中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 近代物理研究所
  3. 中国科学院近代物理研究所
Transformer-Based Generative Model Accelerating the Development of Novel BRAF Inhibitors

文献类型：期刊论文

作者Yang, Lijuan1,2,3,4; Yang, Guanghui1,4; Bing, Zhitong1,4; Tian, Yuan1,5; Niu, Yuzhen6; Huang, Liang2; Yang, Lei1,4
刊名ACS OMEGA
出版日期2021-12-14
卷号6期号:49页码:33864-33873
ISSN号2470-1343
DOI10.1021/acsomega.1c05145
通讯作者Niu, Yuzhen(niuyzh12@lzu.edu.cn) ; Yang, Lei(lyang_imp@outlook.com)
英文摘要The de novo drug design based on SMILES format is a typical sequence-processing problem. Previous methods based on recurrent neural network (RNN) exhibit limitation in capturing long-range dependency, resulting in a high invalid percentage in generated molecules. Recent studies have shown the potential of Transformer architecture to increase the capacity of handling sequence data. In this work, the encoder module in the Transformer is used to build a generative model. First, we train a Transformer-encoder-based generative model to learn the grammatical rules of known drug molecules and a predictive model to predict the activity of the molecules. Subsequently, transfer learning and reinforcement learning were used to fine-tune and optimize the generative model, respectively, to design new molecules with desirable activity. Compared with previous RNN-based methods, our method has improved the percentage of generating chemically valid molecules (from 95.6 to 98.2%), the structural diversity of the generated molecules, and the feasibility of molecular synthesis. The pipeline is validated by designing inhibitors against the human BRAF protein. Molecular docking and binding mode analysis showed that our method can generate small molecules with higher activity than those carrying ligands in the crystal structure and have similar interaction sites with these ligands, which can provide new ideas and suggestions for pharmaceutical chemists.
WOS关键词PROTEINS ; DESIGN
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA21010202]
WOS研究方向Chemistry
语种英语
出版者AMER CHEMICAL SOC
WOS记录号WOS:000757388000057
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences
源URL[http://119.78.100.186/handle/113462/142062]  
专题中国科学院近代物理研究所
通讯作者Niu, Yuzhen; Yang, Lei
作者单位1.Chinese Acad Sci, Inst Modern Phys, Lanzhou 730000, Peoples R China
2.Lanzhou Univ, Sch Phys & Technol, Lanzhou 730000, Peoples R China
3.Univ Chinese Acad Sci, Sch Phys, Beijing 100049, Peoples R China
4.Guangdong Lab, Adv Energy Sci & Technol, Huizhou 516000, Peoples R China
5.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Peoples R China
6.Shandong Univ Technol, Shandong Prov Res Ctr Bioinformat Engn & Tech, Sch Life Sci, Zibo 255000, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Lijuan,Yang, Guanghui,Bing, Zhitong,et al. Transformer-Based Generative Model Accelerating the Development of Novel BRAF Inhibitors[J]. ACS OMEGA,2021,6(49):33864-33873.
APA Yang, Lijuan.,Yang, Guanghui.,Bing, Zhitong.,Tian, Yuan.,Niu, Yuzhen.,...&Yang, Lei.(2021).Transformer-Based Generative Model Accelerating the Development of Novel BRAF Inhibitors.ACS OMEGA,6(49),33864-33873.
MLA Yang, Lijuan,et al."Transformer-Based Generative Model Accelerating the Development of Novel BRAF Inhibitors".ACS OMEGA 6.49(2021):33864-33873.

入库方式： OAI收割

来源：近代物理研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。