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Open Access

A Non-Redundant Benchmark for Symmetric Protein Docking

Institute of Biophysics, Huazhong University of Science and Technology, Wuhan 430074, China.
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Abstract

Symmetric proteins play important roles in many biological processes, such as signal transduction and molecular transportation. Therefore, determining the symmetric oligomeric structure of subunits is crucial to investigate the molecular mechanism of the related processes. Due to the high cost and technical difficulties associated with many experimental methods, computational approaches, such as molecular docking, have played an important complementary role in the determination of symmetric complex structures, in which a benchmark data set is pressingly needed. In the present work, we develop a comprehensive and non-redundant benchmark for symmetric protein docking based on the structures in the Protein Data Bank (PDB). The diverse dataset consists of 251 targets, including 212 cases with cyclic groups symmetry, 35 cases with dihedral groups symmetry, 3 cases with cubic groups symmetry, and 1 case with helical symmetry. According to the conformational changes in the interface between bound and unbound structures, the 251 targets were classified into three groups: 176 "easy", 37 "medium", and 38 "difficult" cases. A preliminary docking test on the targets of cyclic groups symmetry with M-ZDOCK indicated that symmetric multimer docking remains challenging. The benchmark will be beneficial for the development of symmetric protein docking algorithms. The proposed benchmark data set is available for download at http://huanglab.phys.hust.edu.cn/SDBenchmark/.

Keywords

benchmarksymmetric protein

References

[1]
Y. Kosmann-Schwarzbach, The Noether Theorems. New York, NY, USA: Springer, 2011, pp. 55-64.
Crossref
[2]
D. S. Goodsell and A. J. Olson, Structural symmetry and protein function, Ann. Rev. Biophys. Biomol. Struct., vol. 29, no. 1, pp. 105-153, 2000.
Crossref Google Scholar
[3]
I. A. Vakser, Protein-protein docking: From interaction to interactome, Biophys. J., vol. 107, no. 8, pp. 1785-1793, 2014.
Crossref Google Scholar
[4]
G. Waksman and C. Sansom, Introduction: Proteomics and protein-protein interactions: Biology, chemistry, bioinformatics, and drug design, in Proteomics and Protein-Protein Interactions, G. Waksman, ed. Boston, MA, USA: Springer, 2005, pp. 1-18.
Crossref
[5]
S. Y. Huang, Search strategies and evaluation in protein-protein docking: Principles, advances and challenges, Drug Discov. Today, vol. 19, no. 8, pp. 1081-1096, 2014.
Crossref Google Scholar
[6]
R. J. Bienstock, Computational drug design targeting protein-protein interactions, Curr. Pharm. Des., vol. 18, no. 9, pp. 1240-1254, 2012.
Crossref Google Scholar
[7]
Y. M. Yan, Z. Y. Wen, X. X. Wang, and S. Y. Huang, Addressing recent docking challenges: A hybrid strategy to integrate template-based and free protein-protein docking, Proteins, vol. 85, no. 3, pp. 497-512, 2017.
Crossref Google Scholar
[8]
B. Pierce, W. Tong, and Z. Weng, M-ZDOCK: A grid-based approach for Cn symmetric multimer docking, Bioinformatics, vol. 21, no. 8, pp. 1472-1478, 2004.
Crossref Google Scholar
[9]
B. G. Pierce, K. Wiehe, H. Hwang, B. H. Kim, T. Vreven, and Z. P. Weng, ZDOCK server: Interactive docking prediction of protein-protein complexes and symmetric multimers, Bioinformatics, vol. 30, no. 12, pp. 1771-1773, 2014.
Crossref Google Scholar
[10]
I. André, P. Bradley, C. Wang, and D. Baker, Prediction of the structure of symmetrical protein assemblies, Proc. Natl. Acad. Sci. USA, vol. 104, no. 45, pp. 17656-17661, 2007.
Crossref Google Scholar
[11]
D. Schneidman-Duhovny, Y. Inbar, R. Nussinov, and H. J. Wolfson, PatchDock and SymmDock: Servers for rigid and symmetric docking, Nucleic Acids Res., vol. 33, pp. 363-367, 2005.
Crossref Google Scholar
[12]
D. Schneidman-Duhovny, Y. Inbar, R. Nussinov, and H. J. Wolfson, Geometry-based flexible and symmetric protein docking, Proteins, vol. 60, no. 2, pp. 224-231, 2005.
Crossref Google Scholar
[13]
M. Baek, T. Park, L. Heo, C. Park, and C. Seok, GalaxyHomomer: A web server for protein homo-oligomer structure prediction from a monomer sequence or structure, Nucleic Acids Res., vol. 45, no. 1, pp. 320-324, 2017.
Crossref Google Scholar
[14]
I. A. Vakser, Evaluation of GRAMM low-resolution docking methodology on the hemagglutinin-antibody complex, Proteins, vol. 29, no. 1, pp. 226-230, 1997.
Crossref
[15]
C. Dominguez, R. Boelens, and A. M. J. J. Bonvin, HADDOCK: A protein-protein docking approach based on biochemical or biophysical information, J. Am. Chem. Soc., vol. 125, no. 7, pp. 1731-1737, 2003.
Crossref Google Scholar
[16]
D. W. Ritchie and G. J. L. Kemp, Protein docking using spherical polar Fourier correlations, Proteins, vol. 39, no. 2, pp. 178-194, 2000.
Crossref
[17]
M. Zacharias, Protein-protein docking with a reduced protein model accounting for side-chain flexibility, Protein Sci., vol. 12, no. 6, pp. 1271-1282, 2003.
Crossref Google Scholar
[18]
M. Torchala, I. H. Moal, R. A. G. Chaleil, J. Fernandez-Recio, and P. A. Bates, SwarmDock: A server for flexible proteinprotein docking, Bioinformatics, vol. 29, no. 6, pp. 807-809, 2013.
Crossref Google Scholar
[19]
D. Kozakov, D. R. Hall, B. Xia, K. A. Porter, D. Padhorny, C. Yueh, D. Beglov, and S. Vajda, The ClusPro web server for protein-protein docking, Nat. Protoc., vol. 12, no. 2, pp. 255-278, 2017.
Crossref Google Scholar
[20]
T. M. Cheng, T. L. Blundell, and J. Fernandez-Recio, pyDock: Electrostatics and desolvation for effective scoring of rigid-body protein-protein docking, Proteins, vol. 68, no. 2, pp. 503-515, 2007.
Crossref Google Scholar
[21]
Y. M. Yan, D. Zhang, P. Zhou, B. T. Li, and S. Y. Huang, HDOCK: A web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy, Nucleic Acids Res., vol. 45, no. 1, pp. 365-373, 2017.
Crossref Google Scholar
[22]
Y. Yan, H. Tao, and S. Y. Huang, HSYMDOCK: A docking web server for predicting the structure of protein homo-oligomers with Cn or Dn symmetry, Nucleic Acids Res., vol. 46, no. 1, pp. 423-431, 2018.
Crossref Google Scholar
[23]
J. Janin, K. Henrick, J. Moult, L. T. Eyck, M. J. Sternberg, S. Vajda, I. Vakser, and S. J. Wodak, Critical assessment of predicted interactions, Proteins, vol. 52, no. 1, pp. 2-9, 2003.
Crossref Google Scholar
[24]
J. B. Jr. Dunbar, R. D. Smith, C. Y. Yang, P. M. Ung, K. W. Lexa, N. A. Khazanov, J. A. Stuckey, S. M. Wang, and H. A. Carlson, CSAR benchmark exercise of 2010: Selection of the protein-ligand complexes, J. Chem. Inf. Model., vol. 51, no. 9, pp. 2036-2046, 2011.
Crossref Google Scholar
[25]
S. Y. Huang and X. Q. Zou, A non-redundant structure dataset for benchmarking protein-RNA computational docking, J. Comput. Chem., vol. 34, no. 4, pp. 311-318, 2013.
Crossref Google Scholar
[26]
H. Hwang, T. Vreven, J. Janin, and Z. P. Weng, Protein-protein docking benchmark version 4.0, Proteins, vol. 78, no. 15, pp. 3111-3114, 2010.
Crossref Google Scholar
[27]
T. Vreven, I. H. Moal, A. Vangone, B. G. Pierce, P. L. Kastritis, M. Torchala, R. Chaleil, B. Jiménez-García, P. A. Bates, J. Fernandez-Recio, et al., Updates to the integrated protein-protein interaction benchmarks: Docking benchmark version 5 and affinity benchmark version 2, J. Mol. Biol., vol. 427, no. 19, pp. 3031-3041, 2015.
Crossref Google Scholar
[28]
S. Y. Liu, Y. Gao, and I. A. Vakser, DOCKGROUND protein-protein docking decoy set, Bioinformatics, vol. 24, no. 22, pp. 2634-2635, 2008.
Crossref Google Scholar
[29]
I. Anishchenko, P. J. Kundrotas, A. V. Tuzikov, and I. A. Vakser, Protein models docking benchmark 2, Proteins, vol. 83, no. 5, pp. 891-897, 2015.
Crossref Google Scholar
[30]
H. M. Berman, J. Westbrook, Z. K. Feng, G. Gilliland, T. N. Bhat, H. Weissig, I. N. Shindyalov, and P. E. Bourne, The protein data bank, Nucleic Acids Res., vol. 28, no. 1, pp. 235-242, 2000.
Crossref Google Scholar
[31]
A. G. Murzin, S. E. Brenner, T. Hubbard, and C. Chothia, SCOP: A structural classification of proteins database for the investigation of sequences and structures, J. Mol. Biol., vol. 247, no. 4, pp. 536-540, 1995.
Crossref Google Scholar
[32]
L. Lo Conte, S. E. Brenner, T. J. P. Hubbard, C. Chothia, and A. G. Murzin, SCOP database in 2002: Refinements accommodate structural genomics, Nucleic Acids Res., vol. 30, no. 1, pp. 264-267, 2002.
Crossref Google Scholar
[33]
C. Camacho, G. Coulouris, V. Avagyan, N. Ma, J. Papadopoulos, K. Bealer, and T. L. Madden, BLAST+: Architecture and applications, BMC Bioinformatics, vol. 10, p. 421, 2009.
Crossref Google Scholar
[34]
E. F. Pettersen, T. D. Goddard, C. C. Huang, G. S. Couch, D. M. Greenblatt, E. C. Meng, and T. E. Ferrin, UCSF Chimera—A visualization system for exploratory research and analysis, J. Comput. Chem., vol. 25, no. 13, pp. 1605-1612, 2004.
Crossref Google Scholar
[35]
Y. Zhang and J. Skolnick, Scoring function for automated assessment of protein structure template quality, Proteins, vol. 57, no. 4, pp. 702-710, 2004.
Crossref Google Scholar
[36]
Y. M. Yan and S. Y. Huang, RRDB: A comprehensive and non-redundant benchmark for RNA-RNA docking and scoring, Bioinformatics, vol. 34, no. 3, pp. 453-458, 2018.
Crossref Google Scholar
[37]
R. Méndez, R. Leplae, M. F. Lensink, and S. J. Wodak, Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures, Proteins, vol. 60, no. 2, pp. 150-169, 2005.
Crossref Google Scholar
[38]
M. F. Lensink, R. Méndez, and S. J. Wodak, Docking and scoring protein complexes: CAPRI 3rd edition, Proteins, vol. 69, no. 4, pp. 704-718, 2007.
Crossref Google Scholar
Big Data Mining and Analytics
Volume 2 Issue 2,
June 2019
Pages 92-99
DOI: 10.26599/BDMA.2018.9020035
Cite this article:
Yan Y, Huang S-Y. A Non-Redundant Benchmark for Symmetric Protein Docking. Big Data Mining and Analytics, 2019, 2(2): 92-99. https://doi.org/10.26599/BDMA.2018.9020035

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Received: 14 July 2018
Accepted: 10 October 2018
Published: 14 May 2019
© The author(s) 2019
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