IDOS: Improved D3DOCK on Spark
文献类型：期刊论文
| 作者 | Cui, Yonghui1; Xu, Zhijian2 ; Peng, Shaoliang1
|
| 刊名 | BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2021
 |
| 出版日期 | 2021 |
| 卷号 | 13064页码:436-447 |
| 关键词 | Molecular docking Virtual drug screening Big data Distributed computing Spark |
| ISSN号 | 0302-9743 |
| DOI | 10.1007/978-3-030-91415-8_37 |
| 文献子类 | Proceedings Paper |
| 英文摘要 | Virtual molecular docking is a computational method used in computer-aided drug discovery that calculates the binding affinity of a small molecule drug candidate to a target protein and greatly reduces the time and cost of suggesting new potential pharmaceuticals. D3DOCK is a suite of automated docking tools, it was developed for sensitively investigating the effects of halogen bond in drug discovery by based on Autodock Vina. In this study, we developed IDOS, a high-throughput and scalable virtual docking system. We use the open source Hadoop framework implementing the Spark paradigm for distributed computing on a private cloud platform. IDOS can work on a single node as well as on distributed nodes compared with the stand-alone version of D3DOCK, it performed almost linear acceleration on our Spark cluster, with parallel efficiency of more than 80%, and 5x to 6x speedup can be achieved on the cluster depending on the number of work nodes. Moreover, On account of the widely used of cloud computing, IDOS can be easily installed and employed for docking on condition that the IDOS docker image was upload to the docker hub shared warehouse. We also have developed the docking workflow with an MPI version on high-performance computers (HPC). However, compared with HPC system, mounting IDOS on a cheap and easy to obtain cloud computing cluster is obviously more conducive, which allows more researchers to do docking with it expediently. IDOS is freely available at https://github.com/codedinner/IDOS. |
| WOS关键词 | MOLECULAR DOCKING |
| WOS研究方向 | Computer Science ; Mathematical & Computational Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:000922632800037 |
| 出版者 | SPRINGER INTERNATIONAL PUBLISHING AG |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/309400]  |
| 专题 | 新药研究国家重点实验室 |
| 通讯作者 | Peng, Shaoliang |
| 作者单位 | 1.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Peoples R China; 2.Chinese Acad Sci, Drug Discovery & Design Ctr, State Key Lab Drug Res, Shanghai Inst Mat Med, Shanghai, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cui, Yonghui,Xu, Zhijian,Peng, Shaoliang. IDOS: Improved D3DOCK on Spark[J]. BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2021,2021,13064:436-447. |
| APA | Cui, Yonghui,Xu, Zhijian,&Peng, Shaoliang.(2021).IDOS: Improved D3DOCK on Spark.BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2021,13064,436-447. |
| MLA | Cui, Yonghui,et al."IDOS: Improved D3DOCK on Spark".BIOINFORMATICS RESEARCH AND APPLICATIONS, ISBRA 2021 13064(2021):436-447. |
入库方式： OAI收割
来源：上海药物研究所
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。