Characterizing molecular flexibility by combining least root mean square deviation measures.


Journal

Proteins
ISSN: 1097-0134
Titre abrégé: Proteins
Pays: United States
ID NLM: 8700181

Informations de publication

Date de publication:
05 2019
Historique:
received: 22 08 2018
revised: 20 12 2018
accepted: 09 01 2019
pubmed: 22 1 2019
medline: 21 4 2020
entrez: 22 1 2019
Statut: ppublish

Résumé

The root mean square deviation (RMSD) and the least RMSD are two widely used similarity measures in structural bioinformatics. Yet, they stem from global comparisons, possibly obliterating locally conserved motifs. We correct these limitations with the so-called combined RMSD, which mixes independent lRMSD measures, each computed with its own rigid motion. The combined RMSD is relevant in two main scenarios, namely to compare (quaternary) structures based on motifs defined from the sequence (domains and SSE) and to compare structures based on structural motifs yielded by local structural alignment methods. We illustrate the benefits of combined RMSD over the usual RMSD on three problems, namely (a) the assignment of quaternary structures for hemoglobin (scenario #1), (b) the calculation of structural phylogenies (case study: class II fusion proteins; scenario #1), and (c) the analysis of conformational changes based on combined RMSD of rigid structural motifs (case study: one class II fusion protein; scenario #2). Based on these illustrations, we argue that the combined RMSD is a tool of choice to perform positive and negative discrimination of degree of freedom, with applications to the design of move sets and collective coordinates. Executables to compute combined RMSD are available within the Structural Bioinformatics Library (http://sbl.inria.fr).

Identifiants

pubmed: 30663799
doi: 10.1002/prot.25658
doi:

Substances chimiques

Proteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

380-389

Informations de copyright

© 2019 Wiley Periodicals, Inc.

Auteurs

Frédéric Cazals (F)

Inria (Algorithms-Biology-Structure), Université Côte d'Azur, Sophia Antipolis, France.

Romain Tetley (R)

Inria (Algorithms-Biology-Structure), Université Côte d'Azur, Sophia Antipolis, France.

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Classifications MeSH