qDNA 1.0.1

QuantumDNA is an open-source Python package for simulating energy and charge transfer in DNA using quantum mechanical methods.

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Welcome to QuantumDNA

This python package can be cited as:

Herb, D. et al. QuantumDNA: A python package for analyzing quantum charge dynamics in DNA and exploring its biological relevance. Computer Physics Communications 313, 109626 (2025). DOI: 10.1016/j.cpc.2025.109626

Introduction

The study of DNA charge dynamics is a highly interdisciplinary field and plays an important role in processes such as DNA damage detection, protein-DNA interactions, and DNA-based nanotechnology. However, despite significant progress in each of these areas, knowledge often remains inaccessible to researchers in other scientific communities. To bridge this gap, we have developed QuantumDNA: an open-source python package for simulating DNA charge transfer and excited state dynamics using quantum physical methods.

QuantumDNA uses a linear combination of atomic orbitals (LCAO) approach combined with tight-binding models and open quantum systems techniques. This way one can quickly scan large numbers DNA sequences, enabling statistical studies of genetic and epigenetic phenomena.

Whether you're a scientist, student, or just curious, QuantumDNA: dive in and start exploring!

Features

• Coarse-graining approach: linear combination of atomic orbitals (LCAO) and tight-binding models to efficiently simulate DNA charge dynamics.
• Parallelized Calculations: Enabling the analysis of large numbers of DNA seqeunces.
• Integration with publicly accessible databases: Users can input geometries from DNA structure databases as PDB files.
• GUI: Designed for researchers across physics, chemistry, biology, and medicine.

What's new

• Added a graphical user interface (GUI) to the package which is based on the customtkinter package.
• Added a Tutorial Jupyter Notebooks available on another GitHub repopsitory.

Getting started

Quick Installation

For a quick installation, you can install the qDNA package via pip:

pip install qDNA

To ensure compatibility and avoid conflicts with other packages, we recommend using a virtual environment. For detailed installation instructions, please refer to the Installation Guide.

Example Program

To test QuantumDNA, you can run the following simple example where the exciton lifetime and the average charge separation of a double-stranded GCG DNA sequence are calculated. You can try different sequences, tight-binding models, and keyword arguments to investigate how these factors affect the exciton lifetime and average charge separation. For example, you might find that in general more uniform sequences show higher values.

from qDNA import calc_lifetime, calc_dipole

# input
tb_sites = get_tb_sites('GCG')
kwargs = dict(tb_model_name = 'ELM', unit='rad/ps', relax_rate=3, source='Hawke2010')

# calculation
eva = Evaluation(tb_sites, **kwargs)
lifetime = eva.calc_lifetime()
charge_separation = eva.calc_charge_separation()

# output
print(f"Exciton lifetime {lifetime} fs")
print(f"Average charge separation {charge_separation} A")

Documentation

The documentation webpage for the latest release is available for reading on Read The Docs. Tutorials can be found in a separate GitHub repository QuantumDNA-notebooks.

Graphical User Interface

The qDNA package includes a GUI that provides an intuitive and user-friendly way to interact with the package's functionalities. You can access the GUI with the following code:

from qDNA.gui import QDNApp

QDNApp().run()

The GUI allows you to easily explore and utilize the capabilities of the qDNA package. Below are some examples demonstrating its use:

• Usage example: Perform simulations with geometries from publically availbale databases (here: PDB geometry of the 1BNA sequence from RCSB.org).

Simulations with Real Geometries via the GUI

(a) A Protein Data Bank (PDB) file containing the DNA geometry was obtained from RCSB.org (identifier: 1BNA) and modified using Biovia Discovery Studio. The subsequence selected for simulation is highlighted in blue.

(b) The PDB Input Window allows users to upload the modified PDB file, specify an identifier, and select a Tight-Binding (TB) model. Clicking the "Save" button computes TB parameters.

(c) To simulate the highlighted sequence from (a), set the upper strand to 02G_03C_04G and the lower strand to 23C_22G_21C. Ensure the identifier (e.g., 1BNA) is selected as the source. Exciton calculations can be performed using the Evaluation tab, with results displayed in the console at the bottom right (highlighted in green).

(d) The plotting window provides a heatmap visualization of time-evolved populations for the DNA sequence highlighted in (a). All simulation steps can also be performed programmatically without the GUI, such as using Jupyter Notebooks.

• Plot Generation: Plot obtained after pressing the submit button on the menu.

• Calculation Display: Screenshot of the menu of the user interface with calculations of the exciton lifetime, average charge separation and dipole moment displayed in the frame on the bottom right.

Shortcuts

To enhance the readability of the code, we have frequently used the following shortcuts:

• ham: hamiltonian
• dm: density matrix
• tb: tight-binding
• eigv: eigenvalue/ eigenenergy
• eigs: eigenstates/ eigenvectors
• dim: dimension
• fig: figure
• op: operator
• loc: local
• glob: global
• deph: dephasing
• therm: thermalizing
• seq: sequence
• calc: calculate

References

Papers from our group:

• R. Siebert, O. Ammerpohl, M. Rossini et al. A quantum physics layer of epigenetics: a hypothesis deduced from charge transfer and chirality-induced spin selectivity of DNA. Clin Epigenet 15, 145 (2023).
• D. Herb, M. Rossini and J. Ankerhold, Ultrafast excitonic dynamics in DNA: Bridging correlated quantum dynamics and sequence dependence. Physical Review E 109, 064413 (2024).

Tight-binding parameters:

• R. G. Endres, D. L. Cox, and R. R. P. Singh, Colloquium: The quest for high-conductance DNA. Rev. Mod. Phys. 76, 195 (2004)

• H. Mehrez and M. P. Anantram, Interbase electronic coupling for transport through DNA. Phys. Rev. B 71, 115405 (2005)

• L.G.D. Hawke, G. Kalosakas and C. Simserides, Electronic parameters for charge transfer along DNA. The European Physical Journal E 32, 291 (2010)

• C. Simserides, A systematic study of electron or hole transfer along DNA dimers, trimers and polymers. Chemical Physics 440, 31 (2014)

• M. Mantela, C. Simserides and R. Di Felice, LCAO electronic structure of nucleic acid bases and other heterocycles and transfer integrals in B-DNA, including structural variability. Materials 14, 4930 (2021)

Tight-binding models:

• K. Lambropoulos and C. Simserides, Tight-binding modeling of nucleic acid sequences: Interplay between various types of order or disorder and charge transport. Symmetry 11, 968 (2019)

DNA excited states and excitons:

• C. Crespo-Hernandez, B. Cohen and B. Kohler, Base stacking controls excited-state dynamics in A·T DNA. Nature 436, 1141 (2005)

• E.R. Bittner, Lattice theory of ultrafast excitonic and charge-transfer dynamics in DNA. Journal of Chemical Physics 125, 094909 (2006)

• E. R. Bittner, Frenkel exciton model of ultrafast excited state dynamics in AT DNA double helices. Journal of Photochemistry and Photobiology A: Chemistry 190, 328-334 (2007)

• E.M. Conwell, P.M. McLaughlin and S.M. Bloch, Charge-Transfer Excitons in DNA. The Journal of Physical Chemistry B 112, 2268 (2008)

• S. Tornow, R. Bulla, F.B. Anders and G. Zwicknagl, Multiple-charge transfer and trapping in DNA dimers. Physical Review B 82, 195106 (2010)

DNA charge transfer:

• Elizabeth M. Boon and Jacqueline K. Barton, Charge transport in DNA. Current Opinion in Structural Biology 12, 320–329 (2002)

• J.C. Genereux and J.K. Barton, Mechanisms for DNA charge transport. Chemical Reviews 110, 1642 (2010)

• A.R. Arnold, M.A. Grodick and J.K. Barton, DNA Charge Transport: from Chemical Principles to the Cell. Cell Chemical Biology 23, 183 (2016)

Simulation of open quantum systems:

• J.R. Johansson, P.D. Nation and Franco Nori, QuTiP: An open-source Python framework for the dynamics of open quantum systems. Computer Physics Communications 183, 1760 (2012)

• quantum_HEOM (github.com/jwa7/quantum_HEOM), J.W. Abbott, 2022

Support

For support, please contact the author at [e-mail].