Based on structural information from X-ray and NMR experiments, computational simulations performed using molecular dynamics and the quantum mechanical/molecular mechanical (QM/MM) approach are able to describe the mechanisms of chemical reactions 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 approaches. Thus reaction path and activation free energy calculations based on ab initio QM/MM methods encounter unique challenges in simulation timescales and phase space sampling. This proposal aims to develop further the ab initio QM/MM methodology and its application to the investigation of the 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 the structure and chemical reactions of enzymes and to provide detailed insight into chemical reaction mechanisms in biological systems. The ab initio QM/MM-MFEP method has been developed recently to overcome some of the difficulties encountered in previous ab initio QM/MM approaches for obtaining minimum energy reaction paths. Previous total energy-based methods suffer from a dependence on the local conformations of the protein/solvent environment. In the QM/MM-MFEP method, the reaction system is described via the potential of mean force (PMF) surface of the QM subsystem in the active site, while the large number of MM degrees of freedom describing the rest of the protein and solvent are statistically averaged. This proposal aims to develop the QM/MM-MFEP method further into a comprehensive and accurate method for the simulation of reaction processes in solution and in enzymes using ab initio QM/MM methods. The QM/MM methodology will be used to investigate the reaction mechanism of several important enzymes: (1) Tryptophanyl-tRNA synthetase, which catalyzes the amino acid activation process;(2) Sortase, which recognizes and cleaves peptides, and then covalently links the peptides to cell walls, in association with Gram-positive pathogenic bacteria;and (3) Gram-positive bacterial pili, which play important roles in the biological functions of many bacteria. The proposed work will lead to the advancement of theoretical 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

This proposal aims at developing methods for simulating chemical processes catalyzed by enzymes, and investigating the catalytic mechanisms of certain important enzymes. The proposed work will lead to significant advances in research tools for studying enzymes. Because enzymes catalyze most of the chemical processes in living organisms, it will contribute to the understanding of life processes, as well as aiding in the design of inhibitors and drugs.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
Project #
Application #
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Preusch, Peter C
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Duke University
Schools of Arts and Sciences
United States
Zip Code
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

Showing the most recent 10 out of 47 publications