Chanalyzer: A Computational Geometry Approach for the Analysis of Protein Channel Shape and Dynamics.
alpha shapes theory
channel and pore characterization
computational geometry
ion channels
molecular dynamics
molecular surface
skeletonization
Journal
Frontiers in molecular biosciences
ISSN: 2296-889X
Titre abrégé: Front Mol Biosci
Pays: Switzerland
ID NLM: 101653173
Informations de publication
Date de publication:
2022
2022
Historique:
received:
01
05
2022
accepted:
13
06
2022
entrez:
12
8
2022
pubmed:
13
8
2022
medline:
13
8
2022
Statut:
epublish
Résumé
Morphological analysis of protein channels is a key step for a thorough understanding of their biological function and mechanism. In this respect, molecular dynamics (MD) is a very powerful tool, enabling the description of relevant biological events at the atomic level, which might elude experimental observations, and pointing to the molecular determinants thereof. In this work, we present a computational geometry-based approach for the characterization of the shape and dynamics of biological ion channels or pores to be used in combination with MD trajectories. This technique relies on the earliest works of Edelsbrunner and on the NanoShaper software, which makes use of the alpha shape theory to build the solvent-excluded surface of a molecular system in an aqueous solution. In this framework, a channel can be simply defined as a cavity with two entrances on the opposite sides of a molecule. Morphological characterization, which includes identification of the main axis, the corresponding local radius, and the detailed description of the global shape of the cavity, is integrated with a physico-chemical description of the surface facing the pore lumen. Remarkably, the possible existence or temporary appearance of fenestrations from the channel interior towards the outer lipid matrix is also accounted for. As a test case, we applied the present approach to the analysis of an engineered protein channel, the mechanosensitive channel of large conductance.
Identifiants
pubmed: 35959458
doi: 10.3389/fmolb.2022.933924
pii: 933924
pmc: PMC9358003
doi:
Types de publication
Journal Article
Langues
eng
Pagination
933924Informations de copyright
Copyright © 2022 Raffo, Gagliardi, Fugacci, Sagresti, Grandinetti, Brancato, Biasotti and Rocchia.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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