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D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds

文献类型：期刊论文

作者Ma, Minfei1,2,3; Zhang, Xinben1,3; Zhou, Liping1,2,3; Han, Zijian1,2,3; Shi, Yulong1,2,3; Li, Jintian1,2,3; Wu, Leyun1,2,3; Xu, Zhijian1,2,3; Zhu, Weiliang1,2,3
刊名JOURNAL OF CHEMICAL INFORMATION AND MODELING
出版日期2024-01-11
卷号64期号:3页码:724-736
ISSN号1549-9596
DOI10.1021/acs.jcim.3c01657
通讯作者Xu, Zhijian(zjxu@simm.ac.cn) ; Zhu, Weiliang(wlzhu@simm.ac.cn)
英文摘要Continuous exploration of the chemical space of molecules to find ligands with high affinity and specificity for specific targets is an important topic in drug discovery. A focus on cyclic compounds, particularly natural compounds with diverse scaffolds, provides important insights into novel molecular structures for drug design. However, the complexity of their ring structures has hindered the applicability of widely accepted methods and software for the systematic identification and classification of cyclic compounds. Herein, we successfully developed a new method, D3Rings, to identify acyclic, monocyclic, spiro ring, fused and bridged ring, and cage ring compounds, as well as macrocyclic compounds. By using D3Rings, we completed the statistics of cyclic compounds in three different databases, e.g., ChEMBL, DrugBank, and COCONUT. The results demonstrated the richness of ring structures in natural products, especially spiro, macrocycles, and fused and bridged rings. Based on this, three deep generative models, namely, VAE, AAE, and CharRNN, were trained and used to construct two data sets similar to DrugBank and COCONUT but 10 times larger than them. The enlarged data sets were then used to explore the molecular chemical space, focusing on complex ring structures, for novel drug discovery and development. Docking experiments with the newly generated COCONUT-like data set against three SARS-CoV-2 target proteins revealed that an expanded compound database improves molecular docking results. Cyclic structures exhibited the best docking scores among the top-ranked docking molecules. These results suggest the importance of exploring the chemical space of structurally novel cyclic compounds and continuous expansion of the library of drug-like compounds to facilitate the discovery of potent ligands with high binding affinity to specific targets. D3Rings is now freely available at http://www.d3pharma.com/D3Rings/.
WOS关键词CHEMICAL SPACE ; LANGUAGE
资助项目National Natural Science Foundation of China[2022YFA1004304] ; National Key Research and Development Program of China[82273851] ; National Key Research and Development Program of China[82322067] ; National Natural Science Foundation of China
WOS研究方向Pharmacology & Pharmacy ; Chemistry ; Computer Science
语种英语
出版者AMER CHEMICAL SOC
WOS记录号WOS:001161570600001
源URL[http://119.78.100.183/handle/2S10ELR8/309216]  
专题中国科学院上海药物研究所
通讯作者Xu, Zhijian; Zhu, Weiliang
作者单位1.Chinese Acad Sci, Shanghai Inst Materia Med, Drug Discovery & Design Ctr, Shanghai 201203, Peoples R China
2.Univ Chinese Acad Sci, Sch Pharm, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Stake Key Lab Drug Res, Shanghai 201203, Peoples R China
推荐引用方式
GB/T 7714		 Ma, Minfei,Zhang, Xinben,Zhou, Liping,et al. D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds[J]. JOURNAL OF CHEMICAL INFORMATION AND MODELING,2024,64(3):724-736.
APA Ma, Minfei.,Zhang, Xinben.,Zhou, Liping.,Han, Zijian.,Shi, Yulong.,...&Zhu, Weiliang.(2024).D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds.JOURNAL OF CHEMICAL INFORMATION AND MODELING,64(3),724-736.
MLA Ma, Minfei,et al."D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds".JOURNAL OF CHEMICAL INFORMATION AND MODELING 64.3(2024):724-736.

入库方式： OAI收割

来源：上海药物研究所

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