Evidence map›Paper›PMID 35211467›Full record

ArticleFrontiers in bioengineering and biotechnology2022

Combinatorial Approaches for Efficient Design of Photoswitchable Protein-Protein Interactions as

Xiao Zhang, Yuxin Pan, Shoukai Kang, Liangcai Gu

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Xiao ZhangDepartment of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, United States.
Yuxin PanDepartment of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, United States.
Shoukai KangDepartment of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, United States.
Liangcai GuDepartment of Biochemistry and Institute for Protein Design, University of Washington, Seattle, WA, United States.

Funding

De Novo Engineering of Small Molecule-Actuatable Biosensors for Cell TherapyR35GM128918 · NIGMS · UNIVERSITY OF WASHINGTON · PI GU, LIANGCAI · 2018 to 2022
$2.1M
Genetically Encoded Fluorescent Biosensors for Single-Cell and Subcellular Opioid PharmacokineticsR21DA051194 · NIDA · UNIVERSITY OF WASHINGTON · PI GU, LIANGCAI · 2020 to 2021
$428k
Genetically Encoded Optical Biosensors for Dissecting Brain Distribution and Metabolism of CannabinoidsR21DA051555 · NIDA · UNIVERSITY OF WASHINGTON · PI GU, LIANGCAI · 2021 to 2022
$428k
NIDA NIH HHS R21 DA051194NIDA NIH HHS R21 DA051555NIGMS NIH HHS R35 GM128918
6 · The paper itself

Abstract

Light switchable two-component protein dimerization systems offer versatile manipulation and dissection of cellular events in living systems. Over the past 20 years, the field has been driven by the discovery of photoreceptor-based interaction systems, the engineering of light-actuatable binder proteins, and the development of photoactivatable compounds as dimerization inducers. This perspective is to categorize mechanisms and design approaches of these dimerization systems, compare their advantages and limitations, and bridge them to emerging applications. Our goal is to identify new opportunities in combinatorial protein design that can address current engineering challenges and expand

Indexed as

actuatorchemically induced dimerizationcombinatorial protein librarylight induced dimerizationnanobodyopto-binderoptogeneticsphotoreceptor

Identifiers

PMID35211467
PMCPMC8863173

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.