Abstract
Therapeutic proteins continue to yield revolutionary new treatments for a growing spectrum of human disease, but the development of these powerful drugs requires solving a unique set of challenges. For instance, it is increasingly apparent that mitigating potential anti-therapeutic immune responses, driven by molecular recognition of a therapeutic protein’s peptide fragments, may be best accomplished early in the drug development process. One may eliminate immunogenic peptide fragments by mutating the cognate amino acid sequences, but deimmunizing mutations are constrained by the need for a folded, stable, and functional protein structure. We develop a novel approach, called EpiSweep, that simultaneously optimizes both concerns. Our algorithm identifies sets of mutations making Pareto optimal trade-offs between structure and immunogenicity, embodied by a molecular mechanics energy function and a T-cell epitope predictor, respectively. EpiSweep integrates structure-based protein design, sequence-based protein deimmunization, and algorithms for finding the Pareto frontier of a design space. While structure-based protein design is NP-hard, we employ integer programming techniques that are efficient in practice. Furthermore, EpiSweep only invokes the optimizer once per identified Pareto optimal design. We show that EpiSweep designs of regions of the therapeutics erythropoietin and staphylokinase are predicted to outperform previous experimental efforts. We also demonstrate EpiSweep’s capacity for global protein deimmunization, a case analysis involving 50 predicted epitopes and over 30,000 unique side-chain interactions. Ultimately, EpiSweep is a powerful protein design tool that guides the protein engineer towards the most promising immunotolerant biotherapeutic candidates.
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References
Chen, C.Y., Georgiev, I., Anderson, A.C., Donald, B.R.: Computational structure-based redesign of enzyme activity. PNAS 106, 3764–3769 (2009)
Dahiyat, B., Mayo, S.: De novo protein design: fully automated sequence selection. Science 278, 82–87 (1997)
De Groot, A.S., Knopp, P.M., Martin, W.: De-immunization of therapeutic proteins by T-cell epitope modification. Dev. Biol (Basel) 122, 171–194 (2005)
De Groot, A.S., Martin, W.: Reducing risk, improving outcomes: Bioengineering less immunogenic protein therapeutics. Clinical Immunology 131, 189–201 (2009)
De Groot, A.S., Moise, L.: Prediction of immunogenicity for therapeutic proteins: State of the art. Curr. Opin. Drug Discov. Devel. 10, 332–340 (2007)
Desmet, J., De Maeyer, M., Hazes, B., Lasters, I.: The dead-end elimination theorem and its use in protein side-chain positioning. Nature 356, 539–542 (1992)
Dinglasan, R.R., Kalume, D.E., Kanzok, S.M., Ghosh, A.K., Muratova, O., Pandey, A., Jacobs-Lorena, M.: Disruption of Plasmodium falciparum development by antibodies against a conserved mosquito midgut antigen. PNAS 104, 13461–13466 (2007)
Georgiev, I., Lilien, R.H., Donald, B.R.: A Novel 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. In: Apostolico, A., Guerra, C., Istrail, S., Pevzner, P.A., Waterman, M. (eds.) RECOMB 2006. LNCS (LNBI), vol. 3909, pp. 530–545. Springer, Heidelberg (2006)
Goldstein, R.F.: Efficient rotamer elimination applied to protein side-chains and related spin glasses. Biophysical J. 66, 1335–1340 (1994)
Grigoryan, G., Reinke, A., Keating, A.: Design of protein-interaction specificity gives selective bZIP-binding peptides. Nature 458, 859–864 (2009)
He, L., Friedman, A.M., Bailey-Kellogg, C.: A divide and conquer approach to determine the pareto frontier for optimization of protein engineering experiments proteins. Proteins (2011)
Hwang, W.Y.K., Foote, J.: Immunogenicity of engineered antibodies. Methods 36, 3–10 (2005)
Indiveri, F., Murdaca, G.: Immunogenicity of erythropoietin and other growth factors. Rev. Clin. Exp. Hematol. 1, 7–11 (2002)
Jones, P.T., Dear, P.H., Foote, J., Neuberger, M.S., Winter, G.: Replacing the complementarity-determining regions in a human antibody with those from a mouse. Nature 321, 522–525 (1986)
Jones, T.D., Phillips, W.J., Smith, B.J., Bamford, C.A., Nayee, P.D., Baglin, T.P., Gaston, J.S.H., Baker, M.P.: Identification and removal of a promiscuous CD4+ T cell epitope from the C1 domain of factor VIII. J. Thromb. Haemost. 3, 991–1000 (2005)
Kessler, M., Goldsmith, D., Schellekens, H.: Immunogenicity of biopharmaceuticals. Nephrology, Dialysis, Transplantation 21, v9–v12 (2006)
Kingsford, C., Chazelle, B., Singh, M.: Solving and analyzing side-chain positioning problems using linear and integer programming. Bioinf. 21, 1028–1036 (2005)
Klyushnenkova, E.N., Kouiavskaia, D.V., Kodak, J.A., Vandenbark, A.A., Alexander, R.B.: Identification of HLA-DRB1*1501-restricted T-cell epitopes from human prostatic acid phosphatase. Prostate 67, 1019–1028 (2007)
Leader, B., Baca, Q.J., Golan, D.E.: Protein therapeutics: a summary and pharmacological classification. Nat. Rev. Drug Disc. 7, 21–39 (2008)
Lilien, R., Stevens, B., Anderson, A., Donald, B.: 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 adenlytaion enzyme. In: Proc. RECOMB, pp. 46–57 (2004)
McCaldon, P., Argos, P.: Oligopeptide biases in protein sequences and their use in predicting protein coding regions in nucleotide sequences. Proteins: Structure, Function and Genetics 4, 99–122 (1988)
Mustafa, A.S., Shaban, F.A.: Propred analysis and experimental evaluation of promiscuous T-cell epitopes of three major secreted antigens of Mycobacterium tuberculosis. Tuberculosis 86, 115–124 (2006)
Osipovitch, D.C., Parker, A.S., Makokha, C.D., Desrosiers, J., DeGroot, A.S., Baiely-Kellogg, C., Griswold, K.E.: Computational design of immune-evading enzymes for ADEPT therapy (in preperation)
Parker, A.S., Griswold, K.E., Bailey-Kellogg, C.: Optimization of combinatorial mutagenesis. J. Comput. Biol. 18, 1743–1756 (2011); In: Bafna, V., Sahinalp, S.C. (eds.) RECOMB 2011. LNCS, vol. 6577, pp. 321–335. Springer, Heidelberg (2011)
Parker, A.S., Griswold, K.E., Bailey-Kellogg, C.: Optimization of therapeutic proteins to delete t-cell epitopes while maintaining beneficial residue interactions. J. Bioinf. Comput. Biol. 9, 207–229 (2011); conf. ver: Proc CSB, pp.100–113 (2010)
Parker, A.S., Zheng, W., Griswold, K.E., Bailey-Kellogg, C.: Optimization algorithms for functional deimmunization of therapeutic proteins. BMC Bioinf. 11, 180 (2010)
Pierce, N., Winfree, E.: Protein design is NP-hard. Protein Eng. 15, 779–782 (2002)
Schellekens, H.: Bioequivalence and the immunogenicity of biopharmaceuticals. Nature Reviews Drug Discovery 1, 457–462 (2002)
Singh, H., Raghava, G.: ProPred: prediction of HLA-DR binding sites. Bioinformatics 17, 1236–1237 (2001)
Southwood, S., Sidney, J., Kondo, A., del Guercio, M.F., Appella, E., Hoffman, S., Kubo, R.T., Chesnut, R.W., Grey, H.M., Sette, A.: Several common HLA-DR types share largely overlapping peptide binding repertoires. J. Immunol. 160, 3363–3373 (1998)
Sturniolo, T., Bono, E., Ding, J., Raddrizzani, L., Tuereci, O., Sahin, U., Braxenthaler, M., Gallazzi, F., Protti, M.P., Sinigaglia, F., Hammer, J.: Generation of tissue-specific and promiscuous HLA ligand database using DNA microarrays and virtual HLA class II matrices. Nature Biotechnol. 17, 555–561 (1999)
Tangri, S., Mothe, B.R., Eisenbraun, J., Sidney, J., Southwood, S., Briggs, K., Zinckgraf, J., Bilsel, P., Newman, M., Chesnut, R., LiCalsi, C., Sette, A.: Rationally engineered therapeutic proteins with reduced immunogenicity. J. Immunol. 174, 3187–3196 (2005)
Wang, P., Sidney, J., Dow, C., Mothe, B., Sette, A., Peters, B.: A systematic assessment of MHC class II peptide binding predictions and evaluation of a consensus approach. PLoS Comp. Biol. 4, e1000048 (2008)
Warmerdam, P.A.M., Plaisance, S., Vanderlick, K., Vandervoort, P., Brepoels, K., Collen, D., Maeyer, M.D.: Elimination of a human T-cell region in staphylokinase by T-cell screening and computer modeling. J. Thromb. Haemost. 87, 666–673 (2002)
Zheng, W., Friedman, A.M., Bailey-Kellogg, C.: Algorithms for joint optimization of stability and diversity in planning combinatorial libraries of chimeric proteins. J. Comput. Biol. 16, 1151–1168 (2009); In: Vingron, M., Wong, L. (eds.) RECOMB 2008. LNCS (LNBI), vol. 4955, pp. 300–314. Springer, Heidelberg (2008)
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Parker, A.S., Griswold, K.E., Bailey-Kellogg, C. (2012). Structure-Guided Deimmunization of Therapeutic Proteins. In: Chor, B. (eds) Research in Computational Molecular Biology. RECOMB 2012. Lecture Notes in Computer Science(), vol 7262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29627-7_19
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DOI: https://doi.org/10.1007/978-3-642-29627-7_19
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