论文标题
量子化学计算的反应曲线[3 + 2]环加成反应
Reaction profiles for quantum chemistry-computed [3 + 2] cycloaddition reactions
论文作者
论文摘要
基于[3 + 2]偶极环加成的生物正交点击化学对生物化学领域产生了深远的影响，并且已经致力于为此目的确定有希望的新候选反应。为了衡量前瞻性反应是否可以是合适的生物正交点击反应，有关靶向和反应能量的信息都非常有价值。在这里，我们使用基于AUTODE程序的自动化工作流程来计算涉及合成偶极酚和一组生物学启发的结构基序的[3 + 2]环加成的5000多个反应曲线。基于简洁的基准测试研究，B3LYP-D3（BJ）/DEF2-TZVP // B3LYP-D3（BJ）/DEF2-SVP理论选择了DFT计算，并且对模拟物理条件施加了标准条件和（水性）SMD模型。我们认为，这些数据以及用于高通量反应概况计算的提出的工作流程将有助于筛选新的生物正交反应，以及开发新型的机器学习模型，以更广泛地预测化学反应性。
Bio-orthogonal click chemistry based on [3 + 2] dipolar cycloadditions has had a profound impact on the field of biochemistry and significant effort has been devoted to identify promising new candidate reactions for this purpose. To gauge whether a prospective reaction could be a suitable bio-orthogonal click reaction, information about both on- and off-target activation and reaction energies is highly valuable. Here, we use an automated workflow, based on the autodE program, to compute over 5000 reaction profiles for [3 + 2] cycloadditions involving both synthetic dipolarophiles and a set of biologically-inspired structural motifs. Based on a succinct benchmarking study, the B3LYP-D3(BJ)/def2-TZVP//B3LYP-D3(BJ)/def2-SVP level of theory was selected for the DFT calculations, and standard conditions and an (aqueous) SMD model were imposed to mimic physiological conditions. We believe that this data, as well as the presented workflow for high-throughput reaction profile computation, will be useful to screen for new bio-orthogonal reactions, as well as for the development of novel machine learning models for the prediction of chemical reactivity more broadly.
