Capturing molecular interactions in graph neural networks: a case study in multi-component phase equilibrium

作者：Shiyi Qin, Shengli Jiang, Jianping Li, Prasanna Balaprakash, Reid C. Van Lehn, Ví­ctor M. Zavala · 发表于：Digital Discovery · 年份：2022 · DOI：10.1039/d2dd00045h · 被引用次数：53 · 研究领域：Computational Drug Discovery Methods、Machine Learning in Materials Science、Protein Structure and Dynamics

We propose a graph neural network architecture that captures molecular interactions in an explicit manner by combining atomic-level (local) graph convolution and molecular-level (global) message passing through a molecular interaction network.