Ryu Gina, Kim Wankyu
Department of Life Sciences, College of Natural Science, Ewha Womans University, Seoul, 03760, Republic of Korea.
KaiPharm, Seoul, 03759, Republic of Korea.
J Cheminform. 2025 May 5;17(1):70. doi: 10.1186/s13321-025-01023-2.
This study demonstrates the utility of a novel molecular representation, 3D APM and a deep learning model based on it for virtual screening, suggesting that many other prediction models would also benefit from adopting APM. An open-source script to generate 3D APM is available at https://github.com/rimeless/APM.
本研究证明了一种新型分子表示法——3D APM及其基于此的深度学习模型在虚拟筛选中的效用,这表明许多其他预测模型采用APM也将受益。可在https://github.com/rimeless/APM获取用于生成3D APM的开源脚本。