Cloud computing for protein-ligand binding site comparison.

The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparis...

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Publicado en:BioMed Research International Vol. 2013; pp. 170356 - 170357
Autores principales: Hung, Che-Lun, Hua, Guan-Jie
Formato: Journal Article
Publicado: Wiley-Blackwell 2013
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Cloud computing for protein-ligand binding site comparison.
      aug:
        au:
          Hung, Che-Lun
          Hua, Guan-Jie
        affil: Department of Computer Science and Communication Engineering, Providence University, Taiwan Boulevard, Shalu District, Taichung 43301, Taiwan.
      sug:
        subj:
          Bioinformatics Methods
          Proteins Metabolism
          Binding Sites
          Internet
          Ligands
          Software
          Time Factors
      ab: The proteome-wide analysis of protein-ligand binding sites and their interactions with ligands is important in structure-based drug design and in understanding ligand cross reactivity and toxicity. The well-known and commonly used software, SMAP, has been designed for 3D ligand binding site comparison and similarity searching of a structural proteome. SMAP can also predict drug side effects and reassign existing drugs to new indications. However, the computing scale of SMAP is limited. We have developed a high availability, high performance system that expands the comparison scale of SMAP. This cloud computing service, called Cloud-PLBS, combines the SMAP and Hadoop frameworks and is deployed on a virtual cloud computing platform. To handle the vast amount of experimental data on protein-ligand binding site pairs, Cloud-PLBS exploits the MapReduce paradigm as a management and parallelizing tool. Cloud-PLBS provides a web portal and scalability through which biologists can address a wide range of computer-intensive questions in biology and drug discovery.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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