PIPER: An FFT‐based protein docking program with pairwise potentials
Open accessAbstract
The Fast Fourier Transform (FFT) correlation approach to protein–protein docking can evaluate the energies of billions of docked conformations on a grid if the energy is described in the form of a correlation function. Here, this restriction is removed, and the approach is efficiently used with pairwise interaction potentials that substantially improve the docking results. The basic idea is approximating the interaction matrix by its eigenvectors corresponding to the few dominant eigenvalues, resulting in an energy expression written as the sum of a few correlation functions, and solving the problem by repeated FFT calculations. In addition to describing how the method is implemented, we present a novel class of structure‐based pairwise intermolecular potentials. The DARS (Decoys As the Reference State) potentials are extracted from structures of protein–protein complexes and use large sets of docked conformations as decoys to derive atom pair distributions in the reference state. The current version of the DARS potential works well for enzyme–inhibitor complexes. With the new FFT‐based program, DARS provides much better docking results than the earlier approaches, in many cases generating 50% more near‐native docked conformations. Although the potential is far from optimal for antibody–antigen pairs, the results are still slightly better than those given by an earlier FFT method. The docking program PIPER is freely available for noncommercial applications. Proteins 2006. © 2006 Wiley‐Liss, Inc.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Conventional approaches for predicting protein complex structures include a docking component, which is limited by force-field accuracy and completeness of conformational space sampling.
“conventional approaches for predicting the structure of protein complexes include a docking component8–11, which is limited by force-field accuracy and the completeness of conformational space sampling.”
From AF2Complex predicts direct physical interactions in multimeric proteins with deep learning (2022) · cites this paper as [9]
Cites
Principles of protein-protein interactions
Jones, S., & Thornton, J. M. (1996) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.93.1.13 · Cited by 2,684 · see citing works
The atomic structure of protein-protein recognition sites 1 1Edited by A. R. Fersht
Conte, L. L., Chothia, C., & Janin, J. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.2439 · Cited by 1,967 · see citing works
Miyazawa, S., & Jernigan, R. L. (1985) · Macromolecules · doi:10.1021/ma00145a039 · Cited by 1,588 · see citing works
ZDOCK: An initial‐stage protein‐docking algorithm
Chen, R., Li, L., & Weng, Z. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10389 · Cited by 1,393 · see citing works
Principles of docking: An overview of search algorithms and a guide to scoring functions
Halperin, I., Ma, B., Wolfson, H., & Nussinov, R. (2002) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10115 · Cited by 1,294 · see citing works
Miyazawa, S., & Jernigan, R. L. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0114 · Cited by 1,231 · see citing works
Katchalski-Katzir, E., Shariv, I., Eisenstein, M., Friesem, A., Aflalo, C., & Vakser, I. (1992) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.89.6.2195 · Cited by 1,143 · see citing works
Gray, J. J., Moughon, S. E., Wang, C., Schueler‐Furman, O., Kuhlman, B. A., Rohl, C. A., & Baker, D. A. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(03)00670-3 · Cited by 1,130 · see citing works
Zhou, H., & Zhou, Y. (2002) · Protein Science · doi:10.1110/ps.0217002 · Cited by 902 · see citing works
ClusPro: an automated docking and discrimination method for the prediction of protein complexes
Comeau, S. R., GATCHELL, D. W., Vajda, S., & Camacho, C. J. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg371 · Cited by 857 · see citing works
Self-citationGabb, H. A., Jackson, R. M., & Sternberg, M. J. E. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1203 · Cited by 820 · see citing works
Cuff, J. A., & Barton, G. J. (2000) · Proteins Structure Function and Bioinformatics · doi:10.1002/1097-0134(20000815)40:3 · Cited by 768 · see citing works
Analyzing protein circular dichroism spectra for accurate secondary structures
Johnson, W. C. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990515)35:3 · Cited by 639 · see citing works
Dissecting protein–protein recognition sites
Chakrabarti, P., & Janin, J. (2002) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10085 · Cited by 571 · see citing works
Determination of atomic desolvation energies from the structures of crystallized proteins
Zhang, C., Vasmatzis, G., Cornette, J. L., & DeLisi, C. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0859 · Cited by 536 · see citing works
Prediction of protein–protein interactions by docking methods
Smith, G. R., & Sternberg, M. J. E. (2002) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(02)00285-3 · Cited by 446 · see citing works
Assessment of blind predictions of protein–protein interactions: Current status of docking methods
Mendez, R., Leplae, R., Maria, L. D., & Wodak, S. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10393 · Cited by 438 · see citing works
Docking unbound proteins using shape complementarity, desolvation, and electrostatics
Chen, R., & Weng, Z. (2002) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10092 · Cited by 375 · see citing works
A protein–protein docking benchmark
Chen, R., Mintseris, J., Janin, J., & Weng, Z. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10390 · Cited by 345 · see citing works
Assessment of CAPRI predictions in rounds 3–5 shows progress in docking procedures
Méndez, R., Leplae, R., Lensink, M. F., & Wodak, S. J. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20551 · Cited by 340 · see citing works
RDOCK: Refinement of rigid‐body protein docking predictions
Li, L., Chen, R., & Weng, Z. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10460 · Cited by 331 · see citing works
Protein docking using continuum electrostatics and geometric fit
Mandell, J. G., Roberts, V. A., Pique, M. E., Kotlovyi, V., Mitchell, J. C., Nelson, E. D., Tsigelny, I. F., & Eyck, L. F. T. (2001) · Protein Engineering Design and Selection · doi:10.1093/protein/14.2.105 · Cited by 297 · see citing works
A distance‐dependent atomic knowledge‐based potential for improved protein structure selection
Lu, H. J., & Skolnick, J. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.1087 · Cited by 290 · see citing works
Protein–protein docking benchmark 2.0: An update
Mintseris, J., Wiehe, K. J., Pierce, B. G., Anderson, R., Chen, R., Janin, J., & Weng, Z. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20560 · Cited by 278 · see citing works
Skolnick, J., Godzik, A., Jaroszewski, L., & Koliński, A. (1997) · Protein Science · doi:10.1002/pro.5560060317 · Cited by 200 · see citing works
Soft protein–protein docking in internal coordinates
Fernández‐Recio, J., Totrov, M. M., & Abagyan, R. A. (2002) · Protein Science · doi:10.1110/ps.19202 · Cited by 197 · see citing works
Liu, S., Zhang, C., Zhou, H., & Zhou, Y. (2004) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20019 · Cited by 193 · see citing works
Hydrophobic docking: A proposed enhancement to molecular recognition techniques
Vakser, I. A., & Aflalo, C. (1994) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340200405 · Cited by 190 · see citing works
Development of unified statistical potentials describing protein-protein interactions.
Lu, H., Lu, L., & Skolnick, J. (2003) · Biophysical Journal · doi:10.1016/s0006-3495(03)74997-2 · Cited by 144 · see citing works
Optimal Clustering for Detecting Near-Native Conformations in Protein Docking
Kozakov, D., Clodfelter, K. H., Vajda, S., et al. (2005) · Biophysical Journal · doi:10.1529/biophysj.104.058768 · Cited by 131 · see citing works
Self-citationProtein–protein association kinetics and protein docking
Camacho, C. J., & Vajda, S. (2002) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(02)00286-5 · Cited by 115 · see citing works
Self-citationProtein–protein docking: is the glass half-full or half-empty?
Vajda, S., & Camacho, C. J. (2004) · Trends in biotechnology · doi:10.1016/j.tibtech.2004.01.006 · Cited by 109 · see citing works
Self-citationKeskin, Ö., Bahar, İ., Jernigan, R. L., et al. (1998) · Protein Science · doi:10.1002/pro.5560071211 · Cited by 93 · see citing works
Jackson, R. M. (1999) · Protein Science · doi:10.1110/ps.8.3.603 · Cited by 87 · see citing works
Inferring ideal amino acid interaction forms from statistical protein contact potentials
Pokarowski, P., Kloczkowski, A., Jernigan, R. L., et al. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20380 · Cited by 78 · see citing works
Are membrane proteins ?inside-out? proteins?
Stevens, T. J., & Arkin, I. T. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990701)36:1 · Cited by 77 · see citing works
Tsunogae, Y., Tanaka, I., Yamane, T., et al. (1986) · The Journal of Biochemistry · doi:10.1093/oxfordjournals.jbchem.a121872 · Cited by 72 · see citing works
Carugo, O., & Argos, P. (1998) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19980501)31:2 · Cited by 72 · see citing works
Consistency in structural energetics of protein folding and peptide recognition
Zhang, C., Cornette, J. L., & DeLisi, C. (1997) · Protein Science · doi:10.1002/pro.5560060512 · Cited by 49 · see citing works
Knowledge-based potentials for protein folding: what can we learn from known protein structures?
Godzik, A. (1996) · Structure · doi:10.1016/s0969-2126(96)00041-x · Cited by 45 · see citing works
Incremental Grid Sampling Strategies in Robotics
Lindemann, S. R., Yershova, A., & LaValle, S. M. (2005) · Springer tracts in advanced robotics · doi:10.1007/10991541_22 · Cited by 40 · see citing works
Combination of scoring functions improves discrimination in protein–protein docking
Murphy, J. R., GATCHELL, D. W., Prasad, J. C., & Vajda, S. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10473 · Cited by 39 · see citing works
Self-citationHusimi, K., Kitano, Y., & Nishiyama, T. (1958) · Fortschritte der Physik · doi:10.1002/prop.19580060102 · Cited by 27 · see citing works
Villoutreix, B. O., Dahlb�ck, B., Borgel, D., Gandrille, S., & Muller, Y. A. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/1097-0134(20010501)43:2 · Cited by 26 · see citing works
A docking analysis of the statistical physics of protein–protein recognition
Bernauer, J., Anne Poupon, B., Azé, J., & Janin, J. (2005) · Physical Biology · doi:10.1088/1478-3975/2/2/s02 · Cited by 19 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Software for molecular docking: a review
Pagadala, N. S., Syed, K., & Tuszynski, J. (2017) · Biophysical Reviews · doi:10.1007/s12551-016-0247-1 · Cited by 1,522 · see citing works
Harnessing protein folding neural networks for peptide–protein docking
Tsaban, T., Varga, J. K., Avraham, O., Ben-Aharon, Z., Khramushin, A., & Schueler-Furman, O. (2022) · Nature Communications · doi:10.1038/s41467-021-27838-9 · Cited by 1,205 · see citing works
Macromolecular modeling and design in Rosetta: recent methods and frameworks
Leman, J. K., Weitzner, B. D., Lewis, S. M., Adolf-Bryfogle, J., Alam, N., Alford, R. F., Aprahamian, M., Baker, D., Barlow, K. A., Barth, P., et al. (2020) · Nature Methods · doi:10.1038/s41592-020-0848-2 · Cited by 888 · see citing works
Moitessier, N., Englebienne, P., Lee, D., Lawandi, J., & Corbeil, C. R. (2008) · British Journal of Pharmacology · doi:10.1038/sj.bjp.0707515 · Cited by 514 · see citing works
Benchmarking <scp>AlphaFold</scp> for protein complex modeling reveals accuracy determinants
Yin, R., Feng, B. Y., Varshney, A., & Pierce, B. G. (2022) · Protein Science · doi:10.1002/pro.4379 · Cited by 335 · see citing works
Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants
Yin, R., Feng, B. Y., Varshney, A., & Pierce, B. G. (2021) · doi:10.1101/2021.10.23.465575 · Cited by 335 · see citing works
Protein-Protein Docking: From Interaction to Interactome
Vakser, I. A. (2014) · Biophysical Journal · doi:10.1016/j.bpj.2014.08.033 · Cited by 318 · see citing works
Protein-peptide docking: opportunities and challenges
Ciemny, M., Kurcinski, M., Kamel, K., Kolinski, A., Alam, N., Schueler-Furman, O., & Kmiecik, S. (2018) · Drug Discovery Today · doi:10.1016/j.drudis.2018.05.006 · Cited by 306 · see citing works
AF2Complex predicts direct physical interactions in multimeric proteins with deep learning
Gao, M., Nakajima An, D., Parks, J. M., & Skolnick, J. (2022) · Nature Communications · doi:10.1038/s41467-022-29394-2 · Cited by 252 · see citing works
Integrating diverse data for structure determination of macromolecular assemblies
Alber, F., Förster, F., Korkin, D., Topf, M., & Sali, A. (2008) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.77.060407.135530 · Cited by 206 · see citing works
Templates are available to model nearly all complexes of structurally characterized proteins
Kundrotas, P. J., Zhu, Z., Janin, J., & Vakser, I. A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1200678109 · Cited by 179 · see citing works
β-amyloid redirects norepinephrine signaling to activate the pathogenic GSK3β/tau cascade
Zhang, F., Gannon, M., Chen, Y., Yan, S., Zhang, S., Feng, W., Tao, J., Sha, B., Liu, Z., Saito, T., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay6931 · Cited by 133 · see citing works
Mapping Monomeric Threading to Protein–Protein Structure Prediction
Guerler, A., Govindarajoo, B., & Zhang, Y. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci300579r · Cited by 73 · see citing works
Improved Docking of Protein Models by a Combination of Alphafold2 and ClusPro
Ghani, U., Desta, I., Jindal, A., Khan, O., Jones, G., Hashemi, N., Kotelnikov, S., Padhorny, D., Vajda, S., & Kozakov, D. (2021) · doi:10.1101/2021.09.07.459290 · Cited by 68 · see citing works
Self-citationClusPro-DC: dimer classification by the Cluspro server for protein–protein docking
Yueh, C., Hall, D. R., Xia, B., Padhorny, D., Kozakov, D., & Vajda, S. (2017) · Journal of Molecular Biology · doi:10.1016/j.jmb.2016.10.019 · Cited by 53 · see citing works
Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence
Duran-Frigola, M., Cigler, M., & Winter, G. E. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.2c11098 · Cited by 50 · see citing works
Nithin, C., Ghosh, P., & Bujnicki, J. M. (2018) · Genes · doi:10.3390/genes9090432 · Cited by 48 · see citing works
New benchmark metrics for protein‐protein docking methods
Gao, M., & Skolnick, J. (2011) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.22987 · Cited by 42 · see citing works
Memdock: an α-helical membrane protein docking algorithm
Hurwitz, N., Schneidman-Duhovny, D., & Wolfson, H. J. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw184 · Cited by 40 · see citing works
Bohnuud, T., Kozakov, D., & Vajda, S. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003872 · Cited by 27 · see citing works
Self-citationAssessing the binding properties of <scp>CASP14</scp> targets and models
Egbert, M., Ghani, U., Ashizawa, R., Kotelnikov, S., Nguyen, T., Desta, I., Hashemi, N., Padhorny, D., Kozakov, D., & Vajda, S. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26209 · Cited by 10 · see citing works
Self-citationTargeting transcription factors through an IMiD independent zinc finger domain
Liu, B. H., Liu, M., Radhakrishnan, S., Dai, M.-Y., Jaladanki, C. K., Gao, C., Tang, J. P., Kumari, K., Go, M. L., Vu, K. A. L., et al. (2025) · EMBO Molecular Medicine · doi:10.1038/s44321-025-00241-3 · Cited by 8 · see citing works
“The ZFC2-4 of SALL4A and ZFC4 of SALL4B models were docked to CUL4A using Piper (Kozakov et al, 2006).”
- Authors
- Kozakov, D., Brenke, R., Comeau, S. R., & Vajda, S.
- Affiliations
- Boston University (US)
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2006-08-24
- Volume
- 65
- Issue
- 2
- Pages
- 392-406
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2171249995
- Cited by
- 865
- References
- 45
- Citations by year
- 2026: 30 · 2025: 46 · 2024: 53 · 2023: 50 · 2022: 74 · 2021: 53 · 2020: 56 · 2019: 56 · 2018: 57 · 2017: 59 · 2016: 65 · 2015: 52 · 2014: 57 · 2013: 44 · 2012: 38
- FWCI
- 4.08
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Boston Scientific Corporation
- National Institutes of Health (4r01gm061867-15)
- National Institute of General Medical Sciences (GM61867)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- protein-protein docking, Piper, pairwise interaction potential, eigenvalue approximation, enzyme-inhibitor complex, protein-protein complex
- MeSH terms
- Antibodies, Antigens, Enzyme Inhibitors, Fourier Analysis, Models, Biological, Protein Binding, Proteins, Time Factors, Computational Biology, Static Electricity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
