Blind prediction of interfacial water ...
Type de document :
Article dans une revue scientifique
DOI :
PMID :
URL permanente :
Titre :
Blind prediction of interfacial water positions in CAPRI
Auteur(s) :
Lensink, Marc [Auteur]
Moal, Iain H. [Auteur]
Bates, Paul A. [Auteur]
Kastritis, Panagiotis L. [Auteur]
Melquiond, Adrien S. J. [Auteur]
Karaca, Ezgi [Auteur]
Schmitz, Christophe [Auteur]
van Dijk, Marc [Auteur]
Bonvin, Alexandre M. J. J. [Auteur]
Eisenstein, Miriam [Auteur]
Jiménez-García, Brian [Auteur]
Grosdidier, Solène [Auteur]
Solernou, Albert [Auteur]
Pérez-Cano, Laura [Auteur]
Pallara, Chiara [Auteur]
Fernández-Recio, Juan [Auteur]
Xu, Jianqing [Auteur]
Muthu, Pravin [Auteur]
Praneeth Kilambi, Krishna [Auteur]
Gray, Jeffrey J. [Auteur]
Grudinin, Sergei [Auteur]
Derevyanko, Georgy [Auteur]
Mitchell, Julie C. [Auteur]
Wieting, John [Auteur]
Kanamori, Eiji [Auteur]
Tsuchiya, Yuko [Auteur]
Murakami, Yoichi [Auteur]
Sarmiento, Joy [Auteur]
Standley, Daron M. [Auteur]
Shirota, Matsuyuki [Auteur]
Kinoshita, Kengo [Auteur]
Nakamura, Haruki [Auteur]
Chavent, Matthieu [Auteur]
Ritchie, David W. [Auteur]
Park, Hahnbeom [Auteur]
Ko, Junsu [Auteur]
Lee, Hasup [Auteur]
Seok, Chaok [Auteur]
Shen, Yang [Auteur]
Kozakov, Dima [Auteur]
Vajda, Sandor [Auteur]
Kundrotas, Petras J. [Auteur]
Vakser, Ilya A. [Auteur]
Pierce, Brian G. [Auteur]
Hwang, Howook [Auteur]
Vreven, Thom [Auteur]
Weng, Zhiping [Auteur]
Buch, Idit [Auteur]
Farkash, Efrat [Auteur]
Wolfson, Haim J. [Auteur]
Zacharias, Martin [Auteur]
Qin, Sanbo [Auteur]
Zhou, Huan-Xiang [Auteur]
Huang, Shen-You [Auteur]
Zou, Xiaoqin [Auteur]
Wojdyla, Justyna A. [Auteur]
Kleanthous, Colin [Auteur]
Wodak, Shoshana J. [Auteur]
Moal, Iain H. [Auteur]
Bates, Paul A. [Auteur]
Kastritis, Panagiotis L. [Auteur]
Melquiond, Adrien S. J. [Auteur]
Karaca, Ezgi [Auteur]
Schmitz, Christophe [Auteur]
van Dijk, Marc [Auteur]
Bonvin, Alexandre M. J. J. [Auteur]
Eisenstein, Miriam [Auteur]
Jiménez-García, Brian [Auteur]
Grosdidier, Solène [Auteur]
Solernou, Albert [Auteur]
Pérez-Cano, Laura [Auteur]
Pallara, Chiara [Auteur]
Fernández-Recio, Juan [Auteur]
Xu, Jianqing [Auteur]
Muthu, Pravin [Auteur]
Praneeth Kilambi, Krishna [Auteur]
Gray, Jeffrey J. [Auteur]
Grudinin, Sergei [Auteur]
Derevyanko, Georgy [Auteur]
Mitchell, Julie C. [Auteur]
Wieting, John [Auteur]
Kanamori, Eiji [Auteur]
Tsuchiya, Yuko [Auteur]
Murakami, Yoichi [Auteur]
Sarmiento, Joy [Auteur]
Standley, Daron M. [Auteur]
Shirota, Matsuyuki [Auteur]
Kinoshita, Kengo [Auteur]
Nakamura, Haruki [Auteur]
Chavent, Matthieu [Auteur]
Ritchie, David W. [Auteur]
Park, Hahnbeom [Auteur]
Ko, Junsu [Auteur]
Lee, Hasup [Auteur]
Seok, Chaok [Auteur]
Shen, Yang [Auteur]
Kozakov, Dima [Auteur]
Vajda, Sandor [Auteur]
Kundrotas, Petras J. [Auteur]
Vakser, Ilya A. [Auteur]
Pierce, Brian G. [Auteur]
Hwang, Howook [Auteur]
Vreven, Thom [Auteur]
Weng, Zhiping [Auteur]
Buch, Idit [Auteur]
Farkash, Efrat [Auteur]
Wolfson, Haim J. [Auteur]
Zacharias, Martin [Auteur]
Qin, Sanbo [Auteur]
Zhou, Huan-Xiang [Auteur]
Huang, Shen-You [Auteur]
Zou, Xiaoqin [Auteur]
Wojdyla, Justyna A. [Auteur]
Kleanthous, Colin [Auteur]
Wodak, Shoshana J. [Auteur]
Titre de la revue :
Proteins
Nom court de la revue :
Proteins
Numéro :
82
Pagination :
620-632
Date de publication :
2014-04
ISSN :
1097-0134
Mot(s)-clé(s) en anglais :
Water
Colicins
Algorithms
protein interface
Capri
protein docking
Computational Biology
Models, Molecular
Blind prediction
Protein Conformation
Molecular Docking Simulation
Protein Interaction Mapping
Colicins
Algorithms
protein interface
Capri
protein docking
Computational Biology
Models, Molecular
Blind prediction
Protein Conformation
Molecular Docking Simulation
Protein Interaction Mapping
Discipline(s) HAL :
Chimie/Chimie théorique et/ou physique
Résumé en anglais : [en]
We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting ...
Lire la suite >We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes.Lire moins >
Lire la suite >We report the first assessment of blind predictions of water positions at protein-protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community-wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions-20 groups submitted a total of 195 models-were assessed by measuring the recall fraction of water-mediated protein contacts. Of the 176 high- or medium-quality docking models-a very good docking performance per se-only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high-quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein-water interactions and their role in stabilizing protein complexes.Lire moins >
Langue :
Anglais
Établissement(s) :
CNRS
Université de Lille
Université de Lille
Équipe(s) de recherche :
Computational Molecular Systems Biology
Date de dépôt :
2020-02-12T16:20:24Z