1. A pocket-based 3D molecule generative model fueled by experimental electron density
- Author
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Lvwei Wang, Rong Bai, Xiaoxuan Shi, Wei Zhang, Yinuo Cui, Xiaoman Wang, Cheng Wang, Haoyu Chang, Yingsheng Zhang, Jielong Zhou, Wei Peng, Wenbiao Zhou, and Bo Huang
- Subjects
Medicine ,Science - Abstract
Abstract We report for the first time the use of experimental electron density (ED) as training data for the generation of drug-like three-dimensional molecules based on the structure of a target protein pocket. Similar to a structural biologist building molecules based on their ED, our model functions with two main components: a generative adversarial network (GAN) to generate the ligand ED in the input pocket and an ED interpretation module for molecule generation. The model was tested on three targets: a kinase (hematopoietic progenitor kinase 1), protease (SARS‐CoV‐2 main protease), and nuclear receptor (vitamin D receptor), and evaluated with a reference dataset composed of over 8000 compounds that have their activities reported in the literature. The evaluation considered the chemical validity, chemical space distribution-based diversity, and similarity with reference active compounds concerning the molecular structure and pocket-binding mode. Our model can generate molecules with similar structures to classical active compounds and novel compounds sharing similar binding modes with active compounds, making it a promising tool for library generation supporting high-throughput virtual screening. The ligand ED generated can also be used to support fragment-based drug design. Our model is available as an online service to academic users via https://edmg.stonewise.cn/#/create .
- Published
- 2022
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