Cargando…

Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations

Molecular dynamics simulations, at different scales, have been exploited for investigating complex mechanisms ruling biologically inspired systems. Nonetheless, with recent advances and unprecedented achievements, the analysis of molecular dynamics simulations requires customized workflows. In 2018,...

Descripción completa

Detalles Bibliográficos
Autores principales: Fontana, Federico, Carlino, Calogero, Malik, Ashish, Gelain, Fabrizio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138828/
https://www.ncbi.nlm.nih.gov/pubmed/37104393
http://dx.doi.org/10.1371/journal.pone.0284307
_version_ 1785032799284101120
author Fontana, Federico
Carlino, Calogero
Malik, Ashish
Gelain, Fabrizio
author_facet Fontana, Federico
Carlino, Calogero
Malik, Ashish
Gelain, Fabrizio
author_sort Fontana, Federico
collection PubMed
description Molecular dynamics simulations, at different scales, have been exploited for investigating complex mechanisms ruling biologically inspired systems. Nonetheless, with recent advances and unprecedented achievements, the analysis of molecular dynamics simulations requires customized workflows. In 2018, we developed Morphoscanner to retrieve structural relations within self-assembling peptide systems. In particular, we conceived Morphoscanner for tracking the emergence of β-structured domains in self-assembling peptide systems. Here, we introduce Morphoscanner2.0. Morphoscanner2.0 is an object-oriented library for structural and temporal analysis of atomistic and coarse-grained molecular dynamics (CG-MD) simulations written in Python. The library leverages MDAnalysis, PyTorch and NetworkX to perform the pattern recognition of secondary structure patterns, and interfaces with Pandas, Numpy and Matplotlib to make the results accessible to the user. We used Morphoscanner2.0 on both simulation trajectories and protein structures. Because of its dependencies on the MDAnalysis package, Morphoscanner2.0 can read several file formats generated by widely-used molecular simulation packages such as NAMD, Gromacs, OpenMM. Morphoscanner2.0 also includes a routine for tracking the alpha-helix domain formation.
format Online
Article
Text
id pubmed-10138828
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-101388282023-04-28 Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations Fontana, Federico Carlino, Calogero Malik, Ashish Gelain, Fabrizio PLoS One Research Article Molecular dynamics simulations, at different scales, have been exploited for investigating complex mechanisms ruling biologically inspired systems. Nonetheless, with recent advances and unprecedented achievements, the analysis of molecular dynamics simulations requires customized workflows. In 2018, we developed Morphoscanner to retrieve structural relations within self-assembling peptide systems. In particular, we conceived Morphoscanner for tracking the emergence of β-structured domains in self-assembling peptide systems. Here, we introduce Morphoscanner2.0. Morphoscanner2.0 is an object-oriented library for structural and temporal analysis of atomistic and coarse-grained molecular dynamics (CG-MD) simulations written in Python. The library leverages MDAnalysis, PyTorch and NetworkX to perform the pattern recognition of secondary structure patterns, and interfaces with Pandas, Numpy and Matplotlib to make the results accessible to the user. We used Morphoscanner2.0 on both simulation trajectories and protein structures. Because of its dependencies on the MDAnalysis package, Morphoscanner2.0 can read several file formats generated by widely-used molecular simulation packages such as NAMD, Gromacs, OpenMM. Morphoscanner2.0 also includes a routine for tracking the alpha-helix domain formation. Public Library of Science 2023-04-27 /pmc/articles/PMC10138828/ /pubmed/37104393 http://dx.doi.org/10.1371/journal.pone.0284307 Text en © 2023 Fontana et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Fontana, Federico
Carlino, Calogero
Malik, Ashish
Gelain, Fabrizio
Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations
title Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations
title_full Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations
title_fullStr Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations
title_full_unstemmed Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations
title_short Morphoscanner2.0: A new python module for analysis of molecular dynamics simulations
title_sort morphoscanner2.0: a new python module for analysis of molecular dynamics simulations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138828/
https://www.ncbi.nlm.nih.gov/pubmed/37104393
http://dx.doi.org/10.1371/journal.pone.0284307
work_keys_str_mv AT fontanafederico morphoscanner20anewpythonmoduleforanalysisofmoleculardynamicssimulations
AT carlinocalogero morphoscanner20anewpythonmoduleforanalysisofmoleculardynamicssimulations
AT malikashish morphoscanner20anewpythonmoduleforanalysisofmoleculardynamicssimulations
AT gelainfabrizio morphoscanner20anewpythonmoduleforanalysisofmoleculardynamicssimulations