Evidence map›Paper›PMID 37574787›Full record

ArticleProtein science : a publication of the Protein Society2023

Engineering gain-of-function mutants of a WW domain by dynamics and structural analysis.

Jin Lu, Mohammad Imtiazur Rahman, I Can Kazan, Nicholas R Halloran, Andrey A Bobkov, S Banu Ozkan, Giovanna Ghirlanda

Open access · bronzeAbstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. A protein dynamics-based deep learning model enhances predictions of fitness and epistasis.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Engineering gain-of-function mutants of a WW domain by dynamics and structural analysis.Protein science : a publication of the Protein Society · 2023
    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

7 authors at 2 institutions in 1 country.

Jin LuDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, USA.
Mohammad Imtiazur RahmanSchool of Molecular Sciences, Arizona State University, Tempe, Arizona, USA.ORCID 0000-0002-8682-7919
I Can KazanDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, USA.ORCID 0000-0003-2593-4179
Nicholas R HalloranSchool of Molecular Sciences, Arizona State University, Tempe, Arizona, USA.
Andrey A BobkovConrad Prebys Center for Chemical Genomics, Sanford Burnham Prebys Medical Discovery Institute, California, USA.
S Banu OzkanDepartment of Physics and Center for Biological Physics, Arizona State University, Tempe, Arizona, USA.
Giovanna GhirlandaSchool of Molecular Sciences, Arizona State University, Tempe, Arizona, USA.ORCID 0000-0001-5470-1484
Arizona State University · USSanford Burnham Prebys Medical Discovery Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proteins gain optimal fitness such as foldability and function through evolutionary selection. However, classical studies have found that evolutionarily designed protein sequences alone cannot guarantee foldability, or at least not without considering local contacts associated with the initial folding steps. We previously showed that foldability and function can be restored by removing frustration in the folding energy landscape of a model WW domain protein, CC16, which was designed based on Statistical Coupling Analysis (SCA). Substitutions ensuring the formation of five local contacts identified as "on-path" were selected using the closest homolog native folded sequence, N21. Surprisingly, the resulting sequence, CC16-N21, bound to Group I peptides, while N21 did not. Here, we identified single-point mutations that enable N21 to bind a Group I peptide ligand through structure and dynamic-based computational design. Comparison of the docked position of the CC16-N21/ligand complex with the N21 structure showed that residues at positions 9 and 19 are important for peptide binding, whereas the dynamic profiles identified position 10 as allosterically coupled to the binding site and exhibiting different dynamics between N21 and CC16-N21. We found that swapping these positions in N21 with matched residues from CC16-N21 recovers nature-like binding affinity to N21. This study validates the use of dynamic profiles as guiding principles for affecting the binding affinity of small proteins.

Indexed as

Gain of Function MutationProteinsAmino Acid SequenceLigandsPeptidesProtein FoldingWW DomainsLigandsPeptidesProteinsbinding affinityCC16CC16-N21energy landscapeGroup I peptideN21SCAstructure and dynamic-based designWW domain

Identifiers

PMID37574787
PMCPMC10464296
OpenAlexW4385798945

What OpenQuestion 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 OpenQuestion graph.