Based on structural information from X-ray and NMR experiments, computational simulations performed us- ing molecular dynamics and the quantum mechanical/molecular mechanical (QM/MM) approach are able to describe the chemical reactions and redox processes catalyzed by enzymes. Ab initio QM/MM methods capitalize on the accuracy and reliability of the associated quantum mechanical approaches, however at a much higher computational cost compared with corresponding semiempirical quantum mechanical ap- proaches. Thus reaction path and free energy calculations based on ab initio QM/MM methods encounter unique challenges in simulation times and phase space sampling. This proposal aims to develop further the ab initio QM/MM methodology and its application to the studies of redox processes and mechanisms of chemical reactions in important enzymes. The long-term goal is to develop and establish density functional theory-based QM/MM simulation as an equal partner with experiments for the study of enzymes and to provide detailed insight into chemical reaction and redox reaction mechanisms in biological systems. The ab initio QM/MM-MFEP method has been developed recently to overcome some of the difficul- ties encountered in previous ab initio QM/MM approaches for obtaining minimum energy reaction paths. This proposal aims to develop the QM/MM-MFEP method further into a comprehensive and accurate method for the simulation of redox processes in solution and in enzymes using ab initio QM/MM meth- ods. The QM/MM methodology will be used to investigate several important systems: (1) The redox poten- tials in wild-type and single-site variants of the copper protein enzyme peptidyglycine alpha-hydroxylating monooxygenase (PHM), which is a prototype for the two copper family enzymes that includes dopamine beta-monooxygenase and tyramine beta-monooxygenase. (2) Human DNA polymerase , which catalyzes the phosphoryl-transfer reaction in DNA synthesis. (3) Sulfatases, which controls the state of sulfation of proteins, carbohydrates, lipids and steroids, and may produce the largest rate enhancements that are generated by any enzyme. (4) Peptidoglycan recycling enzyme, which catalyze phosphoryl transfer and hydrolysis. The proposed work will lead to the advancement of theoretical and computational methodology and the understanding of important enzyme reaction mechanisms. In addition, it will also serve to aid in the design of new drugs and enzyme inhibitors.

Public Health Relevance

Understanding chemical reactions and redox processes in solution and in enzymes is of ultimate impor- tance. In biological systems, most biological functions are accomplished through the binding of ligands with proteins and/or a series of chemical reactions catalyzed by specific enzymes with different efficiency and specificity. The structure-function relationship and the catalytic role of enzymes are thus fundamental subjects in biochemical research. They are also essential for the development of new or better inhibitors and enzymes, which have important practical applications, ranging from drug design to the development of novel catalysts for drug synthesis. As an increasing amount of structural information for proteins and enzymes becomes available, the structure-function relationship becomes an even more important link in biological science. Quantitative tools such as simulations will make key contributions to the investigation of this topic. This proposal aims at developing methods for simulating chemical and redox processes catalyzed by enzymes, and investigating the mechanisms of important enzymes-copper protein enzyme peptidyglycine alpha-hydroxylating monooxygenase, human DNA polymerase, sulfatases, and peptidoglycan recycling enzyme. The proposed work will lead to significant advances in research tools for studying enzymes. It will contribute to the understanding of life processes, as well as aiding in the design of inhibitors and drugs.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM061870-14
Application #
8918642
Study Section
Special Emphasis Panel (ZRG1-BCMB-P (02))
Program Officer
Preusch, Peter
Project Start
2000-07-01
Project End
2018-08-31
Budget Start
2015-09-01
Budget End
2016-08-31
Support Year
14
Fiscal Year
2015
Total Cost
$311,886
Indirect Cost
$103,566
Name
Duke University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705
Su, Neil Qiang; Li, Chen; Yang, Weitao (2018) Describing strong correlation with fractional-spin correction in density functional theory. Proc Natl Acad Sci U S A 115:9678-9683
Shen, Lin; Zeng, Xiancheng; Hu, Hao et al. (2018) Accurate Quantum Mechanical/Molecular Mechanical Calculations of Reduction Potentials in Azurin Variants. J Chem Theory Comput 14:4948-4957
Shen, Lin; Yang, Weitao (2018) Molecular Dynamics Simulations with Quantum Mechanics/Molecular Mechanics and Adaptive Neural Networks. J Chem Theory Comput 14:1442-1455
Al-Saadon, Rachael; Sutton, Christopher; Yang, Weitao (2018) Accurate Treatment of Charge-Transfer Excitations and Thermally Activated Delayed Fluorescence Using the Particle-Particle Random Phase Approximation. J Chem Theory Comput 14:3196-3204
Wang, Hao; Yang, Weitao (2018) Force Field for Water Based on Neural Network. J Phys Chem Lett 9:3232-3240
Sutton, Christopher; Yang, Yang; Zhang, Du et al. (2018) Single, Double Electronic Excitations and Exciton Effective Conjugation Lengths in ?-Conjugated Systems. J Phys Chem Lett 9:4029-4036
Jin, Ye; Zhang, Du; Chen, Zehua et al. (2017) Generalized Optimized Effective Potential for Orbital Functionals and Self-Consistent Calculation of Random Phase Approximations. J Phys Chem Lett 8:4746-4751
Lewis Jr, Charles A; Shen, Lin; Yang, Weitao et al. (2017) Three Pyrimidine Decarboxylations in the Absence of a Catalyst. Biochemistry 56:1498-1503
Wu, Jingheng; Shen, Lin; Yang, Weitao (2017) Internal force corrections with machine learning for quantum mechanics/molecular mechanics simulations. J Chem Phys 147:161732
Chen, Zehua; Zhang, Du; Jin, Ye et al. (2017) Multireference Density Functional Theory with Generalized Auxiliary Systems for Ground and Excited States. J Phys Chem Lett 8:4479-4485

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