An Integrated Deep Learning and Molecular Dynamics Simulation-Based Screening Pipeline Identifies Inhibitors of a New Cancer Drug Target TIPE2
文献类型：期刊论文
| 作者 | Zhang, Haiping3; Li, Junxin2; Saravanan, Konda Mani3; Wu, Hao3; Wang, Zhichao3; Wu, Du3; Wei, Yanjie3; Lu, Zhen1; Chen, Youhai H.1; Wan, Xiaochun2 |
| 刊名 | FRONTIERS IN PHARMACOLOGY
 |
| 出版日期 | 2021-11-23 |
| 卷号 | 12页码:13 |
| 关键词 | TIPE2 UM-164 virtual screening deep learning molecular dynamics simulation |
| DOI | 10.3389/fphar.2021.772296 |
| 英文摘要 | The TIPE2 (tumor necrosis factor-alpha-induced protein 8-like 2) protein is a major regulator of cancer and inflammatory diseases. The availability of its sequence and structure, as well as the critical amino acids involved in its ligand binding, provides insights into its function and helps greatly identify novel drug candidates against TIPE2 protein. With the current advances in deep learning and molecular dynamics simulation-based drug screening, large-scale exploration of inhibitory candidates for TIPE2 becomes possible. In this work, we apply deep learning-based methods to perform a preliminary screening against TIPE2 over several commercially available compound datasets. Then, we carried a fine screening by molecular dynamics simulations, followed by metadynamics simulations. Finally, four compounds were selected for experimental validation from 64 candidates obtained from the screening. With surprising accuracy, three compounds out of four can bind to TIPE2. Among them, UM-164 exhibited the strongest binding affinity of 4.97 mu M and was able to interfere with the binding of TIPE2 and PIP2 according to competitive bio-layer interferometry (BLI), which indicates that UM-164 is a potential inhibitor against TIPE2 function. The work demonstrates the feasibility of incorporating deep learning and MD simulation in virtual drug screening and provides high potential inhibitors against TIPE2 for drug development. |
| 资助项目 | Shenzhen KQTD Project[KQTD20200820113106007] ; National Key R&D Program of China[2019YFA0906100] ; Key-Area Research and Development Program of Guangdong Province[2019B020201014] ; Guangdong Basic and Applied Basic Research Foundation[2020A1515110840] ; Shenzhen Basic Research Fund[KQTD20200820113106007] ; Shenzhen Basic Research Fund[JCYJ20190807170801656] ; Shenzhen Basic Research Fund[RCYX2020071411473419] ; National Key Research and Development Program of China[2018YFB0204403] ; Research Funding of Shenzhen[JCYJ201803053000708] ; Strategic Priority CAS[XDB38000000] ; National Science Foundation of China[U1813203] ; CAS Key Lab[2011DP173015] |
| WOS研究方向 | Pharmacology & Pharmacy |
| 语种 | 英语 |
| 出版者 | FRONTIERS MEDIA SA |
| WOS记录号 | WOS:000727671000001 |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/18022]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Chen, Youhai H.; Wan, Xiaochun; Pan, Yi |
| 作者单位 | 1.Chinese Acad Sci, Univ City Shenzhen, Shenzhen Inst Adv Technol, Ctr Canc Immunol, Shenzhen, Peoples R China 2.Chinese Acad Sci, Univ City Shenzhen, Shenzhen Inst Adv Technol, Inst Biomed & Biotechnol,Shenzhen Lab Human Antib, Shenzhen, Peoples R China 3.Chinese Acad Sci, Shenzhen Inst Adv Technol, Joint Engn Res Ctr Hlth Big Data Intelligent Anal, Ctr High Performance Comp, Shenzhen, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Haiping,Li, Junxin,Saravanan, Konda Mani,et al. An Integrated Deep Learning and Molecular Dynamics Simulation-Based Screening Pipeline Identifies Inhibitors of a New Cancer Drug Target TIPE2[J]. FRONTIERS IN PHARMACOLOGY,2021,12:13. |
| APA | Zhang, Haiping.,Li, Junxin.,Saravanan, Konda Mani.,Wu, Hao.,Wang, Zhichao.,...&Pan, Yi.(2021).An Integrated Deep Learning and Molecular Dynamics Simulation-Based Screening Pipeline Identifies Inhibitors of a New Cancer Drug Target TIPE2.FRONTIERS IN PHARMACOLOGY,12,13. |
| MLA | Zhang, Haiping,et al."An Integrated Deep Learning and Molecular Dynamics Simulation-Based Screening Pipeline Identifies Inhibitors of a New Cancer Drug Target TIPE2".FRONTIERS IN PHARMACOLOGY 12(2021):13. |
入库方式： OAI收割
来源：计算技术研究所
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