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Searching for the Pareto frontier in multi-objective protein design

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Abstract

The goal of protein engineering and design is to identify sequences that adopt three-dimensional structures of desired function. Often, this is treated as a single-objective optimization problem, identifying the sequence–structure solution with the lowest computed free energy of folding. However, many design problems are multi-state, multi-specificity, or otherwise require concurrent optimization of multiple objectives. There may be tradeoffs among objectives, where improving one feature requires compromising another. The challenge lies in determining solutions that are part of the Pareto optimal set—designs where no further improvement can be achieved in any of the objectives without degrading one of the others. Pareto optimality problems are found in all areas of study, from economics to engineering to biology, and computational methods have been developed specifically to identify the Pareto frontier. We review progress in multi-objective protein design, the development of Pareto optimization methods, and present a specific case study using multi-objective optimization methods to model the tradeoff between three parameters, stability, specificity, and complexity, of a set of interacting synthetic collagen peptides.

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References

  • Ambroggio XI, Kuhlman B (2006) Computational design of a single amino acid sequence that can switch between two distinct protein folds. J Am Chem Soc 128(4):1154–1161

    Article  CAS  PubMed  Google Scholar 

  • Belure SV, Shir OM, Nanda V (2017) Protein design by multiobjective optimization: evolutionary and non-evolutionary approaches. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2017), Berlin, Germany July 2017. ACM Press, New York

  • Braxton S, Wells JA (1992) Incorporation of a stabilizing calcium-binding loop into subtilisin BPN. Biochemistry 31(34):7796–7801

    Article  CAS  PubMed  Google Scholar 

  • Camacho CJ, Katsumata Y, Ascherman DP (2008) Structural and thermodynamic approach to peptide immunogenicity. PLoS Comput Biol 4(11):e1000231

    Article  PubMed  PubMed Central  Google Scholar 

  • Chan HS, Dill KA (1991) “Sequence space soup” of proteins and copolymers. J Chem Phys 95(5):3775–3787

    Article  CAS  Google Scholar 

  • Choi Y, Hua C, Sentman CL, Ackerman ME, Bailey-Kellogg C (2015) Antibody humanization by structure-based computational protein design. MAbs 7(6):1045–1057

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cochran FV, Wu SP, Wang W, Nanda V, Saven JG, Therien MJ, DeGrado WF (2005) Computational de novo design and characterization of a four-helix bundle protein that selectively binds a nonbiological cofactor. J Am Chem Soc 127(5):1346–1347

    Article  CAS  PubMed  Google Scholar 

  • Cutello V, Narzisi G, Nicosia G (2006) A multi-objective evolutionary approach to the protein structure prediction problem. J R Soc Interface 3(6):139–151

    Article  CAS  PubMed  Google Scholar 

  • Das I, Dennis JE (1997) A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems. Struct Multidiscip Optim 14(1):63–69

    Article  Google Scholar 

  • Fallas JA, Gauba V, Hartgerink JD (2009) Solution structure of an ABC collagen heterotrimer reveals a single-register helix stabilized by electrostatic interactions. J Biol Chem 284(39):26851–26859

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fleishman SJ, Baker D (2012) Role of the biomolecular energy gap in protein design, structure, and evolution. Cell 149(2):262–273

    Article  CAS  PubMed  Google Scholar 

  • Fromer M, Shifman JM (2009) Tradeoff between stability and multispecificity in the design of promiscuous proteins. PLoS Comput Biol 5(12):e1000627

    Article  PubMed  PubMed Central  Google Scholar 

  • Gauba V, Hartgerink JD (2007) Self-assembled heterotrimeric collagen triple helices directed through electrostatic interactions. J Am Chem Soc 129(9):2683–2690

    Article  CAS  PubMed  Google Scholar 

  • Grigoryan G, Reinke AW, Keating AE (2009) Design of protein-interaction specificity affords selective bZIP-binding peptides. Nature 458(7240):859–864

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Griswold KE, Bailey-Kellogg C (2016) Design and engineering of deimmunized biotherapeutics. Curr Opin Struct Biol 39:79–88

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hall MP (2014) Biotransformation and in vivo stability of protein biotherapeutics: impact on candidate selection and pharmacokinetic profiling. Drug Metab Dispos 42(11):1873–1880

    Article  PubMed  Google Scholar 

  • Handel TM, Williams SA, DeGrado WF (1993) Metal ion-dependent modulation of the dynamics of a designed protein. Science 261(5123):879–885

    Article  CAS  PubMed  Google Scholar 

  • Hartke B (2004) Application of evolutionary algorithms to global cluster geometry optimization. Appl Evol Comput Chem 110:33–53

    Google Scholar 

  • Havranek JJ, Harbury PB (2003) Automated design of specificity in molecular recognition. Nat Struct Mol Biol 10(1):45–52

    Article  CAS  Google Scholar 

  • He L, Friedman AM, Bailey-Kellogg C (2012) A divide-and-conquer approach to determine the Pareto frontier for optimization of protein engineering experiments. Proteins Struct Funct Bioinf 80(3):790–806

    Article  CAS  Google Scholar 

  • Hellinga HW, Richards FM (1994) Optimal sequence selection in proteins of known structure by simulated evolution. Proc Natl Acad Sci U S A 91(13):5803–5807

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Howell SC, Inampudi KK, Bean DP, Wilson CJ (2014) Understanding thermal adaptation of enzymes through the multistate rational design and stability prediction of 100 adenylate kinases. Structure 22(2):218–229

    Article  CAS  PubMed  Google Scholar 

  • Jiang L, Althoff EA, Clemente FR, Doyle L, Röthlisberger D, Zanghellini A, Gallaher JL, Betker JL, Tanaka F, Barbas CF 3rd, Hilvert D, Houk KN, Stoddard BL, Baker D (2008) De novo computational design of retro-aldol enzymes. Science 319(5868):1387–1391

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kiss G, Çelebi‐Ölçüm N, Moretti R, Baker D, Houk KN (2013) Computational enzyme design. Angew Chem Int Ed Engl 52(22):5700–5725

    Article  CAS  PubMed  Google Scholar 

  • Kuhlman B, Dantas G, Ireton GC, Varani G, Stoddard BL, Baker D (2003) Design of a novel globular protein fold with atomic-level accuracy. Science 302(5649):1364–1368

    Article  CAS  PubMed  Google Scholar 

  • Levy ED, De S, Teichmann SA (2012) Cellular crowding imposes global constraints on the chemistry and evolution of proteomes. Proc Natl Acad Sci U S A 109(50):20461–20466

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nautiyal S, Woolfson DN, King DS, Alber T (1995) A designed heterotrimeric coiled coil. Biochemistry 34(37):11645–11651

    Article  CAS  PubMed  Google Scholar 

  • Nivón LG, Moretti R, Baker D (2013) A Pareto-optimal refinement method for protein design scaffolds. PLoS One 8(4):e59004

    Article  PubMed  PubMed Central  Google Scholar 

  • Povolotskaya IS, Kondrashov FA (2010) Sequence space and the ongoing expansion of the protein universe. Nature 465(7300):922–926

    Article  CAS  PubMed  Google Scholar 

  • Röthlisberger D, Khersonsky O, Wollacott AM, Jiang L, DeChancie J, Betker J, Gallaher JL, Althoff EA, Zanghellini A, Dym O, Albeck S, Houk KN, Tawfik DS, Baker D (2008) Kemp elimination catalysts by computational enzyme design. Nature 453(7192):190–195

    Article  PubMed  Google Scholar 

  • Saccà B, Renner C, Moroder L (2002) The chain register in heterotrimeric collagen peptides affects triple helix stability and folding kinetics. J Mol Biol 324(2):309–318

    Article  PubMed  Google Scholar 

  • Salvat RS, Parker AS, Choi Y, Bailey-Kellogg C, Griswold KE (2015) Mapping the Pareto optimal design space for a functionally deimmunized biotherapeutic candidate. PLoS Comput Biol 11(1):e1003988

    Article  PubMed  PubMed Central  Google Scholar 

  • Sanchez-Faddeev H, Emmerich MTM, Verbeek FJ, Henry AH, Grimshaw S, Spaink HP, van Vlijmen HW, Bender A (2012) Using multiobjective optimization and energy minimization to design an isoform-selective ligand of the 14-3-3 protein. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7610:12–24

  • Seeman NC, Kallenbach NR (1983) Design of immobile nucleic acid junctions. Biophys J 44(2):201–209

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sevy AM, Jacobs TM, Crowe JE Jr, Meiler J (2015) Design of protein multi-specificity using an independent sequence search reduces the barrier to low energy sequences. PLoS Comput Biol 11(7):e1004300

    Article  PubMed  PubMed Central  Google Scholar 

  • Sheftel H, Shoval O, Mayo A, Alon U (2013) The geometry of the Pareto front in biological phenotype space. Ecol Evol 3(6):1471–1483

    Article  PubMed  PubMed Central  Google Scholar 

  • Shifman JM, Mayo SL (2002) Modulating calmodulin binding specificity through computational protein design. J Mol Biol 323(3):417–423

    Article  CAS  PubMed  Google Scholar 

  • Sormanni P, Aprile FA, Vendruscolo M (2015) The CamSol method of rational design of protein mutants with enhanced solubility. J Mol Biol 427(2):478–490

    Article  CAS  PubMed  Google Scholar 

  • Stapleton JA, Whitehead TA, Nanda V (2015) Computational redesign of the lipid-facing surface of the outer membrane protein OmpA. Proc Natl Acad Sci U S A 112(31):9632–9637

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Summa CM, Rosenblatt MM, Hong JK, Lear JD, DeGrado WF (2002) Computational de novo design, and characterization of an A(2)B(2) diiron protein. J Mol Biol 321(5):923–938

    Article  CAS  PubMed  Google Scholar 

  • Tompa P, Rose GD (2011) The Levinthal paradox of the interactome. Protein Sci 20(12):2074–2079

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Voigt CA, Gordon DB, Mayo SL (2000) Trading accuracy for speed: a quantitative comparison of search algorithms in protein sequence design. J Mol Biol 299(3):789–803

    Article  CAS  PubMed  Google Scholar 

  • Warszawski S, Netzer R, Tawfik DS, Fleishman SJ (2014) A “fuzzy”-logic language for encoding multiple physical traits in biomolecules. J Mol Biol 426(24):4125–4138

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Whitehead TA, Chevalier A, Song Y, Dreyfus C, Fleishman SJ, De Mattos C, Myers CA, Kamisetty H, Blair P, Wilson IA, Baker D (2012) Optimization of affinity, specificity and function of designed influenza inhibitors using deep sequencing. Nat Biotechnol 30(6):543–548

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wiecha PR, Arbouet A, Girard C, Lecestre A, Larrieu G, Paillard V (2017) Evolutionary multi-objective optimisation of colour pixels based on dielectric nano-antennas. Nat Nanotechnol 12(2):163–169

    Article  CAS  PubMed  Google Scholar 

  • Xu F, Zhang L, Koder RL, Nanda V (2010) De novo self-assembling collagen heterotrimers using explicit positive and negative design. Biochemistry 49(11):2307–2316

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Xu F, Zahid S, Silva T, Nanda V (2011) Computational design of a collagen A:B:C-type heterotrimer. J Am Chem Soc 133(39):15260–15263

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Xu F, Silva T, Joshi M, Zahid S, Nanda V (2013) Circular permutation directs orthogonal assembly in complex collagen peptide mixtures. J Biol Chem 288(44):31616–31623

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yue K, Fiebig KM, Thomas PD, Chan HS, Shakhnovich EI, Dill KA (1995) A test of lattice protein folding algorithms. Proc Natl Acad Sci U S A 92(1):325–329

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zanghellini A, Jiang L, Wollacott AM, Cheng G, Meiler J, Althoff EA, Röthlisberger D, Baker D (2006) New algorithms and an in silico benchmark for computational enzyme design. Protein Sci 15(12):2785–2794

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Center for Advanced Biotechnology and Medicine, Rutgers University, Piscataway, NJ, USA

    Vikas Nanda & Sandeep V. Belure

  2. Department of Biochemistry and Molecular Biophysics, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ, USA

    Vikas Nanda & Sandeep V. Belure

  3. Department of Computer Science, Tel-Hai College, Kiryat Shmona, Upper Galilee, Israel

    Ofer M. Shir

  4. The Galilee Research Institute—Migal, Kiryat Shmona, Upper Galilee, Israel

    Ofer M. Shir

Authors
  1. Vikas Nanda
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  2. Sandeep V. Belure
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Correspondence to Vikas Nanda.

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Vikas Nanda declares that he has no conflict of interest. Sandeep V. Belure declares that he has no conflict of interest. Ofer M. Shir declares that he has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

This article is part of a Special Issue on ‘IUPAB Edinburgh Congress’ edited by Damien Hall.

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Nanda, V., Belure, S.V. & Shir, O.M. Searching for the Pareto frontier in multi-objective protein design. Biophys Rev 9, 339–344 (2017). https://doi.org/10.1007/s12551-017-0288-0

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