Grall Simon, Madrid Ignacio, Dufour Aramis, Sands Helen, Kato Masaki, Fujiwara Akira, Kim Soo Hyeon, Chovin Arnaud, Demaille Christophe, Clément Nicolas
LAAS, CNRS, Toulouse, France.
LIMMS, CNRS, Meguro-ku, Tokyo, Japan.
Commun Chem. 2025 Jul 19;8(1):210. doi: 10.1038/s42004-025-01603-1.
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.
生物电化学对于理解生物功能以及推动合成生物学、医疗保健和催化领域的应用至关重要。然而,当前的模拟方法无法捕捉分子运动的随机性以及在从皮秒到分钟的相关时间尺度上的电子转移。我们展示了QBIOL,这是一款可通过网络访问的软件,它整合了分子动力学、应用数学、GPU编程和量子电荷传输来应对这一挑战。QBIOL能够进行定量随机电子转移模拟,并且有潜力通过数值方法重现任何(生物)电化学实验。我们通过将我们的模拟与关于附着在电极上的氧化还原标记DNA或纳米受限氧化还原物种在响应各种电激发波形时产生的电流的实验数据进行比较,来说明这种潜力,这些波形是生物传感和催化中感兴趣的配置。QBIOL的适应性架构扩展到量子和分子技术设备的开发,使我们的软件成为在这个快速发展的领域开展新研究的强大工具。