Alexander BaryshevDepartment of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA.
Alyssa La FleurPaul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA 98195, USA.
Benjamin GrovesDepartment of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA.
Cirstyn MichelDepartment of Bioengineering, University of Washington, Seattle, WA 98195, USA.
David BakerDepartment of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Ajasja LjubetičDepartment of Biochemistry, University of Washington, Seattle, WA 98195, USA.
Georg SeeligDepartment of Electrical & Computer Engineering, University of Washington, Seattle, WA 98195, USA.
University of Washington · USHoward Hughes Medical Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein-protein interactions (PPIs) regulate many cellular processes, and engineered PPIs have cell and gene therapy applications. Here we introduce massively parallel protein-protein interaction measurement by sequencing (MP3-seq), an easy-to-use and highly scalable yeast-two-hybrid approach for measuring PPIs. In MP3-seq, DNA barcodes are associated with specific protein pairs, and barcode enrichment can be read by sequencing to provide a direct measure of interaction strength. We show that MP3-seq is highly quantitative and scales to over 100,000 interactions. We apply MP3-seq to characterize interactions between families of rationally designed heterodimers and to investigate elements conferring specificity to coiled-coil interactions. Finally, we predict coiled heterodimer structures using AlphaFold-Multimer (AF-M) and train linear models on physics simulation energy terms to predict MP3-seq values. We find that AF-M and AF-M complex prediction-based models could be valuable for pre-screening interactions, but that measuring interactions experimentally remains necessary to rank their strengths quantitatively.

Identifiers

PMID36798377
PMCPMC9934699
OpenAlexW4319724539

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.