ConfID: an analytical method for conformational characterization of small molecules using molecular dynamics trajectories.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
01 06 2020
Historique:
received: 16 07 2019
revised: 08 11 2019
accepted: 24 02 2020
pubmed: 28 2 2020
medline: 30 10 2020
entrez: 28 2 2020
Statut: ppublish

Résumé

The conformational space of small molecules can be vast and difficult to assess. Molecular dynamics (MD) simulations of free ligands in solution have been applied to predict conformational populations, but their characterization is often based on clustering algorithms or manual efforts. Here, we introduce ConfID, an analytical tool for conformational characterization of small molecules using MD trajectories. The evolution of conformational sampling and population frequencies throughout trajectories is calculated to check for sampling convergence while allowing to map relevant conformational transitions. The tool is designed to track conformational transition events and calculate time-dependent properties for each conformational population detected. Toolkit and documentation are freely available at http://sbcb.inf.ufrgs.br/confid. marcelo.poleto@ufv.br or bigrisci@inf.ufrgs.br. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 32105299
pii: 5762609
doi: 10.1093/bioinformatics/btaa130
doi:

Substances chimiques

Ligands 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3576-3577

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Auteurs

Marcelo D Polêto (MD)

Centro de Biotecnologia, Universidade Federal do Rio Grande do Sul, Porto Alegre 91509-900.
Departamento de Biologia Geral, Universidade Federal de Viçosa, Viçosa 36570-000.

Bruno I Grisci (BI)

Instituto de Informática, Universidade Federal do Rio Grande do Sul, Porto Alegre 91509-900, Brazil.

Marcio Dorn (M)

Instituto de Informática, Universidade Federal do Rio Grande do Sul, Porto Alegre 91509-900, Brazil.

Hugo Verli (H)

Centro de Biotecnologia, Universidade Federal do Rio Grande do Sul, Porto Alegre 91509-900.

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Classifications MeSH