Evidence map›Paper›PMID 21592348›Full record

ArticleBMC bioinformatics2011

Objective identification of residue ranges for the superposition of protein structures.

Donata K Kirchner, Peter Güntert

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Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

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39citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

39 citing papers in PubMed.

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  7. Blind assessment of monomeric AlphaFold2 protein structure models with experimental NMR data.Journal of magnetic resonance (San Diego, Calif. : 1997) · 2023
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  19. Validation of Structures in the Protein Data Bank.Structure (London, England : 1993) · 2017
    Article
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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Donata K KirchnerInstitute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, and Frankfurt Institute for Advanced Studies, Goethe University Frankfurt am Main, Max-von-Laue-Str, 9, 60438 Frankfurt am Main, Germany.
Peter Güntert

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe automation of objectively selecting amino acid residue ranges for structure superpositions is important for meaningful and consistent protein structure analyses. So far there is no widely-used standard for choosing these residue ranges for experimentally determined protein structures, where the manual selection of residue ranges or the use of suboptimal criteria remain commonplace.

resultsWe present an automated and objective method for finding amino acid residue ranges for the superposition and analysis of protein structures, in particular for structure bundles resulting from NMR structure calculations. The method is implemented in an algorithm, CYRANGE, that yields, without protein-specific parameter adjustment, appropriate residue ranges in most commonly occurring situations, including low-precision structure bundles, multi-domain proteins, symmetric multimers, and protein complexes. Residue ranges are chosen to comprise as many residues of a protein domain that increasing their number would lead to a steep rise in the RMSD value. Residue ranges are determined by first clustering residues into domains based on the distance variance matrix, and then refining for each domain the initial choice of residues by excluding residues one by one until the relative decrease of the RMSD value becomes insignificant. A penalty for the opening of gaps favours contiguous residue ranges in order to obtain a result that is as simple as possible, but not simpler. Results are given for a set of 37 proteins and compared with those of commonly used protein structure validation packages. We also provide residue ranges for 6351 NMR structures in the Protein Data Bank.

conclusionsThe CYRANGE method is capable of automatically determining residue ranges for the superposition of protein structure bundles for a large variety of protein structures. The method correctly identifies ordered regions. Global structure superpositions based on the CYRANGE residue ranges allow a clear presentation of the structure, and unnecessary small gaps within the selected ranges are absent. In the majority of cases, the residue ranges from CYRANGE contain fewer gaps and cover considerably larger parts of the sequence than those from other methods without significantly increasing the RMSD values. CYRANGE thus provides an objective and automatic method for standardizing the choice of residue ranges for the superposition of protein structures.

Indexed as

AlgorithmsStructural Homology, ProteinAnimalsDatabases, ProteinHumansModels, MolecularNuclear Magnetic Resonance, BiomolecularProteinsProtein Structure, TertiaryProteins

Identifiers

PMID21592348
PMCPMC3120703

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LicenceCC BY
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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.