Evidence map›Paper›PMID 40835842›Full record

ArticleScientific data2025

A Paired Database of Predicted and Experimental Protein Peptide Binding Information.

Jazmine A Torres, Chris A Kieslich, Robert J Pantazes

Abstract readDataset
In one paragraph

Article in Scientific data, 2025. 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

3 authors.

Jazmine A TorresDepartment of Chemical Engineering, Auburn University, Auburn, AL, 36849-5127, USA.ORCID 0000-0001-8600-9409
Chris A KieslichDepartment of Chemical Engineering, Auburn University, Auburn, AL, 36849-5127, USA.
Robert J PantazesDepartment of Chemical Engineering, Auburn University, Auburn, AL, 36849-5127, USA. rjp0029@auburn.edu.ORCID 0000-0002-0994-007X

Funding

Development of computational tools for accounting for host variability in predicting T-cell epitopesR35GM147164 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI Chris A. Kieslich · 2022 to 2026
$1.9M
The Development and Experimental Verification of Computational Methods to Design and Predict the Properties of Therapeutic ProteinsR35GM138220 · NIGMS · AUBURN UNIVERSITY AT AUBURN · PI PANTAZES, ROBERT J · 2020 to 2024
$1.7M
National Science Foundation (NSF) 2119237NIGMS NIH HHS R35 GM138220NIGMS NIH HHS R35 GM147164U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R35GM138220U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) R35GM147164
6 · The paper itself

Abstract

Peptides are important biomolecules, and their interactions with proteins make them useful in sensing and therapeutic applications. Computational peptide design methods can benefit from high-quality peptide-protein structures paired with thermodynamic data. The Predicted and Experimental Peptide Binding Information (PEPBI) database provides 329 predicted peptide-protein complexes, each based on an experimentally determined structure, with corresponding experimental measurements of changes in Gibbs free energy, enthalpy, and entropy. For each complex, 40 properties calculated using Rosetta's Interface Analyzer are included. Complexes were selected for inclusion in PEPBI using eight stringent structural criteria, including peptide length (5-20 residues), structure resolution (≤2.0 Å), less than 30% sequence identity between complexes, and having a corresponding unbound protein structure in the Protein Data Bank with at least 90% sequence identity to the bound form with minimal changes in the binding pocket. PEPBI is expected to be of use for the development of computational methods for peptide design with desired binding properties to protein targets.

Indexed as

Databases, ProteinPeptidesProteinsProtein BindingProtein ConformationThermodynamicsPeptidesProteins

Identifiers

PMID40835842
PMCPMC12368006

What OpenQuestion holds

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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.