Blind prediction of interfacial water positions in CAPRI

Marc F. Lensink 1 Aiain H. Moal 2 Paul A. Bates 2 Panagiotis L. Kastritis 3 Adrien S. J. Melquiond 3 Ezgi Karaca 3 Christophe Schmitz 3 Marc Van Dijk 3 Alexandre Bonvin 3 Miriam Eisenstein 4 Brian Jiménez-Garcí 5 Solène Grosdidier 5 Albert Solernou 5 Laura Pérez-Cano 5 Chiara Pallar 5 Juan Fernández-Recio 5 Jianqing Xu 6 Pravin Muthu 7 Krishna Praneeth Kilambi 6 Jeffrey Gray 6, 7 Sergei Grudinin 8 Georgy Derevyanko 8 Julie Mitchell 9 John Wieting 9 Eiji Kanamori 10 Yuko Tsuchiya 11 Yoichi Murakami 12 Joy Sarmiento 13 Daron Standley 13 Matsuyuki Shirota 14 Kengo Kinoshita 14 Haruki Nakamura 11 Matthieu Chavent 15 Hahnbeom Park 16 Junsu Ko 16 Hasup Lee 16 Chaok Seok 16 Yang Shen 17 Dima Kozakov 18 Sandor Vajda 18 Petras Kundrotas 19 Ilya Vakser 19 Brian Pierce 20 Howook Hwang 20 Thom Vreven 20 Zhiping Weng 20 Idit Buch 21 Efrat Farkash 22 Haim Wolfson 22 Martin Zacharias 23 Sanbo Qin 24 Huan-Xiang Zhou 23, 24 Shen-You Huang 25, 26, 27 Xiaoqin Zou 25, 26, 27 Justyna Wojdyla 28 Colin Kleanthous 28 Shoshana Wodak 29, 30
8 NANO-D - Algorithms for Modeling and Simulation of Nanosystems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
17 SRMA - Service des Recherches Métallurgiques Appliquées
DMN - Département des Matériaux pour le Nucléaire : DEN/DMN
Abstract : 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.
Type de document :
Article dans une revue
Proteins - Structure, Function and Bioinformatics, Wiley, 2014, 82 (4), pp.620-632. 〈10.1002/prot.24439〉
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Soumis le : mardi 5 novembre 2013 - 19:21:05
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Marc F. Lensink, Aiain H. Moal, Paul A. Bates, Panagiotis L. Kastritis, Adrien S. J. Melquiond, et al.. Blind prediction of interfacial water positions in CAPRI. Proteins - Structure, Function and Bioinformatics, Wiley, 2014, 82 (4), pp.620-632. 〈10.1002/prot.24439〉. 〈hal-00880345〉



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