2016
DOI: 10.2174/157016461302160514003915
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Predicting Protein Ligand Binding Sites with Structure Alignment Method on Hadoop

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Cited by 5 publications
(6 citation statements)
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“…In molecular docking, [16] observed a fall in parallel efficiency of 55.3% (99.1% -43.8%) when scaling from 2 nodes to 32 nodes. In structural alignment, [39] observed that performance degraded slightly after 8 mappers was increased to 30. Furthermore, this trend has also been observed on the MS Azure platform we have discussed for comparison -in scaling Cloud4Psi, also a structural alignment application [51], observed that horizontal scaling resulted in performance degradation as a result of an increase in nodes sharing a virtual disk, and that vertical scaling resulted in performance degradation as a result of increased CPU utilisation (due to more processes running per node).…”
Section: Discussionmentioning
confidence: 99%
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“…In molecular docking, [16] observed a fall in parallel efficiency of 55.3% (99.1% -43.8%) when scaling from 2 nodes to 32 nodes. In structural alignment, [39] observed that performance degraded slightly after 8 mappers was increased to 30. Furthermore, this trend has also been observed on the MS Azure platform we have discussed for comparison -in scaling Cloud4Psi, also a structural alignment application [51], observed that horizontal scaling resulted in performance degradation as a result of an increase in nodes sharing a virtual disk, and that vertical scaling resulted in performance degradation as a result of increased CPU utilisation (due to more processes running per node).…”
Section: Discussionmentioning
confidence: 99%
“…A variety of of algorithms have been developed to perform structural alignment of proteins, such as, for example, STRUCTAL (Structural Analysis Algorithm), DALI (Distant Alignment) [22], CE (Combinatorial Extension) [69], VAST (Vector Alignment Search Tool) [19], and FATCAT (Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists) [82], SSAP (Sequential Structure Alignment Program) [57], and MUSTANG (Multiple Sequence Alignment Algorithm) [32]. The technique has been applied to the study of protein binding sites, and solvent exposed surfaces (these effect the energetics of protein-ligand conformations) [42,33,39].…”
Section: Structural Alignmentmentioning
confidence: 99%
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“…A variety of of algorithms have been developed to perform structural alignment of proteins, such [77], CE (Combinatorial Extension) [78], VAST (Vector Alignment Search Tool) [75], and FATCAT (Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists) [79], SSAP (Sequential Structure Alignment Program) [80], and MUSTANG (Multiple Sequence Alignment Algorithm) [81]. The technique has been applied to the study of protein binding sites, and solvent exposed surfaces (these effect the energetics of protein-ligand conformations) [82,83,84].…”
Section: Structural Alignmentmentioning
confidence: 99%
“…There is also a need to apply such techniques at scale. For example, Hadoop has been employed by [84] who implemented structural alignment for binding site prediction. Using test sets of 200 and 48 ligand-protein complexes, they were able to achieve 93% and 98% accuracy, respectively, and were able to improve the efficiency of the experiment by exploiting parallelisation.…”
Section: Structural Alignmentmentioning
confidence: 99%