Evidence map›Paper›PMID 34779043›Full record

ArticleProtein science : a publication of the Protein Society2022

The importance of residue-level filtering and the Top2018 best-parts dataset of high-quality protein residues.

Christopher J Williams, David C Richardson, Jane S Richardson

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Cis-nonProline peptides: Genuine occurrences and their functional roles.Protein science : a publication of the Protein Society · 2025
    Article
  4. PhiSiCal-Checkup: A Bayesian framework to validate amino acid conformations within experimental protein structures.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
  7. Invariant point message passing for protein side chain packing.bioRxiv : the preprint server for biology · 2023
    Article
  8. Review
  9. 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.

Christopher J WilliamsDepartment of Biochemistry, Duke University, Durham, North Carolina, USA.ORCID 0000-0002-5808-8768
David C RichardsonDepartment of Biochemistry, Duke University, Durham, North Carolina, USA.ORCID 0000-0001-5069-343X
Jane S RichardsonDepartment of Biochemistry, Duke University, Durham, North Carolina, 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 GM131883
6 · The paper itself

Abstract

We have curated a high-quality, "best-parts" reference dataset of about 3 million protein residues in about 15,000 PDB-format coordinate files, each containing only residues with good electron density support for a physically acceptable model conformation. The resulting prefiltered data typically contain the entire core of each chain, in quite long continuous fragments. Each reference file is a single protein chain, and the total set of files were selected for low redundancy, high resolution, good MolProbity score, and other chain-level criteria. Then each residue was critically tested for adequate local map quality to firmly support its conformation, which must also be free of serious clashes or covalent-geometry outliers. The resulting Top2018 prefiltered datasets have been released on the Zenodo online web service and are freely available for all uses under a Creative Commons license. Currently, one dataset is residue filtered on main chain plus Cβ atoms, and a second dataset is full-residue filtered; each is available at four different sequence-identity levels. Here, we illustrate both statistics and examples that show the beneficial consequences of residue-level filtering. That process is necessary because even the best of structures contain a few highly disordered local regions with poor density and low-confidence conformations that should not be included in reference data. Therefore, the open distribution of these very large, prefiltered reference datasets constitutes a notable advance for structural bioinformatics and the fields that depend upon it.

Indexed as

AlgorithmsComputational BiologyDatabases, ProteinModels, MolecularSoftwareCrystallography, X-RayProtein ConformationProteinsProteinsprotein libraryreference datastructural bioinformaticsstructure validationZenodo

Identifiers

PMID34779043
PMCPMC8740842

What Socratic 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 Socratic graph.