Abstract
The ability to design novel activities in existing metalloenzyme active sites is a stringent test of our understanding of enzyme mechanisms, sheds light on enzyme evolution, and would have many practical applications. Here, we describe a computational method in the context of the macromolecular modeling suite Rosetta to repurpose active sites containing metal ions for reactions of choice. The required inputs for the method are a model of the transition state(s) for the reaction and a set of crystallographic structures of proteins containing metal ions. The coordination geometry associated with the metal ion (Zn2+, for example) is automatically detected and the transition state model is aligned to the open metal coordination site(s) in the protein. Additional interactions to the transition state model are made using RosettaMatch and the surrounding amino acid side chain identities are optimized for transition state stabilization using RosettaDesign. Validation of the design is performed using docking and molecular dynamics simulations, and candidate designs are generated for experimental validation. Computational metalloenzyme repurposing is complementary to directed evolution approaches for enzyme engineering and allows large jumps in sequence space to make concerted sequence and structural changes for introducing novel enzymatic activities and specificities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lu Y, Yeung N, Sieracki N, Marshall NM (2009) Design of functional metalloproteins. Nature 460:855–862
Zastrow ML, Pecoraro VL (2013) Designing functional metalloproteins: from structural to catalytic metal sites. Coord Chem Rev 257: 2565–2588
Vallee BL, Auld DS (1990) Zinc coordination, function, and structure of zinc enzymes and other proteins. Biochemistry 29:5647–5659
Vallee BL, Hoch FL (1955) Zinc, a component of yeast alcohol dehydrogenase. Proc Natl Acad Sci U S A 41:327–338
Christianson DW, Cox JD (1999) Catalysis by metal-activated hydroxide in zinc and manganese metalloenzymes. Annu Rev Biochem 68:33–57
Khare SD, Kipnis Y, Greisen P, Takeuchi R, Ashani Y, Goldsmith M et al (2012) Computational redesign of a mononuclear zinc metalloenzyme for organophosphate hydrolysis. Nat Chem Biol 8:294–300
Rohl CA, Strauss CEM, Misura KMS, Baker D (2004) Protein structure prediction using Rosetta. Methods Enzymol 383:66–93
Richter F, Leaver-Fay A, Khare SD, Bjelic S, Baker D (2011) De novo enzyme design using Rosetta3. PloS One 6:e19230
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 302:1364–1368
Meiler J, Baker D (2006) ROSETTALIGAND: protein-small molecule docking with full side-chain flexibility. Proteins 65:538–548
Ashkenazy H, Erez E, Martz E, Pupko T, Ben-Tal N (2010) ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids. Nucleic Acids Res 38(Web Server issue):W529–W533
Landau M, Mayrose I, Rosenberg Y, Glaser F, Martz E, Pupko T et al (2005) ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures. Nucleic Acids Res 33(Web Server issue):W299–W302
Cooper S, Khatib F, Treuille A, Barbero J, Lee J, Beenen M et al (2010) Predicting protein structures with a multiplayer online game. Nature 466:756–760
Wang J, Wang W, Kollman PA, Case DA (2006) Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Graph Model 25:247–260
Case DA, Cheatham TE III, Darden T, Gohlke H, Luo R, Merz KM Jr et al (2005) The Amber biomolecular simulation programs. J Comput Chem 26:1668–1688
Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935
Ryckaert JP, Ciccotti G, Berendsen HJC (1977) Numerical-integration of Cartesian equations of motion of a system with constraints – molecular-dynamics of N-alkanes. J Comput Phys 23:327–341
Darden T, York D, Pedersen L (1993) Particle mesh Ewald – an N.Log(N) method for Ewald sums in large systems. J Chem Phys 98:10089–10092
Hornak V, Abel R, Okur A, Strockbine B, Roitberg A, Simmerling C (2006) Comparison of multiple Amber force fields and development of improved protein backbone parameters. Proteins Struct Funct Bioinf 65:712–725
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Science+Business Media New York
About this protocol
Cite this protocol
Greisen, P.J., Khare, S.D. (2014). Computational Redesign of Metalloenzymes for Catalyzing New Reactions. In: Köhler, V. (eds) Protein Design. Methods in Molecular Biology, vol 1216. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-1486-9_14
Download citation
DOI: https://doi.org/10.1007/978-1-4939-1486-9_14
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-1485-2
Online ISBN: 978-1-4939-1486-9
eBook Packages: Springer Protocols