Quantum bioelectrochemical (QBIOL) software based on point stochastic processes

Bioelectrochemistry is crucial for understanding biological functions and driving applications in synthetic biology, healthcare, and catalysis. However, current simulation methods fail to capture both the stochastic nature of molecular motion and electron transfer across the relevant picosecond-to-minute timescales. We present QBIOL, a web-accessible software that integrates molecular dynamics, applied mathematics, GPU programming, and quantum charge transport to address this challenge. QBIOL enables quantitative stochastic electron transfer simulations and has the potential to reproduce numerically any (bio) electrochemical experiments. We illustrate this potential by comparing our simulations with experimental data on the current generated by electrode-attached redox-labeled DNA, or by nanoconfined redox species, in response to a variety of electrical excitation waveforms, configurations of interest in biosensing and catalysis. The adaptable architecture of QBIOL extends to the development of devices for quantum and molecular technologies, positioning our software as a powerful tool for enabling new research in this rapidly evolving field.

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Publication Details

Journal
Communications Chemistry
Published
2025-07-19
DOI
https://doi.org/10.1038/s42004-025-01603-1
Citations
1
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
0.81

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Quantum bioelectrochemical (QBIOL) software based on point stochastic processes

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Quantum bioelectrochemical (QBIOL) software based on point stochastic processes

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article en
1 citations

Abstract

Bioelectrochemistry is crucial for understanding biological functions and driving applications in synthetic biology, healthcare, and catalysis. However, current simulation methods fail to capture both the stochastic nature of molecular motion and electron transfer across the relevant picosecond-to-minute timescales. We present QBIOL, a web-accessible software that integrates molecular dynamics, applied mathematics, GPU programming, and quantum charge transport to address this challenge. QBIOL enables quantitative stochastic electron transfer simulations and has the potential to reproduce numerically any (bio) electrochemical experiments. We illustrate this potential by comparing our simulations with experimental data on the current generated by electrode-attached redox-labeled DNA, or by nanoconfined redox species, in response to a variety of electrical excitation waveforms, configurations of interest in biosensing and catalysis. The adaptable architecture of QBIOL extends to the development of devices for quantum and molecular technologies, positioning our software as a powerful tool for enabling new research in this rapidly evolving field.

Communications ChemistryVol. 8(1)
Centre National de la Recherche Scientifique (FR), Université Fédérale de Toulouse Midi-Pyrénées (FR), Laboratoire d'Analyse et d'Architecture des Systèmes (FR), Université Paris Cité (FR), Hokkaido University (JP), Sorbonne Paris Cité (FR), Tokyo Medical Center (JP), NTT Basic Research Laboratories (JP), Interfaces Traitements Organisation et Dynamique des Systèmes (FR), Meguro Parasitological Museum (JP)
Agence Nationale de la Recherche, Centre National de la Recherche Scientifique
Openalex Percentile: Top 26%
Advanced biosensing and bioanalysis techniques
0.81
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