Evidence map›Paper›PMID 40937679›Full record

ArticleActa crystallographica. Section D, Structural biology2025

Categorizing prediction modes within low-pLDDT regions of AlphaFold2 structures: near-predictive, pseudostructure and barbed wire.

Christopher J Williams, Vincent B Chen, David C Richardson, Jane S Richardson

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Article in Acta crystallographica. Section D, Structural biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Christopher J WilliamsDepartment of Biochemistry, Duke University School of Medicine, 132 Nanaline Duke Building 3711 DUMC, Durham, NC 27710, USA.ORCID 0000-0002-5808-8768
Vincent B ChenDepartment of Biochemistry, Duke University School of Medicine, 132 Nanaline Duke Building 3711 DUMC, Durham, NC 27710, USA.ORCID 0000-0003-2492-979X
David C RichardsonDepartment of Biochemistry, Duke University School of Medicine, 132 Nanaline Duke Building 3711 DUMC, Durham, NC 27710, USA.
Jane S RichardsonDepartment of Biochemistry, Duke University School of Medicine, 132 Nanaline Duke Building 3711 DUMC, Durham, NC 27710, USA.ORCID 0000-0002-3311-2944

Funding

PROJECT 5 - DUKE - STRUCTURE VALIDATION AND IMPROVEMENT FOR PROTEINS AND N. ACIDSP01GM063210 · NIGMS · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI ADAMS, PAUL DAVID · 2001 to 2021
$33.5M
Extending MolProbity Diagnosis & Healing Methods to Empower Better CryoEM & Xray Models at 2.5-4A Resolution, plus Versioned, Redeposited "GEMS" for Important Individual StructuresR35GM131883 · NIGMS · DUKE UNIVERSITY · PI RICHARDSON, DAVID CLAUDE · 2019 to 2022
$1.7M
NIGMS NIH HHS P01 GM063210NIGMS NIH HHS R35 GM131883NIH HHS P01GM063210NIH HHS R35GM131883
6 · The paper itself

Abstract

AlphaFold2 protein structure predictions are widely available for structural biology uses. These predictions, especially for eukaryotic proteins, frequently contain extensive regions predicted below the pLDDT = 70 level, the rule-of-thumb cutoff for high confidence. This work identifies major modes of behavior within low-pLDDT regions through a survey of human proteome predictions provided by the AlphaFold Protein Structure Database. The near-predictive mode resembles folded protein and can be a nearly accurate prediction. Barbed wire is extremely unprotein-like, being recognized by wide looping coils, an absence of packing contacts and numerous signature validation outliers, and it represents a region where the conformation has no predictive value. Pseudostructure presents an intermediate behavior with a misleading appearance of isolated and badly formed secondary-structure-like elements. These prediction modes are compared with annotations of disorder from MobiDB, showing general correlation between barbed wire/pseudostructure and many measures of disorder, an association between pseudostructure and signal peptides, and an association between near-predictive and regions of conditional folding. To enable users to identify these regions within a prediction, a new Phenix tool is developed encompassing the results of this work, including prediction annotation, visual markup and residue selection based on these prediction modes. This tool will help users develop expertise in interpreting difficult AlphaFold predictions and identify the near-predictive regions that can aid in molecular replacement when a prediction does not contain enough high-pLDDT regions.

Indexed as

Protein FoldingProteinsDatabases, ProteinHumansModels, MolecularProtein ConformationProtein Structure, SecondaryProteinsAlphaFold2barbed wireconditional foldingintrinsically disordered regionslow pLDDTnear-predictivesignal peptidesstructure predictionstructure validation

Identifiers

PMID40937679
PMCPMC12485489

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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.