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 M. J. J. 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 J. Gray
(6, 7)
,
Sergei Grudinin
(8)
,
Georgy Derevyanko
(8)
,
Julie C. Mitchell
(9)
,
John Wieting
(9)
,
Eiji Kanamori
(10)
,
Yuko Tsuchiya
(11)
,
Yoichi Murakami
(12)
,
Joy Sarmiento
(13)
,
Daron M. 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 J. Kundrotas
(19)
,
Ilya A. Vakser
(19)
,
Brian G. Pierce
(20)
,
Howook Hwang
(20)
,
Thom Vreven
(20)
,
Zhiping Weng
(20)
,
Idit Buch
(21)
,
Efrat Farkash
(22)
,
Haim J. 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 A. Wojdyla
(28)
,
Colin Kleanthous
(28)
,
Shoshana J. Wodak
(29, 30)
1
IRI -
Institut de Recherche Interdisciplinaire [Villeneuve d'Ascq]
2 Biomolecular Modelling laboratory [London]
3 Bijvoet Center for Biomolecular Research [Utrecht]
4 Chemical Research Support [Rehovot]
5 BSC-CNS - Barcelona Supercomputing Center - Centro Nacional de Supercomputacion
6 Department of Chemical and Biomolecular Engineering [Baltimore]
7 Program in Molecular Biophysics [Baltimore]
8 NANO-D - Algorithms for Modeling and Simulation of Nanosystems
9 University of Wisconsin-Madison
10 Japan Biological Informatics Consortium [Tokyo]
11 Institute for Protein Research [Osaka]
12 National Institute of Biomedical Innovation [Osaka]
13 IFREC - WPI Immunology Frontier Research Center
14 Graduate School of Information Sciences [Sendai]
15 LBT (UPR_9080) - Laboratoire de biochimie théorique [Paris]
16 Department of Chemistry
17 SRMA - Service des Recherches Métallurgiques Appliquées
18 Department of Biomedical Engineering [Boston]
19 Department of Molecular Biosciences [Lawrence]
20 Institute of Molecular Biophysics [Tallahassee]
21 TAU - Tel Aviv University
22 TAU-CS - School of Computer Science
23 Physics Department [Garching]
24 Department of Physics [Tallahassee]
25 Dalton Cardiovascular Research Center [Columbia]
26 Mizzou Physics - Department of Physics and Astronomy [Columbia]
27 Informatics Institute [Columbia]
28 Department of Biochemistry [Oxford]
29 SickKids - The Hospital for sick children [Toronto]
30 Department of Molecular Genetics [Toronto]
2 Biomolecular Modelling laboratory [London]
3 Bijvoet Center for Biomolecular Research [Utrecht]
4 Chemical Research Support [Rehovot]
5 BSC-CNS - Barcelona Supercomputing Center - Centro Nacional de Supercomputacion
6 Department of Chemical and Biomolecular Engineering [Baltimore]
7 Program in Molecular Biophysics [Baltimore]
8 NANO-D - Algorithms for Modeling and Simulation of Nanosystems
9 University of Wisconsin-Madison
10 Japan Biological Informatics Consortium [Tokyo]
11 Institute for Protein Research [Osaka]
12 National Institute of Biomedical Innovation [Osaka]
13 IFREC - WPI Immunology Frontier Research Center
14 Graduate School of Information Sciences [Sendai]
15 LBT (UPR_9080) - Laboratoire de biochimie théorique [Paris]
16 Department of Chemistry
17 SRMA - Service des Recherches Métallurgiques Appliquées
18 Department of Biomedical Engineering [Boston]
19 Department of Molecular Biosciences [Lawrence]
20 Institute of Molecular Biophysics [Tallahassee]
21 TAU - Tel Aviv University
22 TAU-CS - School of Computer Science
23 Physics Department [Garching]
24 Department of Physics [Tallahassee]
25 Dalton Cardiovascular Research Center [Columbia]
26 Mizzou Physics - Department of Physics and Astronomy [Columbia]
27 Informatics Institute [Columbia]
28 Department of Biochemistry [Oxford]
29 SickKids - The Hospital for sick children [Toronto]
30 Department of Molecular Genetics [Toronto]
Marc F. Lensink
- Function : Author
- PersonId : 180132
- IdHAL : marc-lensink
- ORCID : 0000-0003-3957-9470
- IdRef : 223604917
Sergei Grudinin
- Function : Author
- PersonId : 175316
- IdHAL : sergei-grudinin
- ORCID : 0000-0002-1903-7220
- IdRef : 186189729
Matsuyuki Shirota
- Function : Author
- PersonId : 769730
- ORCID : 0000-0002-7776-9964
Matthieu Chavent
- Function : Author
- PersonId : 180797
- IdHAL : matthieu-chavent
- ORCID : 0000-0003-4524-4773
- IdRef : 142529273
Yang Shen
- Function : Author
- PersonId : 768356
- ORCID : 0000-0002-1703-7796
Dima Kozakov
- Function : Author
- PersonId : 761929
- ORCID : 0000-0003-0464-4500
Sandor Vajda
- Function : Author
- PersonId : 761930
- ORCID : 0000-0003-1540-8220
Xiaoqin Zou
- Function : Author
- PersonId : 765071
- ORCID : 0000-0003-0637-8648
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.