The organic chemist’s toolbox is vast, with technologies to accelerate the synthesis of novel chemical matter. The field of asymmetric catalysis is one approach to accessing new areas of chemical space and computational power is today sufficient to assist in this exploration. Unfortunately, existing techniques generally require computational expertise and are therefore underutilized in synthetic chemistry. Here we present our platform Virtual Chemist, which allows bench chemists to predict outcomes of asymmetric chemical reactions ahead of testing in the laboratory, in just a few clicks. Modular workflows facilitate the simulation of various sets of experiments, including the four realistic scenarios discussed: one-by-one design, library screening, hit optimization and substrate-scope evaluation. Catalyst candidates are screened within hours and the enantioselectivity predictions provide substantial enrichments compared to random testing. The achieved accuracies within ~1 kcal mol^–1 provide opportunities for computational chemistry in the field of asymmetric catalyst design, allowing bench chemists to guide the design and discovery of asymmetric catalysts.

有机化学家的工具箱非常广泛，具有加速新型化学物质合成的技术。不对称催化领域是进入化学空间新领域的一种方法，今天的计算能力足以协助这一探索。不幸的是，现有技术通常需要计算专业知识，因此在合成化学中未得到充分利用。在这里，我们介绍我们的平台虚拟化学家，这使实验室化学家只需单击几下，即可在实验室测试之前预测不对称化学反应的结果。模块化的工作流程促进了各种实验的仿真，包括讨论的四个实际场景：一对一设计，库筛选，命中优化和底物范围评估。数小时之内即可筛选出候选催化剂，与随机测试相比，对映体选择性预测可提供实质性的富集。在不超过1 kcal mol ^–1范围内获得的精度为不对称催化剂设计领域的计算化学提供了机会，从而使化学家可以指导不对称催化剂的设计和发现。