Evidence map›Paper›PMID 40571939›Full record

ArticleJournal of computational chemistry2025

Evaluation of Physics-Based Protein Design Methods for Predicting Single Residue Effects on Peptide Binding Specificities.

Merve Ayyildiz, Jakob Noske, Florian J Gisdon, Josef P Kynast, Birte Höcker

Abstract read
In one paragraph

Article in Journal of computational chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Merve AyyildizDepartment of Biochemistry, University of Bayreuth, Bayreuth, Germany.
Jakob NoskeDepartment of Biochemistry, University of Bayreuth, Bayreuth, Germany.
Florian J GisdonDepartment of Biochemistry, University of Bayreuth, Bayreuth, Germany.
Josef P KynastDepartment of Biochemistry, University of Bayreuth, Bayreuth, Germany.ORCID https://orcid.org/0000-0003-1412-1797
Birte HöckerDepartment of Biochemistry, University of Bayreuth, Bayreuth, Germany.ORCID https://orcid.org/0000-0002-8250-9462

Funding

H2020 European Research Council 764434H2020 European Research Council H2020-FETopen-RIA grant 764434 'PRe-ART'HORIZON EUROPE European Innovation Council 101058027HORIZON EUROPE European Innovation Council EIC Transition grant 101058027 'PRe-ART-2T'
6 · The paper itself

Abstract

Understanding the interactions that make up protein-protein or protein-peptide interfaces is a crucial step towards applications in biotechnology. The mutation of a single residue can have a strong impact on binding affinity and specificity, which is difficult to capture in sampling and scoring. Many established computational methods provide an estimate of binding or non-binding; however, comparing highly similar ligands is an important and significantly more challenging problem. Here we evaluated the capability of predicting ligand binding specificity using three established but conceptually different physics-based methods for protein design. As a model system, we analyzed the binding of peptides to designed armadillo repeat proteins, where a single residue of the peptide was changed systematically, leading to affinity changes in the range of 1-1000 nM. We critically assessed the prediction accuracy of the computational methods. While a good correlation with experimentally determined data was observed in several cases, specific biases in the prediction performance of each method were identified.

Indexed as

Armadillo Domain ProteinsPeptidesBinding SitesLigandsProtein BindingArmadillo Domain ProteinsLigandsPeptidesarmadillo repeat proteinBBK*binding affinity calculationbinding pocket designflex ddGPocketOptimizerprotein–peptide interactions

Identifiers

PMID40571939
PMCPMC12202725

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.