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Next-generation DFT-based quantum models for simulations of biocatalysis

Next-generation DFT-based quantum models for simulations of biocatalysis. Darrin M. York U niversity of M innesota Minneapolis, Minnesota USA. http:// theory.chem.umn.edu. Outline. AM1/d-PhoT model for RNA catalysis

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Next-generation DFT-based quantum models for simulations of biocatalysis

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  1. Next-generation DFT-based quantum models for simulations of biocatalysis Darrin M. York University of Minnesota Minneapolis, Minnesota USA http://theory.chem.umn.edu

  2. Outline • AM1/d-PhoT model for RNA catalysis • Efficient treatment of long-range electrostatics in semiempirical calculations • Improved charge-dependant response properties • Selected applications

  3. …in words • Study phosphate reactivity comprehensively (using small models) with high-level quantum models (ab initio and DFT) • Construct accurate semiempirical quantum models capable of being used in linear-scaling electronic structure and QM/MM simulations • Develop improved (accurate, fast and general) models for electrostatics, solvation and generalized solvent boundary potentials. • Investigate how to improve next-generation semiempirical quantum models to account for charge-dependent response properties without significant sacrifice of efficiency. • Validate methods with respect to known reactions in solution, then apply them to the important problem of RNA catalysis in a realistic system consisting of many thousands of particles, and simulated for many tens of nanoseconds.

  4. Phosphates and phosphoranes

  5. Dissociative DN Concerted ANDN Associative AN+DN Mechanisms for phosphoryl transfer

  6. QCRNA – Online!http://theory.chem.umn.edu/QCRNA Molecule (2000+) Reaction Mechanism (300+) Giese et al.,J. Mol. Graph. Model. 25, 423 (2006).

  7. QCRNA – Online! http://theory.chem.umn.edu/QCRNA Potential Energy Surface Reaction Tables Graphical Interface Giese et al.,J. Mol. Graph. Model. 25, 423 (2006).

  8. Phosphate isomerization (Migration) movie Liu et al., J. Phys. Chem. B, .109, 19987 (2005); Chem. Commun., 31, 3909 (2005). Silva-Lopez et al., Chem. Eur. J.,11, 2081 (2005); Mayaan et al., J. Biol. Inorg. Chem., 9, 807 (2004). Range et al., J. Am. Chem. Soc.,126, 1654 (2004).

  9. Parameter Optimization: AM1/d Methods Training set included a wide variety of biological phosphates and phosphoranes, hydrogen bonded complexes, proton affinities and reaction paths of associative and dissociative mechanisms in different charge states. Nam et al.,J. Chem. Theory Comput., submitted.

  10. Why use a semiempirical model? It is important to note that for the ribozyme systems of interest, the details of the mechanisms remain topics of considerable debate. Hence the goal is to test multiple mechanisms with a model that is sufficiently predictive to discern the most probable path. A consensus has emerged that, in certain ribozymes such as HHR and HDV, a large scale conformational change either precedes or is concomitant with the chemical step of the reaction. This necessitates the use of a quantum model that is able to be used with extensive conformational sampling (i.e., simulation) while providing an accurate description, in terms of energy, structure and charge distribution, along multiple mechanistic paths (i.e., not a single pre-determined 1-D reaction coordinate) in order to be predictive.

  11. Modification for AM1/d-PhoT Model Want a d-orbital method for hypervalent species, but one that also describes reasonably hydrogen bonding interactions. Combine MNDO/d framework with a modified core-core term similar to AM1 (and retaining some AM1 parameters unmodified) to build a semiempirical model for phosphoryl transfer reactions: AM1/d-PhoT Core-Core Repulsion MNDO AM1 and PM3 Modified Core-Core Repulsion If GA and GB = 1,  AM1 and PM3 If GA and GB = 0,  MNDO Hamiltonian

  12. AM1/d-PhoT Model for Phosphoryl Transfer

  13. AM1/d-PhoT Model for Phosphoryl Transfer

  14. AM1/d-PhoT Model for Phosphoryl Transfer

  15. AM1/d-PhoT Model for Phosphoryl Transfer

  16. AM1/d-PhoT Model for Phosphoryl Transfer

  17. Reaction Energies and Barrier Heights *Errors are computed against “B3LYP/6-311++G(3df,2p) adiabatic energies”

  18. Linear Free Energy Relations Transphosphorylation of a cyclic phosphate with enhanced leaving groups. Slope of plot is the Brønsted correlation parameter βlg often used to characterize phosphoryl transfer reactions. The logk values were calculated from DFT and are contained in QCRNA.

  19. Gas Phase Proton Affinity I Range et al., Phys. Chem. Chem. Phys.7, 3070 (2005). B3LYP: B3LYP/6-311++G(3df,2p)//B3LYP/6-31++G(d,p)

  20. Gas Phase Proton Affinity II: Phosphorane Compounds Range et al., Phys. Chem. Chem. Phys.7, 3070 (2005). B3LYP: B3LYP/6-311++G(3df,2p)//B3LYP/6-31++G(d,p)

  21. Comparison with DFT and Expt. in kcal/mol q = R(P-Ol) - R(On-P) Example: QM/MM of Di-anionic Reactions in Water *DFT: B3LYP/6-311++G(3df,2p) Dejaegere and Karplus, JACS 1993 Cox and Ramsay, Chem. Rev. 1964

  22. Problems • Dispersion interactions • Relative conformational energies: sugar puckering and pseudorotation transition states • Proper treatment of polarizability and multiple charge states

  23. The Problem of Charge-dependent Response Properties with Semiempirical Methods Atoms are of course an extreme case: but typically polarizabilities of neutral molecules are typically off by 25%, and anions by significantly more… Giese et al., J. Chem. Phys., 123, 164108 (2005).

  24. Goal:Improve charge-dependent response properties of semiempirical methods without significantly increasing computational cost. Possible solutions: • Reparameterize models • Increase minimal basis-set representation • Make basis set exponents charge dependent

  25. DFT-based model… Giese et al., J. Chem. Phys.123, 164108 (2005).

  26. A Variational Electrostatic Projection (VEP) Method for QM/MM Calculations Goal: Model large-scale electrostatic effects of solvent-shielded macromolecular environment - and it’s linear response – in hybrid QM/MM calculations for a fraction of computational cost of explicit simulation Method: Green’s function approach that involves variational projection and reduced dimensional mapping of surrounding solvent-shielded macromolecular environment onto the dynamical reaction zone Gregersen and York, J. Phys. Chem. B, 109, 536-556 (2005). Gregersen and York, J. Comput. Chem., 27, 103 (2006).

  27. Multi-scale Quantum Models External potential of solute and solvent Stochastic boundary Reaction Region QM active site + MM surrounding (Newtonian dynamics) Buffer Region (Langevin dynamics)

  28. Linear-scaling QM/MM-Ewald Method Nam et al., J. Chem. Theory Comput., 1, 2 (2005).

  29. Applications to enzymes and ribozymes • Hammerhead ribozyme Best characterized ribozyme – but complicated: role of metals, chemical/conformational steps, non-inline native structure • Hairpin ribozyme No metal cofactor, in-line configuration

  30. General acid/base mechanism

  31. Tai-Sung Lee et al., submitted. Mg2+ ion is observed to coordinate the O2’ of G8 increasing it’s acidity in the early TS and then migrate closer to the leaving group O5’ position of the scissile phosphate in the late TS. Simulations help to explain the long-standing disconnect between available structures and biochemical data (in particular, thio effect studies).

  32. Early TS Late TS

  33. Other Projects… • Parameters for RNA reactive intermediates • DNA bending • Polarization-exchange coupling • Linear-scaling electronic structure

  34. Acknowledgements George Giambasu Dr. Tim Giese Yun Liu Dr. Evelyn Mayaan Adam Moser Dr. Kwangho Nam Dr. Kevin Range Dr. Olalla Nieto Faza Dr. Francesca Guerra Dr. Carlos Silva Lopez Prof. Xabier Lopez Dr. Anguang Hu Prof Bill Scott Prof. Qiang Cui Dhd Marcus Elstner Prof. Jiali Gao Prof. Walter Thiel Funding/Resources: • University of Minnesota • NIH • ACS-PRF • Army High-Performance Computing Research Center • Minnesota Supercomputing Institute

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