Abstract
The HDOCK server (http://hdock.phys.hust.edu.cn/) is a highly integrated suite of homology search, template-based modeling, structure prediction, macromolecular docking, biological information incorporation and job management for robust and fast protein–protein docking. With input information for receptor and ligand molecules (either amino acid sequences or Protein Data Bank structures), the server automatically predicts their interaction through a hybrid algorithm of template-based and template-free docking. The HDOCK server distinguishes itself from similar docking servers in its ability to support amino acid sequences as input and a hybrid docking strategy in which experimental information about the protein–protein binding site and small-angle X-ray scattering can be incorporated during the docking and post-docking processes. Moreover, HDOCK also supports protein–RNA/DNA docking with an intrinsic scoring function. The server delivers both template- and docking-based binding models of two molecules and allows for download and interactive visualization. The HDOCK server is user friendly and has processed >30,000 docking jobs since its official release in 2017. The server can normally complete a docking job within 30 min.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
The raw data and example files can be downloaded on our HDOCK server (http://hdock.phys.hust.edu.cn/) or are available from the corresponding author upon request.
Code availability
The HDOCK service is freely available for academic use at http://hdock.phys.hust.edu.cn/.
References
Berman, H. M. et al. The Protein Data Bank. Nucleic Acids Res. 28, 235–242 (2000).
Vajda, S., Hall, D. R. & Kozakov, D. Sampling and scoring: a marriage made in heaven. Proteins 81, 1874–1884 (2013).
Vakser, I. A. Protein-protein docking: from interaction to interactome. Biophys. J. 107, 1785–1793 (2014).
Huang, S. Y. Exploring the potential of global protein-protein docking: an overview and critical assessment of current programs for automatic ab initio docking. Drug Discov. Today 20, 969–977 (2015).
Huang, S. Y. Search strategies and evaluation in protein-protein docking: principles, advances and challenges. Drug Discov. Today 19, 1081–1096 (2014).
Wodak, S. J. & Janin, J. Computer analysis of protein-protein interaction. J. Mol. Biol. 124, 323–342 (1978).
Katchalski-Katzir, E. et al. Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques. Proc. Natl Acad. Sci. USA 89, 2195–2199 (1992).
Gabb, H. A., Jackson, R. M. & Sternberg, M. J. E. Modelling protein docking using shape complementarity, electrostatics and biochemical information. J. Mol. Biol. 272, 106–120 (1997).
Vakser, I. A. Evaluation of GRAMM low-resolution docking methodology on the hemagglutinin-antibody complex. Proteins (Suppl 1), 226–230 (1997).
Dominguez, C., Boelens, R. & Bonvin, A. M. J. J. HADDOCK: a protein-protein docking approach based on biochemical or biophysical information. J. Am. Chem. Soc. 125, 1731–1737 (2003).
De Vries, S. J., van Dijk, M. & Bonvin, A. M. J. J. The HADDOCK web server for data-driven biomolecular docking. Nat. Protoc. 5, 883–897 (2010).
van Zundert, G. C. P. et al. The HADDOCK2.2 web server: user-friendly integrative modeling of biomolecular complexes. J. Mol. Biol. 428, 720–725 (2016).
Yu, J. C. et al. InterEvDock: a docking server to predict the structure of protein-protein interactions using evolutionary information. Nucleic Acids Res. 44, W542–W549 (2016).
Lensink, M. F., Nadzirin, N., Velankar, S. & Wodak, S. J. Modeling protein-protein, protein-peptide, and protein-oligosaccharide complexes: CAPRI 7th edition. Proteins 1–23 (2020).
Janin, J. et al. CAPRI: a Critical Assessment of PRedicted Interactions. Proteins 52, 2–9 (2003).
wwPDB consortium. Protein Data Bank: the single global archive for 3D macromolecular structure data. Nucleic Acids Res. 47, D520–D528 (2019).
Hopf, T. A. et al. Sequence co-evolution gives 3D contacts and structures of protein complexes. Elife 3, e3430 (2014).
Zeng, H. et al. ComplexContact: a web server for inter-protein contact prediction using deep learning. Nucleic Acids Res. 46, W432–W437 (2018).
Huang, S. Y. & Zou, X. Q. An iterative knowledge-based scoring function for protein-protein recognition. Proteins 72, 557–579 (2008).
Lensink, M. F. et al. Blind prediction of homo- and hetero-protein complexes: the CASP13-CAPRI experiment. Proteins 87, 1200–1221 (2019).
Yan, Y. M., Wen, Z. Y., Wang, X. X. & Huang, S. Y. Addressing recent docking challenges: a hybrid strategy to integrate template-based and free protein-protein docking. Proteins 85, 497–512 (2017).
Yan, Y. & Huang, S.-Y. Protein-protein docking with improved shape complementarity. In Intelligent Computing Theories and Application (eds. Huang, D.-S., Bevilacqua, V.,Premaratne, P. & Gupta, P.) 600–605 (Springer International Publishing, Cham, Switzerland, 2018).
Huang, S. Y. & Zou, X. Q. MDockPP: a hierarchical approach for protein-protein docking and its application to CAPRI rounds 15-19. Proteins 78, 3096–3103 (2010).
Huang, S. Y. et al. Inclusion of the orientational entropic effect and low-resolution experimental information for protein-protein docking in Critical Assessment of PRedicted Interactions (CAPRI). Proteins 81, 2183–2191 (2013).
Lensink, M. F. et al. The challenge of modeling protein assemblies: the CASP12-CAPRI experiment. Proteins 86(Suppl 1), 257–273 (2018)..
Lensink, M. F. et al. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment. Proteins 84, 323–348 (2016).
Yan, Y., Zhang, D., Zhou, P., Li, B. & Huang, S.-Y. HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy. Nucleic Acids Res. 45, W365–W373 (2017).
Porter, K. A., Desta, I., Kozakov, D. & Vajda, S. What method to use for protein-protein docking? Curr. Opin. Struct. Biol. 55, 1–7 (2019).
Nithin, C., Ghosh, P. & Bujnicki, J. M. Bioinformatics tools and benchmarks for computational docking and 3D structure prediction of RNA-protein complexes. Genes (Basel) 9, E432 (2018).
Macalino, S. J. Y. et al. Evolution of in silico strategies for protein-protein interaction drug discovery. Molecules 23, E1963 (2018).
Dudenhoeffer, B. R., Schneider, H., Schweimer, K. & Knauer, S. H. SuhB is an integral part of the ribosomal antitermination complex and interacts with NusA. Nucleic Acids Res. 47, 6504–6518 (2019).
Fux, A., Korotkov, V. S., Schneider, M., Antes, I. & Sieber, S. A. Chemical cross-linking enables drafting ClpXP proximity maps and taking snapshots of in situ interaction networks. Cell Chem. Biol. 26, 48–59.e7 (2019).
Deep, A. et al. Structural, functional and biological insights into the role of Mycobacterium tuberculosis VapBC11 toxin-antitoxin system: targeting a tRNase to tackle mycobacterial adaptation. Nucleic Acids Res. 46, 11639–11655 (2018).
Kostareva, O. et al. Fab fragment of VHH-based antibody netakimab: crystal structure and modeling interaction with cytokine IL-17A. Crystals 9, 177 (2019).
Sharma, S., Ahmed, M. & Akhter, Y. The molecular link between tyrosol binding to tri6 transcriptional regulator and downregulation of trichothecene biosynthesis. Biochimie 160, 14–23 (2019).
Rose, A. S. et al. NGL viewer: web-based molecular graphics for large complexes. Bioinformatics 34, 3755–3758 (2018).
Huang, S. Y. & Zou, X. Q. A knowledge-based scoring function for protein-RNA interactions derived from a statistical mechanics-based iterative method. Nucleic Acids Res. 42, e55 (2014).
Kozakov, D. et al. The ClusPro web server for protein-protein docking. Nat. Protoc. 12, 255–278 (2017).
Comeau, S. R., Gatchell, D. W., Vajda, S. & Camacho, C. J. ClusPro: a fully automated algorithm for protein-protein docking. Nucleic Acids Res. 32, W96–W99 (2004).
Tovchigrechko, A. & Vakser, I. A. GRAMM-X public web server for protein-protein docking. Nucleic Acids Res. 34, W310–W314 (2006).
Lesk, V. I. & Sternberg, M. J. 3D-Garden: a system for modelling protein-protein complexes based on conformational refinement of ensembles generated with the marching cubes algorithm. Bioinformatics 24, 1137–1144 (2008).
Macindoe, G., Mavridis, L., Venkatraman, V., Devignes, M. D. & Ritchie, D. W. HexServer: an FFT-based protein docking server powered by graphics processors. Nucleic Acids Res. 38, W445–W449 (2010).
Torchala, M., Moal, I. H., Chaleil, R. A. G., Fernandez-Recio, J. & Bates, P. A. SwarmDock: a server for flexible protein-protein docking. Bioinformatics 29, 807–809 (2013).
Pierce, B. G. et al. ZDOCK server: interactive docking prediction of protein-protein complexes and symmetric multimers. Bioinformatics 30, 1771–1773 (2014).
Schneidman-Duhovny, D., Inbar, Y., Nussinov, R. & Wolfson, H. J. PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic Acids Res. 33, W363–W367 (2005).
Lyskov, S. & Gray, J. J. The RosettaDock server for local protein-protein docking. Nucleic Acids Res. 36, W233–W238 (2008).
de Vries, S. J., Schindler, C. E. M., de Beauchene, I. C. & Zacharias, M. A web interface for easy flexible protein-protein docking with ATTRACT. Biophys. J. 108, 462–465 (2015).
Cheng, T. M. K., Blundell, T. L. & Fernandez-Recio, J. pyDock: electrostatics and desolvation for effective scoring of rigid-body protein-protein docking. Proteins 68, 503–515 (2007).
Jimenez-Garcia, B., Pons, C. & Fernandez-Recio, J. pyDockWEB: a web server for rigid-body protein-protein docking using electrostatics and desolvation scoring. Bioinformatics 29, 1698–1699 (2013).
Jimenez-Garcia, B., Pons, C., Svergun, D. I., Bernado, P. & Fernandez-Recio, J. pyDockSAXS: protein-protein complex structure by SAXS and computational docking. Nucleic Acids Res. 43, W356–W361 (2015).
Tuszynska, I., Magnus, M., Jonak, K., Dawson, W. & Bujnicki, J. M. NPDock: a web server for protein-nucleic acid docking. Nucleic Acids Res. 43, W425–W430 (2015).
Remmert, M., Biegert, A., Hauser, A. & Soding, J. HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment. Nat. Methods 9, 173–175 (2012).
Larkin, M. A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007).
Marti-Renom, M. A. et al. Comparative protein structure modeling of genes and genomes. Annu. Rev. Biophys. Biomol. Struct. 29, 291–325 (2000).
Yan, Y. & Huang, S.-Y. Pushing the accuracy limit of shape complementarity for protein-protein docking. BMC Bioinformatics 20(Suppl 25), 696 (2019).
Venkatraman, V., Yang, Y. F. D., Sael, L. & Kihara, D. Protein-protein docking using region-based 3D Zernike descriptors. BMC Bioinformatics 10,, 47 (2009).
Xu, X. J. et al. Performance of MDockPP in CAPRI rounds 28-29 and 31-35 including the prediction of water-mediated interactions. Proteins 85, 424–434 (2017).
Baek, M., Park, T., Heo, L., Park, C. & Seok, C. GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure. Nucleic Acids Res. 45, W320–W324 (2017).
Weng, G. et al. HawkDock: a web server to predict and analyze the protein-protein complex based on computational docking and MM/GBSA. Nucleic Acids Res. 47, W322–W330 (2019).
Kryshtafovych, A., Schwede, T., Topf, M., Fidelis, K. & Moult, J. Critical assessment of methods of protein structure prediction (CASP)-Round XIII. Proteins 87, 1011–1020 (2019).
Baker, D. & Sali, A. Protein structure prediction and structural genomics. Science 294, 93–96 (2001).
Yan, Y. et al. Challenges and opportunities of automated protein-protein docking: HDOCK server versus human predictions in CAPRI Rounds 38-46. Proteins 1–15 (2020).
Roy, A., Kucukural, A. & Zhang, Y. I-TASSER: a unified platform for automated protein structure and function prediction. Nat. Protoc. 5, 725–738 (2010).
Yang, J. Y. et al. The I-TASSER Suite: protein structure and function prediction. Nat. Methods 12, 7–8 (2015).
Yang, J. Y. & Zhang, Y. I-TASSER server: new development for protein structure and function predictions. Nucleic Acids Res. 43, W174–W181 (2015).
Case, D. A. et al. The Amber biomolecular simulation programs. J. Comput. Chem. 26, 1668–1688 (2005).
Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997).
Yan, Y. M., Tao, H. Y. & Huang, S. Y. HSYMDOCK: a docking web server for predicting the structure of protein homo-oligomers with Cn or Dn symmetry. Nucleic Acids Res. 46, W423–W431 (2018).
Yan, Y. & Huang, S.-Y. CHDOCK: a hierarchical docking approach for modeling Cn symmetric homo-oligomeric complexes. Biophys. Rep. 5, 65–72 (2019).
Franke, D. et al. ATSAS 2.8: a comprehensive data analysis suite for small-angle scattering from macromolecular solutions. J. Appl. Crystallogr 50, 1212–1225 (2017).
Schneidman-Duhovny, D., Hammel, M. & Sali, A. Macromolecular docking restrained by a small angle X-ray scattering profile. J. Struct. Biol. 173, 461–471 (2011).
Schindler, C. E. M., de Vries, S. J., Sasse, A. & Zacharias, M. SAXS data alone can generate high-quality models of protein-protein complexes. Structure 24, 1387–1397 (2016).
Li, S. X., Olson, W. K. & Lu, X. J. Web 3DNA 2.0 for the analysis, visualization, and modeling of 3D nucleic acid structures. Nucleic Acids Res. 47, W26–W34 (2019).
Wang, J. & Xiao, Y. Using 3dRNA for RNA 3-D structure prediction and evaluation. Curr. Protoc. Bioinformatics 57, 5.9.1–5.9.12 (2017).
Zhao, Y. J. et al. Automated and fast building of three-dimensional RNA structures. Sci. Rep. 2, 734 (2012).
Liu, J. H., Wang, J. T. L., Hu, J. & Tian, B. A method for aligning RNA secondary structures and its application to RNA motif detection. BMC Bioinformatics 6, 89 (2005).
Lorenz, R. et al. ViennaRNA Package 2.0. Algorithms Mol. Biol. 6, 26 (2011).
Rother, M., Rother, K., Puton, T. & Bujnicki, J. M. ModeRNA: a tool for comparative modeling of RNA 3D structure. Nucleic Acids Res. 39, 4007–4022 (2011).
Wang, J., Zhao, Y. J., Zhu, C. Y. & Xiao, Y. 3dRNAscore: a distance and torsion angle dependent evaluation function of 3D RNA structures. Nucleic Acids Res. 43, e63 (2015).
Wang, J. et al. Optimization of RNA 3D structure prediction using evolutionary restraints of nucleotide-nucleotide interactions from direct coupling analysis. Nucleic Acids Res. 45, 6299–6309 (2017).
Wallner, B. & Elofsson, A. Can correct protein models be identified? Protein Sci. 12, 1073–1086 (2003).
Larsson, P., Skwark, M. J., Wallner, B. & Elofsson, A. Assessment of global and local model quality in CASP8 using Pcons and ProQ. Proteins 77(Suppl 9), 167–172 (2009).
Zhang, Y. & Skolnick, J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 33, 2302–2309 (2005).
Capriotti, E. & Marti-Renom, M. A. Quantifying the relationship between sequence and three-dimensional structure conservation in RNA. BMC Bioinformatics 11, 322 (2010).
Gardner, P. P., Wilm, A. & Washietl, S. A benchmark of multiple sequence alignment programs upon structural RNAs. Nucleic Acids Res. 33, 2433–2439 (2005).
Zhang, Y. & Skolnick, J. Scoring function for automated assessment of protein structure template quality. Proteins 57, 702–710 (2004).
Xu, J. & Zhang, Y. How significant is a protein structure similarity with TM-score = 0.5? Bioinformatics 26, 889–895 (2010).
Gong, S., Zhang, C. & Zhang, Y. RNA-align: quick and accurate alignment of RNA 3D structures based on size-independent TM-scoreRNA. Bioinformatics 35, 4459–4461 (2019).
Yoo, A. B., Jette, M. A. & Grondona, M. SLURM: Simple Linux Utility for Resource Management. In Job Scheduling Strategies for Parallel Processing. (eds. Feitelson, D., Rudolph, L. & Schwiegelshohn, U.) 44–60 (Springer, Berlin, Heidelberg, 2003).
Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).
Hwang, H., Vreven, T., Janin, J. & Weng, Z. P. Protein-protein docking benchmark version 4.0. Proteins 78, 3111–3114 (2010).
Kundrotas, P. J. et al. Dockground: a comprehensive data resource for modeling of protein complexes. Protein Sci. 27, 172–181 (2018).
Mendez, R., Leplae, R., De Maria, L. & Wodak, S. J. Assessment of blind predictions of protein-protein interactions: current status of docking methods. Proteins 52, 51–67 (2003).
Yan, Y. & Huang, S. A non-redundant benchmark for symmetric protein docking. Big Data Mining and Analytics 2, 92–99 (2019).
Nithin, C., Mukherjee, S. & Bahadur, R. P. A non-redundant protein-RNA docking benchmark version 2.0. Proteins 85, 256–267 (2017).
Huang, S. Y. & Zou, X. A nonredundant structure dataset for benchmarking protein-RNA computational docking. J. Comput. Chem. 34, 311–318 (2013).
Perez-Cano, L., Jimenez-Garcia, B. & Fernandez-Recio, J. A protein-RNA docking benchmark (II): extended set from experimental and homology modeling data. Proteins 80, 1872–1882 (2012).
van Dijk, M. & Bonvin, A. M. J. J. A protein-DNA docking benchmark. Nucleic Acids Res. 36, e88 (2008).
Valentini, E., Kikhney, A. G., Previtali, G., Jeffries, C. M. & Svergun, D. I. SASBDB, a repository for biological small-angle scattering data. Nucleic Acids Res. 43, D357–D363 (2014).
Pearson, W. R. & Lipman, D. J. Improved tools for biological sequence comparison. Proc. Natl Acad. Sci. USA 85, 2444–2448 (1988).
Miao, Z. et al. RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures. RNA 21, 1066–1084 (2015).
Miao, Z. et al. RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme. RNA 23, 655–672 (2017).
Miao, Z. C. & Westhof, E. RNA structure: advances and assessment of 3D structure prediction. Annu. Rev. Biophys. 46, 483–503 (2017).
Jeffries, C. M. et al. Preparing monodisperse macromolecular samples for successful biological small-angle X-ray and neutron-scattering experiments. Nat. Protoc. 11, 2122–2153 (2016).
Grant, T. D. et al. The accurate assessment of small-angle X-ray scattering data. Acta Crystallogr. D Biol. Crystallogr. 71, 45–56 (2015).
Bernado, P. & Svergun, D. I. Structural analysis of intrinsically disordered proteins by small-angle X-ray scattering. Mol. Biosyst. 8, 151–167 (2012).
Jacques, D. A. & Trewhella, J. Small-angle scattering for structural biology—expanding the frontier while avoiding the pitfalls. Protein Sci. 19, 642–657 (2010).
Putnam, C. D., Hammel, M., Hura, G. L. & Tainer, J. A. X-ray solution scattering (SAXS) combined with crystallography and computation: defining accurate macromolecular structures, conformations and assemblies in solution. Q. Rev. Biophys. 40, 191–285 (2007).
Acknowledgements
This work was supported by the National Natural Science Foundation of China (grant no. 31670724), the National Key Research and Development Program of China (grant nos. 2016YFC1305800 and 2016YFC1305805) and the startup grant of Huazhong University of Science and Technology.
Author information
Authors and Affiliations
Contributions
S.-Y.H. conceived and supervised the project. Y.Y., H.T., J.H. and S.-Y.H. designed and performed the experiments. Y.Y., H.T., J.H. and S.-Y.H. wrote the manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Related links
Key references using this protocol
Yan, Y. et al. Nucleic Acids Res. 45, W365–W373 (2017): https://doi.org/10.1093/nar/gkx407
Yan, Y. et al. Proteins 85, 497–512 (2017): https://doi.org/10.1002/prot.25234
Yan, Y. et al. Nucleic Acids Res. 46, W423–W431 (2018): https://doi.org/10.1093/nar/gky398
Yan, Y. and Huang, S.-Y. BMC Bioinformatics 20(Suppl 25), 696 (2019): https://doi.org/10.1186/s12859-019-3270-y
Integrated supplementary information
Supplementary Fig. 1 Template-free docking example.
The HDOCK results for template-free docking with target 1CGI, in which sequences were provided as inputs and the template-free docking option was checked.
Supplementary Fig. 2 Symmetric multimer docking example.
The HDOCK results for symmetric multimer docking with D2 target 1HCJ, in which sequences were provided for template-free docking.
Supplementary Fig. 3 SAXS-assisted docking example.
The HDOCK results for SAXS-assisted template-free docking with target 1CGI, in which sequences and SAXS data were provided.
Supplementary Fig. 4 Interaction restraint-guided docking example.
The HDOCK results for interaction restraint-guided template-free docking with target 1CGI, in which residue distance restraints and sequences were provided for docking.
Supplementary Fig. 5 Protein–RNA docking example.
The HDOCK results for template-based modeling and template-free docking with protein–RNA target 1C0A, in which individual structures were provided as inputs.
Supplementary information
Supplementary Information
Supplementary Figs. 1–5.
Rights and permissions
About this article
Cite this article
Yan, Y., Tao, H., He, J. et al. The HDOCK server for integrated protein–protein docking. Nat Protoc 15, 1829–1852 (2020). https://doi.org/10.1038/s41596-020-0312-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41596-020-0312-x