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Title
Japanese:タンパク質の特性に基づくunboundドッキングのための剛体予測手法の改良 
English:Improvement of rigid-body prediction for unbound docking based on protein feature 
Author
Japanese: 松崎裕介, 大上雅史, 松崎由理, 佐藤智之, 関嶋政和, 秋山泰.  
English: Yusuke Matsuzaki, Masahito Ohue, Yuri Matsuzaki, Toshiyuki Sato, Masakazu Sekijima, Yutaka Akiyama.  
Language Japanese 
Journal/Book name
Japanese:研究報告バイオ情報学（BIO） 
English:IPSJ SIG Technical Report 
Volume, Number, Page Vol. 2010-BIO-20    No. 4    pp. 1-8
Published date Feb. 25, 2010 
Publisher
Japanese:情報処理学会 
English: 
Conference name
Japanese:情報処理学会 第20回バイオ情報学研究会 
English: 
Conference site
Japanese:石川県 
English: 
Official URL https://ipsj.ixsq.nii.ac.jp/ej/?action=pages_view_main&active_action=repository_view_main_item_detail&item_id=68043&item_no=1&page_id=13&block_id=8
 
Abstract In protein-protein docking prediction system MEGADOCK that we are developing, the target function calculating the docking scores depends on the shape complementarity and electrostatic interaction. And the weight of each term doesn't depend on the target protein and be constant. However, there are a lot of varieties in the shape of proteins and their conformational changes in the docking. Thus, the improvement of the prediction can be expected by changing this proportion in the target function based on the feature of proteins. In this study, we proposed a new method to optimize the electrostatic weight of the target function based on the feature of individual proteins such as the solvent accessible surface area, the surface charge and the structural changes, for improving the docking prediction in the unbound docking.

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