This work introduces MiDi, a diffusion model for jointly generating molecular graphs and corresponding 3D conformers. In contrast to existing models, which derive molecular bonds from the conformation using predefined rules, MiDi streamlines the molecule generation process with an end-to-end differentiable model. Experimental results demonstrate the benefits of this approach: on the complex GEOM-DRUGS dataset, our model generates significantly better molecular graphs than 3D-based models and even surpasses specialized algorithms that directly optimize the bond orders for validity. Our code is available at github.com/cvignac/MiDi.
翻译:这项工作引入了Midi, 这是一种用于联合生成分子图和相应的 3D 相配器的传播模型。 与现有的模型相比,Midi 利用预先定义的规则从符合性中产生分子联结,与现有的模型相比,Midi 将分子生成过程简化为端到端的不同模型。 实验结果显示了这种方法的好处:在复杂的GEOM-DRUGS数据集中,我们的模型生成的分子图比基于3D 的模型要好得多得多,甚至超过了直接优化组合订单以取得有效性的专门算法。 我们的代码可以在 github.com/cvignac/Midi上找到。