Evidence map›Paper›PMID 29214605›Full record

ReviewBiophysical reviews2018

Creation of artificial protein-protein interactions using α-helices as interfaces.

Sota Yagi, Satoshi Akanuma, Akihiko Yamagishi

Abstract readReview
In one paragraph

Review in Biophysical reviews, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. 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

3 authors.

Sota YagiDepartment of Applied Life Sciences, Tokyo University of Pharmacy and Life Sciences, 1432-1 Horinouchi, Hachioji, Tokyo, 192-0392, Japan.
Satoshi AkanumaFaculty of Human Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama, 359-1192, Japan.
Akihiko YamagishiDepartment of Applied Life Sciences, Tokyo University of Pharmacy and Life Sciences, 1432-1 Horinouchi, Hachioji, Tokyo, 192-0392, Japan. yamagish@toyaku.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Designing novel protein-protein interactions (PPIs) with high affinity is a challenging task. Directed evolution, a combination of randomization of the gene for the protein of interest and selection using a display technique, is one of the most powerful tools for producing a protein binder. However, the selected proteins often bind to the target protein at an undesired surface. More problematically, some selected proteins bind to their targets even though they are unfolded. Current state-of-the-art computational design methods have successfully created novel protein binders. These computational methods have optimized the non-covalent interactions at interfaces and thus produced artificial protein complexes. However, to date there are only a limited number of successful examples of computationally designed de novo PPIs. De novo design of coiled-coil proteins has been extensively performed and, therefore, a large amount of knowledge of the sequence-structure relationship of coiled-coil proteins has been accumulated. Taking advantage of this knowledge, de novo design of inter-helical interactions has been used to produce artificial PPIs. Here, we review recent progress in the in silico design and rational design of de novo PPIs and the use of α-helices as interfaces.

Indexed as

Computational designDe novo interactionsInterfaceNovel protein bindingProtein–protein interactions

Identifiers

PMID29214605
PMCPMC5899712

What OpenQuestion holds

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Registered trials

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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.