We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTB model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol^–1.

中文翻译：

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使用力匹配的半经验模型生成化学反应的聚合精确自由能面

我们展示了通过与短时间尺度的量子自由能估计值进行力匹配，为益生元混合物中的化学反应创建鲁棒的密度泛函紧密结合（DFTB）模型的能力。使用密度泛函理论（DFT）的分子动力学是产生用于化学反应的自由能表面的高度精确的方法，但是极高的计算成本通常限制了可以进行研究的时间尺度和热力学状态范围。相比之下，DFTB是一种半经验量子方法，可以将成本降低多达千倍，并且可以恢复DFT级的准确性。在这里，我们显示了甘氨酸缩合反应的力匹配DFTB模型产生的自由能表面与反应能学的实验观察结果一致。收敛性分析表明，需要多个纳秒的组合轨迹才能实现甘氨酸缩合的稳定波动的自由能估计。通过与DFT的直接比较证明了力匹配DFTB的预测精度，这两种方法所产生的表面具有大的区域，相差仅几kcal mol。^–1。