Understanding chemical reactivity through the use of state-of-the-art computational techniques enables chemists to both predict reactivity and rationally design novel reactions. This protocol aims to provide chemists with the tools to implement a powerful and robust method for analyzing and understanding any chemical reaction using PyFrag 2019. The approach is based on the so-called activation strain model (ASM) of reactivity, which relates the relative energy of a molecular system to the sum of the energies required to distort the reactants into the geometries required to react plus the strength of their mutual interactions. Other available methods analyze only a stationary point on the potential energy surface, but our methodology analyzes the change in energy along a reaction coordinate. The use of this methodology has been proven to be critical to the understanding of reactions, spanning the realms of the inorganic and organic, as well as the supramolecular and biochemical, fields. This protocol provides step-by-step instructions—starting from the optimization of the stationary points and extending through calculation of the potential energy surface and analysis of the trend-decisive energy terms—that can serve as a guide for carrying out the analysis of any given reaction of interest within hours to days, depending on the size of the molecular system.

通过使用最先进的计算技术了解化学反应性，使化学家能够预测反应性并合理设计新反应。该协议旨在为化学家提供工具，以使用 PyFrag 2019 实施强大而稳健的方法来分析和理解任何化学反应。该方法基于所谓的反应性活化应变模型 (ASM)，该模型与相对能量相关分子系统的能量之和是将反应物扭曲成反应所需的几何形状所需的能量之和加上它们相互相互作用的强度。其他可用的方法仅分析势能表面上的固定点，但我们的方法分析了沿反应坐标的能量变化。事实证明，这种方法的使用对于理解反应至关重要，跨越无机和有机领域，以及超分子和生化领域。该协议提供了分步说明——从优化固定点开始，延伸到计算势能面和分析趋势决定性能量项——可以作为对任何数据进行分析的指南根据分子系统的大小，在几小时到几天内给出感兴趣的反应。