Skip to main content
SpringerLink
Log in

Computational Protein Design Methods for Synthetic Biology

  • Protocol
  • First Online:
Computational Methods in Synthetic Biology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1244))

Abstract

Computational protein design, a process that searches for mutants with desired improved properties, plays a central role in the conception of many synthetic biology devices including biosensors, bioproduction, or regulation circuits. To that end, a rational workflow for computational protein design is described here consisting of (a) searching in the sequence, structure or chemical spaces for the desired function and associated protein templates; (b) finding the list of potential hot regions to mutate in the parent proteins; and (c) performing in silico screening of mutants with predicted improved properties.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kazlauskas RJ, Bornscheuer UT (2009) Finding better protein engineering strategies. Nat Chem Biol 5:526–529

    Article  CAS  PubMed  Google Scholar 

  2. Cobb RE, Sun N, Zhao H (2012) Directed evolution as a powerful synthetic biology tool. Methods. doi:10.1016/j.ymeth.2012.03.009

    PubMed Central  PubMed  Google Scholar 

  3. Hayes RJ, Bentzien J, Ary ML et al (2002) Combining computational and experimental screening for rapid optimization of protein properties. Proc Natl Acad Sci U S A 99:15926–15931

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  4. Becskei A, Serrano L (2000) Engineering stability in gene networks by autoregulation. Nature 405:590–593

    Article  CAS  PubMed  Google Scholar 

  5. Elowitz MB, Leibler S (2000) A synthetic oscillatory network of transcriptional regulators. Nature 403:335–338

    Article  CAS  PubMed  Google Scholar 

  6. Gardner TS, Cantor CR, Collins JJ (2000) Construction of a genetic toggle switch in Escherichia coli. Nature 403:339–342

    Article  CAS  PubMed  Google Scholar 

  7. Van der Sloot AM, Kiel C, Serrano L, Stricher F (2009) Protein design in biological networks: from manipulating the input to modifying the output. Protein Eng Des Sel 22:537–542

    Article  PubMed  Google Scholar 

  8. Chang MC, Keasling JD (2006) Production of isoprenoid pharmaceuticals by engineered microbes. Nat Chem Biol 2:674–681

    Article  CAS  PubMed  Google Scholar 

  9. Carbonell P, Planson AG, Fichera D, Faulon JL (2011) A retrosynthetic biology approach to metabolic pathway design for therapeutic production. BMC Syst Biol 5:122

    Article  PubMed Central  PubMed  Google Scholar 

  10. Grünberg R, Serrano L (2010) Strategies for protein synthetic biology. Nucleic Acids Res 38:2663–2675

    Article  PubMed Central  PubMed  Google Scholar 

  11. Looger LL, Dwyer MA, Smith JJ, Hellinga HW (2003) Computational design of receptor and sensor proteins with novel functions. Nature 423:185–190

    Article  CAS  PubMed  Google Scholar 

  12. Schmidt M, de Lorenzo V (2012) Synthetic constructs in/for the environment: managing the interplay between natural and engineered Biology. FEBS Lett 586:2199–2206

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  13. Dueber JE, Wu GC, Malmirchegini GR et al (2009) Synthetic protein scaffolds provide modular control over metabolic flux. Nat Biotechnol 27:753–759

    Article  CAS  PubMed  Google Scholar 

  14. Foo JL, Ching CB, Chang MW, Leong SS (2011) The imminent role of protein engineering in synthetic biology. Biotechnol Adv. doi:10.1016/j.biotechadv.2011.09.008

    PubMed  Google Scholar 

  15. Pleiss J (2011) Protein design in metabolic engineering and synthetic biology. Curr Opin Biotechnol 22:611–617

    Article  CAS  PubMed  Google Scholar 

  16. Lippow SM, Tidor B (2007) Progress in computational protein design. Curr Opin Biotechnol 18:305–311

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Li X, Zhang Z, Song J (2012) Computational protein design approaches with significant biological outcomes: progress and challenges. Comp Struct Biotechnol J. doi:10.5936/csbj.201209007

    Google Scholar 

  18. Tiwari M, Singh R, Singh R et al (2012) Computational approaches for rational design of proteins with novel functionalities. Comp Struct Biotechnol J. doi:10.5936/csbj.201209002

    Google Scholar 

  19. Tsai M, Wu JT, Gunawardhana L, Naik H (2012) The effects of xanthine oxidase inhibition by febuxostat on the pharmacokinetics of theophylline. Int J Clin Pharmcol Ther 50:331–337

    Article  CAS  Google Scholar 

  20. Rudolph MM, Vockenhuber MP, Suess B (2013) Synthetic riboswitches for the conditional control of gene expression in Streptomyces coelicolor. Microbiology. doi:10.1099/mic.0.067322-0

    PubMed  Google Scholar 

  21. Michener JK, Smolke CD (2012) High-throughput enzyme evolution in Saccharomyces cerevisiae using a synthetic RNA switch. Metab Eng 14:306–316

    Article  CAS  PubMed  Google Scholar 

  22. Li W, Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22:1658–1659

    Article  CAS  PubMed  Google Scholar 

  23. Taly JF, Magis C, Bussotti G et al (2011) Using the T-Coffee package to build multiple sequence alignments of protein, RNA, DNA sequences and 3D structures. Nat Protoc 6:1669–1682

    Article  CAS  PubMed  Google Scholar 

  24. Pettersen EF, Goddard TD, Huang CC et al (2004) UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612

    Article  CAS  PubMed  Google Scholar 

  25. Doppelt-Azeroual O, Moriaud F, Adcock SA, Delfaud F (2009) A review of MED-SuMo applications. Infect Disord Drug Targets 9:344–357

    Article  CAS  PubMed  Google Scholar 

  26. Jambon M, Andrieu O, Combet C et al (2005) The SuMo server: 3D search for protein functional sites. Bioinformatics 21:3929–3930

    Article  CAS  PubMed  Google Scholar 

  27. Maggiora GM, Shanmugasundaram V (2011) Molecular similarity measures. Methods Mol Biol 672:39–100

    Article  CAS  PubMed  Google Scholar 

  28. Carbonell P, Carlsson L, Faulon JL (2013) Stereo signature molecular descriptor. J Chem Inf Model 53:887–897

    Article  CAS  PubMed  Google Scholar 

  29. Chang A, Scheer M, Grote A et al (2009) BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Res 37:D588–D592

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  30. Karatzoglou A, Smola A, Hornik K, Zeileis A (2004) Kernlab—an S4 package for Kernel methods in R. J Stat Software 11:1–20

    Google Scholar 

  31. Liu Y, Kuhlman B (2006) RosettaDesign server for protein design. Nucleic Acids Res 34:W235–W238

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  32. Richter F, Leaver-Fay A, Khare SD et al (2011) De novo enzyme design using Rosetta3. PLoS One 6:e19230

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  33. Zhou JZ (2008) Structure-directed combinatorial library design. Curr Opin Chem Biol 12:379–385

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was funded by Genopole®, UniverSud Paris, and Agence Nationale de la Recherche (ANR Chaire d’excellence). UPFellows program with the support of the Marie Curie COFUND program.

Author information

Authors and Affiliations

  1. Research Program on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, IMIM (Hospital del Mar Medical Research Institute), Dr. Aiguader, 88 E-8003, Barcelona, Spain

    Pablo Carbonell

  2. Institute of Systems and Synthetic Biology (iSSB-CNRS), University of Evry, Genopole Campus 1, 5 rue Henri Desbruères, F-91030, Evry Cedex, France

    Pablo Carbonell

  3. SUP’Biotech, Villejuif, 94800, France

    Jean-Yves Trosset

Authors
  1. Pablo Carbonell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jean-Yves Trosset
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pablo Carbonell .

Editor information

Editors and Affiliations

  1. School of Life Science and Technology, Harbin Institute of Technology, Harbin, China

    Mario Andrea Marchisio

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this protocol

Cite this protocol

Carbonell, P., Trosset, JY. (2015). Computational Protein Design Methods for Synthetic Biology. In: Marchisio, M. (eds) Computational Methods in Synthetic Biology. Methods in Molecular Biology, vol 1244. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1878-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-1878-2_1

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-1877-5

  • Online ISBN: 978-1-4939-1878-2

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation