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Software Developed by the Donald Lab

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OSPREY 3.0

Our software is
Open-Source

Our software is
Free software

Dlab software:
OSPREY
DISCO
PIV
LibProtNMR
ConDIOs
RDC-PANDA
NASCA
POOL
Q5
CRANS

Software previously released by the Donald Lab:
Exact-2NH
MTC
NVR/HD/GD
Rage/Enrage

Osprey JCC Cover Article | Quick Start | Licensing and Legal Terms | Download | OspreyTube | Examples/Bibliography | Other Versions

Welcome to the website for the OSPREY (Open Source Protein REdesign for You) software.

OSPREY is free and open-source software, and is available on Github, where you can always find our latest updates. Please read the licensing and legal terms first! Please e-mail us if you have any questions.

The latest version of OSPREY is 3.2.101. It is significantly refactored compared to previous releases, and comes with a convenient Python interface, as well as several new algorithms and marked performance improvements including (but not limited to) GPU acceleration.

OSPREY is a suite of programs for computational structure-based protein design. OSPREY is developed in the lab of Prof. Bruce Donald at Duke University.

OSPREY is specifically designed to predict protein mutants that possess desired target properties (e.g., improved stability, switch of substrate specificity, etc.). OSPREY can also be used for predicting small-molecule drug inhibitors. Starting with version 2.0, OSPREY can now design protein-protein and protein-peptide interactions.

OSPREY incorporates several different algorithmic modules for structure-based protein design, including a number of powerful Dead-End Elimination algorithms and the ensemble-based K* algorithm for protein-ligand binding prediction. OSPREY allows the incorporation of continuous protein side-chain and continuous or discrete backbone flexibility, while maintaining provable guarantees with respect to the input model (input structure, rotamer library, energy function, and any backbone perturbations) for a given protein design problem.

To our knowledge, OSPREY is the only open-source, freely-available implementation of the DEE/A* algorithms. DEE/A* combines the provable Dead-End Elimination (DEE) algorithms with the A* search enumeration. OSPREY also includes many extensions and improvements to the DEE framework (e.g., minDEE, iMinDEE, K*, DACS, BD, BRDEE, DEEPer, EPIC, COMETS, BWM*, LUTE, BBK*, and CATS). These extensions improve efficiency and allow the modelling of molecular flexibility. OSPREY includes the K* (pronounced "K-star") module, which is a provably-good ε-approximation (epsilon-approximation) algorithm for computing binding constants (KD) over molecular ensembles of the bound and unbound states of a protein:ligand complex using minimized DEE/A* (namely, minDEE/A*/K*). See our papers for details.

Legal Terms, Citation Requirements and Software License

To use Osprey, please first read the following Citation Requirements. In short, users must cite Osprey in papers, patents, or presentations, and must use the name "Osprey" in the text thereof.

Beyond that, OSPREY is free software and can be redistributed and/or modified under the terms of version 2 of the GNU General Public License as published by the Free Software Foundation. OSPREY is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. Full licensing details, including citation requirements for the various different modules of the software, are found on our Github page. In particular, we require that everyone who publishes or presents results from OSPREY to mention the name OSPREY and (if they used OSPREY 3) to cite our paper introducing OSPREY 3.0, along with the papers for the specific modules or algorithms they used (see Github and/or below).

Examples and Bibliography

Selcted Examples and use-cases:

  1. Textbook
  2. Anti-infectives: Predicting resistance mutations (1)
  3. Anti-infectives: Predicting resistance mutations (2)
  4. Anti-virals: Here is a tutorial by Brian Cox, on Osprey-based prediction of influenza resistance mutations:
  5. Anti-neoplastics: T. Kaserer and J. Blagg. Osprey-based workflow predicts mutations likely to arise upon drug treatment in a particular cancer tumor type.
  6. Antibodies: Design of biologics
  7. Computational design of a tight binder to KRas, an "undruggable" cancer target, and redesign of the Ras:Raf protein:protein interface
  8. Osprey-based Analysis of Energy Landscapes
  9. GPU support, PPI design, Benchmarks, Advanced algorithms
  10. Tutorial on Protein Design
  11. Multi-state design and resistance mutations
Selected Empirical Designs that used OSPREY:
  1. Provable algorithms for ensemble-based computational protein design and the redesign of the KRas:RAF-kinase protein:protein interface (with A. Lowegard, M. Frenkel, J. Jou, A. Ojewole, and G. Holt). PLoS Computational Biology 2020; 16(6): e1007447. PMID: 32511232
  2. Toward Broad Spectrum DHFR inhibitors Targeting Trimethoprim Resistant Enzymes Identified in Clinical Isolates of Methicillin-Resistant Staphylococcus aureus. (with S. Reeve, D. Si, J. Krucinska, Y. Yan, K. Viswanathan, S. Wang, G. Holt, M. Frenkel, A. Ojewole, A. Estrada, S. Agabiti, J. Alverson, N. Gibson, N. Priestly, A. Wiemer, and D. Wright).
    ACS Infectious Diseases 2019; 5(11):1896-1906. .
    (doi: 10.1021/acsinfecdis.9b00222)
    Preprint on BioRχiv 648808; doi: https://doi.org/10.1101/648808
  3. Computational Analysis of Energy Landscapes Reveals Dynamic Features that Contribute to Binding of Inhibitors to CFTR-Associated Ligand (with G. Holt, J. Jou, N. Gill, A. Lowegard, J. Martin, and D. Madden). Jour. Physical Chemistry B. 2019; 123(49):10441-10455. PMID: 31697075
  4. T. Kaserer and J. Blagg. Combining Mutational Signatures, Clonal Fitness, and Drug Affinity to Define Drug-Specific Resistance Mutations in Cancer. Cell Chem Biol. 2018; 25(11):1359-1371.e2. doi: 10.1016/j.chembiol.2018.07.013.
  5. A systematic molecular and pharmacologic evaluation of AKT inhibitors reveals new insight into their biological activity. Kostaras E, Kaserer T, Lazaro G, Heuss SF, Hussain A, Casado P, Hayes A, Yandim C, Palaskas N, Yu Y, Schwartz B, Raynaud F, Chung YL, Cutillas PR, Vivanco I. Br J Cancer. 2020 May 22. doi: 10.1038/s41416-020-0889-4. Online ahead of print. PMID: 32439931
  6. Structure-Based Design of a Soluble Prefusion-Closed HIV-1 Env Trimer with Reduced CD4 Affinity and Improved Immunogenicity. Gwo-Yu Chuang, Hui Geng, Marie Pancera, Kai Xu, Cheng Cheng, Priyamvada Acharya, Michael Chambers, Aliaksandr Druz, Yaroslav Tsybovsky, Timothy G. Wanninger, Yongping Yang, Nicole A. Doria-Rose, Ivelin S. Georgiev, Jason Gorman, M. Gordon Joyce, Sijy O'Dell, Tongqing Zhou, Adrian B. McDermott, John R. Mascola, Peter D. Kwong Journal of Virology Apr 2017, 91 (10) e02268-16; DOI: 10.1128/JVI.02268-16
  7. S. Reeve, P. Gainza, K. Frey, I. Georgiev, B. R. Donald, and A. Anderson. Protein Design Algorithms Predict Viable Resistance to an Experimental Antifolate. Proceedings of the National Academy of Sciences, U.S.A. (PNAS). 2015; doi: 10.1073/pnas.1411548112
  8. R. Rudicell, Y. Kwon, S.Y. Ko, A. Pegu, M. Louder, I. Georgiev, X. Wu, J. Zhu, J. Boyington, X. Chen, W. Shi, Z. Yang, N. Doria-Rose, K. McKee, S. O'Dell, S. Schmidt, G.Y. Chuang, A. Druz, C. Soto, Y. Yang, B. Zhang, T. Zhou, J.P. Todd, K. Lloyd, J. Eudailey, K. Roberts, B. R. Donald, R. Bailer, J. Ledgerwood, NISC Comparative Sequencing Program, J. Mullikin, L. Shapiro, R. Koup, B. Graham, M. Nason, M. Connors, B. Haynes, S. Rao, M. Roederer, P. Kwong, J. Mascola, and G. Nabel. Enhanced potency of a broadly neutralizing HIV-1 antibody in vitro improves protection against lentiviral infection in vivo. Journal of Virology (2014) doi: 10.1128/JVI.02213-14
  9. Ivelin S. Georgiev, Rebecca S. Rudicell, Kevin O. Saunders, Wei Shi, Tatsiana Kirys, Krisha McKee, Sijy O'Dell, Gwo-Yu Chuang, Zhi-Yong Yang, Gilad Ofek, Mark Connors, John R. Mascola, Gary J. Nabel and Peter D. Kwong. Antibodies VRC01 and 10E8 Neutralize HIV-1 with High Breadth and Potency Even with Ig-Framework Regions Substantially Reverted to Germline. The Journal of Immunology (2014). doi: 10.4049/.jimmunol.1302515
  10. De novo design of a transmembrane Zn2+-transporting four-helix bundle. Joh NH, Wang T, Bhate MP, Acharya R, Wu Y, Grabe M, Hong M, Grigoryan G, DeGrado WF. Science. 2014 Dec 19;346(6216):1520-4. doi: 10.1126/science.1261172. PMID: 25525248.
  11. I. Georgiev, P. Acharya, S. Schmidt, Y. Li, D. Wycuff, G. Ofek, N. Doria-Rose, T. Luongo, Y, Yang, T. Zhou, B. R. Donald, J. Mascola, P. Kwong. Design of Epitope-Specific Probes for Sera Analysis and Antibody Isolation. Retrovirology 2012; 9(Suppl.2):P50.
  12. A critical analysis of computational protein design with sparse residue interaction graphs (with S. Jain, J. Jou, and I. Georgiev). PLoS Comput. Biol. 2017 Mar 30;13(3):e1005346. doi: 10.1371/journal.pcbi.1005346.
  13. Roberts KE, Cushing PR, Boisguerin P, Madden DR, Donald BR. Computational Design of a PDZ Domain Peptide Inhibitor that Rescues CFTR Activity. PLoS Comput Biol. 2012 Apr;8(4):e1002477. Epub 2012 Apr 19. PubMed PMID: 22532795; PubMed Central PMCID: PMC3330111.
  14. Frey KM, Georgiev I, Donald BR, Anderson AC. Predicting resistance mutations using protein design algorithms. Proc Natl Acad Sci U S A. 2010 Aug 3;107(31):13707-12. Epub 2010 Jul 19. PubMed PMID: 20643959; PubMed Central PMCID: PMC2922245.
  15. Chen CY, Georgiev I, Anderson AC, Donald BR. Computational structure-based redesign of enzyme activity. Proc Natl Acad Sci U S A. 2009 Mar 10;106(10):3764-9. Epub 2009 Feb 19. PubMed PMID: 19228942; PubMed Central PMCID: PMC2645347.
  16. Gorczynski MJ, Grembecka J, Zhou Y, Kong Y, Roudaia L, Douvas MG, Newman M, Bielnicka I, Baber G, Corpora T, Shi J, Sridharan M, Lilien R, Donald BR, Speck NA, Brown ML, Bushweller JH. Allosteric inhibition of the protein-protein interaction between the leukemia-associated proteins Runx1 and CBFbeta. Chem Biol. 2007 Oct;14(10):1186-97. PubMed PMID: 17961830.
  17. Stevens BW, Lilien RH, Georgiev I, Donald BR, Anderson AC. Redesigning the PheA domain of Gramicidin Synthetase leads to a new understanding of the enzyme's mechanism and selectivity. Biochemistry. 2006 Dec 26;45(51):15495-504. Epub 2006 Dec 19. PubMed PMID: 17176071.
Selected Crystal Stuctures That Confirmed OSPREY Designs:
  1. See structures here.

    Search PDB (NCBI) for all our protein structures (NMR, X-ray)

The Book, and Selected Papers on OSPREY Algorithms, Methodology, and Validation:
    The textbook describes the algorithms in detail: Algorithms in Structural Molecular Biology. MIT Press (2011).
    Order from Amazon.




  1. The most recent algorithms and software papers are here. (MARK*, CATS, BBK*, EWAK*, FRIES, PPI predictions, etc.)
  2. Provable algorithms for ensemble-based computational protein design and the redesign of the KRas:RAF-kinase protein:protein interface (with A. Lowegard, M. Frenkel, J. Jou, A. Ojewole, and G. Holt). PLoS Computational Biology 2020; 16(6): e1007447. PMID: 32511232
  3. M. Hallen, J. Martin, et al.
    OSPREY 3.0: Open-Source Protein Redesign for You, with Powerful New Features.
    Journal of Computational Chemistry 2018; 39(30): 2494-2507 Cover article.
    Available here:
  4. M. Hallen, J. Martin, A. Ojewole, J. Jou, A. Lowegard, M. Frenkel, P. Gainza, H. Nisonoff, A. Mukund, S. Wang, G. Holt, D. Zhou, E. Dowd, B. R. Donald*. OSPREY 3.0: Open-Source Protein Redesign for You, with Powerful New Features. bioRxiv 306324 (Cold Spring Harbor); doi: https://doi.org/10.1101/306324. URL: https://www.biorxiv.org/content/early/2018/04/23/306324.
  5. Hallen, Mark A. and Bruce R. Donald. "CATS (Coordinates of Atoms by Taylor Series): Protein design with backbone flexibility in all locally feasible directions." Bioinformatics 2017;33(14): i5-i12.
  6. Ojewole, Adegoke A., Jonathan D. Jou, Vance G. Fowler, and Bruce R. Donald. BBK* (Branch and Bound over K*): A Provable and Efficient Ensemble-Based Algorithm to Optimize Stability and Binding Affinity over Large Sequence Spaces. Proceedings of the Annual International Conference on Research in Computational Molecular Biology (RECOMB), Hong Kong. (May 3-7, 2017). In: Research in Computational Molecular Biology, Lecture Notes in Computer Science (LNCS), Springer-Verlag (Berlin) vol. 10229, pp. 157-172.
  7. Hallen, Mark A., Jonathan D. Jou, and Bruce R. Donald. "LUTE (Local Unpruned Tuple Expansion): Accurate continuously flexible protein design with general energy functions and rigid-rotamer-like efficiency." Research in Computational Molecular Biology (RECOMB) 2016 proceedings, volume 9649 of Lecture Notes in Computer Science, pp. 122-136. Springer International Publishing, 2016.
  8. Jou, Jonathan D., Swati Jain, Ivelin S. Georgiev, and Bruce R. Donald. BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design. Proceedings of the Annual International Conference on Research in Computational Molecular Biology (RECOMB), Warsaw, April 12-15, 2015. In Research in Computational Molecular Biology Lecture Notes in Computer Science, Springer-Verlag (Berlin), Volume 9029, 2015, pp 154-166
  9. Hallen, Mark A., Pablo Gainza, and Bruce R. Donald. "Compact representation of continuous energy surfaces for more efficient protein design." Journal of Chemical Theory and Computation 2015;11(5):2292-2306.
  10. Hallen, Mark A. and Bruce R. Donald. "COMETS (Constrained Optimization of Multistate Energies by Tree Search): A provable and efficient algorithm to optimize binding affinity and specificity with respect to sequence." Research in Computational Molecular Biology (RECOMB) 2015 proceedings, volume 9029 of Lecture Notes in Computer Science, pp. 122-135. Springer International Publishing, 2015.
  11. P. Gainza, K. Roberts, I. Georgiev, R. Lilien, D. Keedy, C.-Y. Chen, F. Reza, A Anderson, D. Richardson, J. Richardson, and B. R. Donald. OSPREY: Protein design with ensembles, flexibility, and provable algorithms. Methods in Enzymology, Vol. 523, Methods in Protein Design, pp87-107. (2013). ISBN: 9780123942920.
    http://store.elsevier.com/Methods-in-Protein-Design/isbn-9780123942920/
  12. Structure-guided deimmunization of therapeutic proteins. Parker AS, Choi Y, Griswold KE, Bailey-Kellogg C. J Comput Biol. 2013 Feb;20(2):152-65. doi: 10.1089/cmb.2012.0251.
  13. Hallen MA, Keedy DA, Donald BR. Dead-End Elimination with Perturbations (DEEPer): A Provable Protein Design Algorithm with Continuous Sidechain and Backbone Flexibility. Proteins. 2012, in press. Epub 2012 Jul 21. PubMed PMID: 22821798.
  14. Y. Zhou, W. Xu, B. R. Donald, and J. (Michael) Zeng. An efficient parallel algorithm for accelerating computational protein design. Bioinformatics. 2014 Jun 15;30(12):i255-i263. Proceedings of ISMB, Boston, MA. doi: 10.1093/bioinformatics/btu264.
  15. Roberts KE, Cushing PR, Boisguerin P, Madden DR, Donald BR. Computational Design of a PDZ Domain Peptide Inhibitor that Rescues CFTR Activity. PLoS Comput Biol. 2012 Apr;8(4):e1002477. Epub 2012 Apr 19. PubMed PMID: 22532795; PubMed Central PMCID: PMC3330111.
  16. Gainza P, Roberts KE, Donald BR. Protein design using continuous rotamers. PLoS Comput Biol. 2012 Jan;8(1):e1002335. Epub 2012 Jan 12. PubMed PMID: 22279426; PubMed Central PMCID: PMC3257257.
  17. Frey KM, Georgiev I, Donald BR, Anderson AC. Predicting resistance mutations using protein design algorithms. Proc Natl Acad Sci U S A. 2010 Aug 3;107(31):13707-12. Epub 2010 Jul 19. PubMed PMID: 20643959; PubMed Central PMCID: PMC2922245.
  18. Chen CY, Georgiev I, Anderson AC, Donald BR. Computational structure-based redesign of enzyme activity. Proc Natl Acad Sci U S A. 2009 Mar 10;106(10):3764-9. Epub 2009 Feb 19. PubMed PMID: 19228942; PubMed Central PMCID: PMC2645347.
  19. Georgiev I, Keedy D, Richardson JS, Richardson DC, Donald BR. Algorithm for backrub motions in protein design. Bioinformatics. 2008 Jul 1;24(13):i196-204. PubMed PMID: 18586714; PubMed Central PMCID: PMC2718647.
  20. Georgiev I, Donald BR. Dead-end elimination with backbone flexibility. Bioinformatics. 2007 Jul 1;23(13):i185-94. PubMed PMID: 17646295.
  21. Georgiev I, Lilien RH, Donald BR. The minimized dead-end elimination criterion and its application to protein redesign in a hybrid scoring and search algorithm for computing partition functions over molecular ensembles. J Comput Chem. 2008 Jul 30;29(10):1527-42. PubMed PMID: 18293294; PubMed Central PMCID: PMC3263346.
  22. Lilien RH, Stevens BW, Anderson AC, Donald BR. A novel ensemble-based scoring and search algorithm for protein redesign and its application to modify the substrate specificity of the Gramicidin Synthetase A phenylalanine adenylation enzyme. J Comput Biol. 2005 Jul-Aug;12(6):740-61. PubMed PMID: 16108714.
  23. Georgiev I, Lilien RH, Donald BR. Improved Pruning algorithms and Divide-and-Conquer strategies for Dead-End Elimination, with application to protein design. Bioinformatics. 2006 Jul 15;22(14):e174-83. PubMed PMID: 16873469.