MoleQCage: Geometric High-Throughput Screening for Molecular Caging Prediction

Although being able to determine whether a host molecule can enclose a guest molecule and form a caging complex could benefit numerous chemical and medical applications, the experimental discovery of molecular caging complexes has not yet been achieved at scale. Here, we propose MoleQCage, a simple tool for the high-throughput screening of host and guest candidates based on an efficient robotics-inspired geometric algorithm for molecular caging prediction, providing theoretical guarantees and robustness assessment. MoleQCage is distributed as Linux-based software with a graphical user interface and is available online at https://hub.docker.com/r/dantrigne/moleqcage in the form of a Docker container. Documentation and examples are available as Supporting Information and online at https://hub.docker.com/r/dantrigne/moleqcage.尽管能够判定主体分子是否可包裹客体分子并形成笼状配合物可赋能众多化学与医学应用，但目前尚未能大规模通过实验发现分子笼状配合物。在此，我们提出MoleQCage——一款基于受机器人学启发的高效几何算法以预测分子笼状配合物的工具，可用于主体与客体候选物的高通量筛选，并提供理论保证与稳健性评估。MoleQCage以基于Linux且搭载图形用户界面的软件形式分发，并可通过https://hub.docker.com/r/dantrigne/moleqcage以Docker容器的形式在线获取。相关文档与示例可作为支持信息获取，同时也可在上述Docker容器页面在线查阅。