A high performance cloud-based protein-ligand docking prediction algorithm.
The potential of predicting draggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the...
| Publicado en: | BioMed Research International Vol. 2013; pp. 909717 - 909718 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Wiley-Blackwell
2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109857948&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109857948 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 2013 vid: 2013 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 109857948 2012152596 NLM23762864 PMC3666298 109857948 ppf: 909717 ppct: 1 formats: fmt: @attributes: type: P tig: atl: A high performance cloud-based protein-ligand docking prediction algorithm. aug: au: Chen, Jui-Le Tsai, Chun-Wei Chiang, Ming-Chao Yang, Chu-Sing affil: Department of Electrical Engineer, National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan 70101, Taiwan ; Department of Digital Multimedia Design, Tajen University, Pingtung 90741, Taiwan. sug: subj: Algorithms Internet Computer Simulation Proteins Metabolism Ligands Time Factors ab: The potential of predicting draggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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