The efficient exploration of chemical space to design molecules with intended properties enables the accelerated discovery of drugs, materials, and catalysts, and is one of the most important outstanding challenges in chemistry. Encouraged by the recent surge in computer power and artificial intelligence development, many algorithms have been developed to tackle this problem. However, despite the emergence of many new approaches in recent years, comparatively little progress has been made in developing realistic benchmarks that reflect the complexity of molecular design for real-world applications. In this work, we develop a set of practical benchmark tasks relying on physical simulation of molecular systems mimicking real-life molecular design problems for materials, drugs, and chemical reactions. Additionally, we demonstrate the utility and ease of use of our new benchmark set by demonstrating how to compare the performance of several well-established families of algorithms. Overall, we believe that our benchmark suite will help move the field towards more realistic molecular design benchmarks, and move the development of inverse molecular design algorithms closer to the practice of designing molecules that solve existing problems in both academia and industry alike.
翻译:有效探索化学空间以设计具有预期特性的分子,可以加速发现药物、材料和催化剂,这是化学领域最突出的突出挑战之一。由于最近计算机动力和人工智能发展激增,为解决这一问题发展了许多算法。然而,尽管近年来出现了许多新的办法,但在制订反映现实世界应用分子设计复杂性的现实基准方面进展相对甚微。在这项工作中,我们制定了一套实际的基准任务,依靠模拟材料、药物和化学反应方面真实分子设计问题的分子系统物理模拟。此外,我们通过展示如何比较若干成熟的算法系列的性能,展示了我们新基准的效用和容易使用。总的来说,我们认为,我们的基准套件将有助于将该领域推向更现实的分子设计基准,并将反分子设计算法的开发更接近于设计分子的实践,从而解决学术界和工业界的现有问题。