Metalloenzymes, computational

This chapter mainly focuses on the reactivity of 02 and its partially reduced forms. Over the past 5 years, oxygen isotope fractionation has been applied to a number of mechanistic problems. The experimental and computational methods developed to examine the relevant oxidation/reduction reactions are initially discussed. The use of oxygen equilibrium isotope effects as structural probes of transition metal 02 adducts will then be presented followed by a discussion of density function theory (DFT) calculations, which have been vital to their interpretation. Following this, studies of kinetic isotope effects upon defined outer-sphere and inner-sphere reactions will be described in the context of an electron transfer theory framework. The final sections will concentrate on implications for the reaction mechanisms of metalloenzymes that react with 02, 02 -, and H202 in order to illustrate the generality of the competitive isotope fractionation method. 

Further progress in the experimental and computational methodology is essential to address the following (i) the relationship between kinetic and equilibrium isotope effects, (ii) the roles of excited vibrational states, and (iii) how small molecule activation reactions in metalloenzymes relate to those of synthetic inorganic compounds. Once these issues are better understood, isotope fractionation patterns in complex and natural environments can be interpreted at the molecular level. This level of analysis will advance the utility of isotope fractionation in many types of laboratories especially those concentrating on small molecule reactivity. 

When the prediction or interpretation of spectroscopic properties and reactivities of metalloenzymes is the aim, QM-based methods - and DFT in particular - have proven to be the methods of choice [498]. Some of the recent results in the area of blue-copper proteins have been discussed above, and the methods used to interpret and predict spectroscopic parameters are provided in Chapter 10. Here, we concentrate on computational studies related to the understanding of the reactivity of... 

Leopoldini M, Marino T, Russo N, Toscano M (2009) Potential energy surfaces for reaction catalyzed by metalloenzymes from quantum chemical computations. In Russo N, Anton-chenko VY, Kryachko ES (eds) Self-organization of molecular systems from molecules and clusters to nanotubes and proteins, NATO Science for Peace and Security Series A Chemistry and Biology. Springer, New York, p 275-313. doi 10.1007/978-90-481-2590-6 13... 

De La Lande A, Salahub DR, Maddaluno J, Scemama A, Pilme J, Parisel O, Gerard H, Caffarel M, Piquemal J-P (2011) Rapid communication spin-driven activation of dioxygen in various metalloenzymes and their inspired models. J Comput Chem 32 1178-1182... 

Khare, S.D., Kipnis, Y, Greisen Jr., R, et al., 2012. Computational redesign of a mononuclear zinc metalloenzyme for organophosphate hydrolysis. Nat. Chem. Biol 8, 294-300. 

Woodcock HL, Miller BT, Hodoscek M, Okur A, Larkin JD, Pond JW, Brooks BR (2011) MSCALE a general utility for multiscale modeling. J Chem Theory Comput 7 1208-1219 Chung LW, Hirao H, Li X, Morokuma K (2012) The ONIOM method its foundation and applications to metalloenzymes and phombiology. Wiley Interdiscip Rev Comput Mol Sci 2 327-350... 

Chung LW, Hirao H, Li X, Morokuma K (2011) The ONIOM method its foundation and applications to metalloenzymes and photobiology. Wiley Interdisc Rev Comput Mol Sci 2 327-350... 

A. De La Lande, D. R. Salahub, J. Maddaluno, A. Scemama, J. Pilme, O. Parisel, H. Gerard, M. Caffarel, and J. P. Piquemal,/. Comput. Chem., 32(6), 1178-1182 (2011). Rapid Communication Spin-Driven Activation of Dioxygen in Various Metalloenzymes and Their Inspired Models. 

David Case grew up in Ohio and did undergraduate studies at Michigan State University. He received a PhD in chemical physics from Harvard and has held faculty positions at the University of California, Davis, The Scripps Research Institute, and Rutgers University. His work centers on molecular dynamics (MD) simulations of proteins, nucleic acids, and carbohydrates, and he is the leader of the development team for the Amber suite of computer codes (see http //ambermd.org/). Current research interests include interpretation of nuclear magnetic resonance (NMR) results on biomolecules, the structures and mechanisms of metalloenzymes, and the development of implicit solvent models for biochemical simulations. More details are available at http //casegroup.rutgers.edu. 

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