GNN-MTB: An Anti-Mycobacterium Drug Virtual Screening Method based on Graph Neural Network Gu Yaowen, Zheng Si, Yang Chunfeng,Li Jiao (Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020,China) Abstract:[Objective] This study aims to construct an anti-tuberculosis drug virtual screening model for the research and development of anti-tuberculosis drugs. [Methods] We proposed a curriculum learning-optimized graph neural network model for anti- tuberculosis inhibitors virtual screening, which called GNN-MTB. Furthermore, a benchmark dataset for anti-tuberculosis drugs was collected from the public database, then we compared the performance of GNN-MTB with four classic machine learning models and two graph neural network models on the benchmark dataset. [Results] We collected and integrated 10,789 available anti-tuberculosis drug screening experimental data as our benchmark dataset. Our proposed GNN-MTB model achieved the area under the receiver operating