- Title
- Predicting protein protein interfaces as clusters of optimal docking area points
- Creator
- Arafat, Yasir; Kamruzzaman, Joarder; Karmakar, Gour; Fernandez-Recio, Juan
- Date
- 2009
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/55311
- Identifier
- vital:6203
- Identifier
- ISSN:1748-5673
- Abstract
- Abstract: Desolvation property is used here to predict protein-protein binding sites exploiting the fact that lower-valued 'optimal docking area' ODA (Fernandez-Recio et al., 2005) points form cluster at the interface. The proposed method involves two steps; clustering the ODA points and representing ODA points by average ODA values. On 51 nonredundant proteins, results show the success rate improved considerably. Considering only significant ODA, the previous ODA method has obtained a success rate of 65% with overall success rate of 39%. The proposed method improved the overall success rate to 61%. Further, comparable results were found for X-ray and NMR structures.
- Relation
- International Journal of data mining and bioinformatics Vol. 3, no. 1 (2009), p. 55-67
- Rights
- Copyright Inderscience
- Rights
- This metadata is freely available under a CCO license
- Subject
- 01 Mathematical Sciences; 06 Biological Sciences; 08 Information and Computing Sciences; Desolvation energy; Protein; Protein binding
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