Development of a novel computational technique to create DNA and cell geometrical models for Geant4-DNA.

DNA damage response DNA geometries Geant4-DNA Monte Carlo simulations

Journal

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
ISSN: 1724-191X
Titre abrégé: Phys Med
Pays: Italy
ID NLM: 9302888

Informations de publication

Date de publication:
25 Oct 2024
Historique:
received: 26 06 2024
revised: 12 09 2024
accepted: 21 10 2024
medline: 27 10 2024
pubmed: 27 10 2024
entrez: 26 10 2024
Statut: aheadofprint

Résumé

This study aimed to develop a novel human cell geometry for the Geant4-DNA simulation toolkit that explicitly incorporates all 23 chromosome pairs of the human cell. This approach contrasts with the existing, default human cell, geometrical model, which utilizes a continuous Hilbert curve. A Python-based tool named "complexDNA" was developed to facilitate the design of both simple and complex DNA geometries. This tool was employed to construct a human cell geometry with individual pairs of chromosomes. Subsequently, the performance of this chromosomal model was compared to the standard human cell model provided in the "molecularDNA" Geant4-DNA example. Simulations using the new chromosomal model revealed minimal discrepancies in DNA damage yield and fragment size distribution compared to the default human cell model. Notably, the chromosomal model demonstrated significant computational efficiency, requiring approximately three times less simulation time to achieve equivalent results. This work highlights the importance of incorporating chromosomal structure into human cell models for radiation biology research. The "complexDNA" tool offers a valuable resource for creating intricate DNA structures for future studies. Further refinements, such as implementing smaller voxels for euchromatin regions, are proposed to enhance the model's accuracy.

Sections du résumé

BACKGROUND BACKGROUND
This study aimed to develop a novel human cell geometry for the Geant4-DNA simulation toolkit that explicitly incorporates all 23 chromosome pairs of the human cell. This approach contrasts with the existing, default human cell, geometrical model, which utilizes a continuous Hilbert curve.
METHODS METHODS
A Python-based tool named "complexDNA" was developed to facilitate the design of both simple and complex DNA geometries. This tool was employed to construct a human cell geometry with individual pairs of chromosomes. Subsequently, the performance of this chromosomal model was compared to the standard human cell model provided in the "molecularDNA" Geant4-DNA example.
RESULTS RESULTS
Simulations using the new chromosomal model revealed minimal discrepancies in DNA damage yield and fragment size distribution compared to the default human cell model. Notably, the chromosomal model demonstrated significant computational efficiency, requiring approximately three times less simulation time to achieve equivalent results.
CONCLUSIONS CONCLUSIONS
This work highlights the importance of incorporating chromosomal structure into human cell models for radiation biology research. The "complexDNA" tool offers a valuable resource for creating intricate DNA structures for future studies. Further refinements, such as implementing smaller voxels for euchromatin regions, are proposed to enhance the model's accuracy.

Identifiants

pubmed: 39461070
pii: S1120-1797(24)01096-2
doi: 10.1016/j.ejmp.2024.104839
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104839

Informations de copyright

Copyright © 2024 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Konstantinos P Chatzipapas (KP)

University of Brest, INSERM, LaTIM, UMR 1101, F-29200 Brest, France. Electronic address: konstantinos.chatzipapas@univ-brest.fr.

Hoang Ngoc Tran (HN)

University of Bordeaux, CNRS, LP2i Bordeaux, UMR 5797, F-33170 Gradignan, France.

Milos Dordevic (M)

Vinca Institute of Nuclear Sciences - National Institute of the Republic of Serbia, University of Belgrade, Belgrade, Serbia.

Dousatsu Sakata (D)

Division of Health Science, Osaka University, Osaka, Japan.

Sebastien Incerti (S)

University of Bordeaux, CNRS, LP2i Bordeaux, UMR 5797, F-33170 Gradignan, France.

Dimitris Visvikis (D)

University of Brest, INSERM, LaTIM, UMR 1101, F-29200 Brest, France.

Julien Bert (J)

University of Brest, INSERM, LaTIM, UMR 1101, F-29200 Brest, France.

Classifications MeSH