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Computer simulation of protein structure and dynamics:

  • School of Life Sciences, and Hefei National Laboratory of Physical Sciences at Microscale, University of Science and Technology of China, Hefei 230027, China

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  • Received Date: 28 June 2008
  • Rev Recd Date: 05 July 2008
  • Publish Date: 31 August 2008
    Abstract

  • Abstract

    Computer simulation has been developed into an important tool for the elucidation of biological functions from the atomic level structures and dynamics of biomolecules. Compared with current experimental techniques probing atomic level structures, simulations provide not only averages, but also distributions. Besides structures, biological functions often rely on sophisticatedly controlled dynamics of biomolecules, such as the allosteric effects in enzyme catalysis or the effects of ligand-receptor binding in signal transduction. To help understand and eventually control such processes, simulations can be used to reconstruct conformational pathways, identifying intermediates and transition states. This report highlights our recent work in this field. One focus of our research is on developing, testing and refining energy functions for protein simulations, including pure molecular mechanical models for modeling conformational dynamics and hybrid quantum mechanical/molecular mechanical models for modeling enzyme catalysis. Another focus is on developing methods for efficient sampling in the conformational space and for mapping conformational pathways.

    Abstract

    Computer simulation has been developed into an important tool for the elucidation of biological functions from the atomic level structures and dynamics of biomolecules. Compared with current experimental techniques probing atomic level structures, simulations provide not only averages, but also distributions. Besides structures, biological functions often rely on sophisticatedly controlled dynamics of biomolecules, such as the allosteric effects in enzyme catalysis or the effects of ligand-receptor binding in signal transduction. To help understand and eventually control such processes, simulations can be used to reconstruct conformational pathways, identifying intermediates and transition states. This report highlights our recent work in this field. One focus of our research is on developing, testing and refining energy functions for protein simulations, including pure molecular mechanical models for modeling conformational dynamics and hybrid quantum mechanical/molecular mechanical models for modeling enzyme catalysis. Another focus is on developing methods for efficient sampling in the conformational space and for mapping conformational pathways.
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    • References(21)
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    Van Gunsteren W F, Bakowies D, Baron R, et al. Biomolecular modelling: goals, problems, perspectives[J]. Angew Chem Int Ed Eng, 2006, 45:4 064-4 092.
    [2]
    Ding H S，Yang Y Ｄ，Zhang J H, et al. Structural basis for SUMO-E2 interaction revealed by a complex model using docking approach in combination with NMR data[J]. Proteins, 2005,61:1 050-1 058.
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    Liu H Y, Duan Z H, Luo Q M, et al. Structure-based ligand design by dynamically assembling molecular building blocks at binding site[J]. Proteins, 1999, 36:462-470.
    [4]
    Zhu J, Shi Y Y, Liu H Y. Parametrization of a generalized Born/solvent-accessible surface area model and applications to the simulation of protein dynamics[J]. J Phys Chem B, 2002, 106:4 844-4 853.
    [5]
    Zhu J, Zhu Q Q, Shi Y Y, et al. How well can we predict native contacts in proteins based on decoy structures and their energies[J]. Proteins, 2003,52:598-608.
    [6]
    Xie L, Liu H Y. The treatment of solvation by a generalized Born model and a self-consistent charge-density functional theory-based tight-binding method[J]. J Comput Chem, 2002, 23:1 404-1 415.
    [7]
    Wang J, Gu Y, Liu H Y. Determination of conformational free energies of peptides by multidimensional adaptive umbrella sampling[J]. J Chem Phys, 2006,125:094907.
    [8]
    Cao Z X, Lin Z X, Liu H Y. Refining the description of peptide backbone conformations improves protein simulations using the GROMOS 53A6 force field[J]. J Comput Chem, 2008(in press).
    [9]
    Xu C， Wang J， Liu H Y. A Hamiltonian replica exchange approach and its application to the study of side chain type and neighbor effects on peptide backbone conformations[J]. J Chem Theo Comput, 2008(in press).
    [10]
    Cao Z X, Liu H Y. Using free energy perturbation to predict effects of changing force field parameters on computed conformational equilibriums of peptides[J]. J Chem Phys, 2008(in press).
    [11]
    Zhang Z Y, Shi Y Y, Liu H Y. Molecular dynamics simulations of peptides and proteins with amplified collective motions[J]. Biophys J, 2003, 84:3 583-3 593.
    [12]
    He J B，Zhang Z Y，Shi Y Y， et al. Efficiently explore the energy landscape of proteins in molecular dynamics simulations by amplifying collective motions[J]. J Chem Phys, 2003, 119:4 005-4 017.
    [13]
    Yang Y D, Liu H Y. Genetic algorithms for protein conformation sampling and optimization in a discrete backbone dihedral angle space[J]. J Comput Chem, 2006, 27:1 593-1 602.
    [14]
    Cheng S M, Yang Y D, Wang W R, et al. Transition state ensemble for the folding of B domain of protein A: A comparison of distributed molecular dynamics simulations with experiments[J]. J Phys Chem B, 2005,109:23 645-23 654.
    [15]
    Xie L, Liu H Y, Yang W T. Adapting the nudged elastic band method for determining minimum-energy paths of chemical reactions in enzymes[J]. J Chem Phys, 2004, 120:8 039-8 052.
    [16]
    Liu H Y, Lu Z Y, Cisneros G A, et al. Parallel iterative reaction path optimization in ab initio quantum mechanical/molecular mechanical modeling of enzyme reactions[J]. J Chem Phys, 2004, 121:697-706.
    [17]
    Gu W, Wang T T, Zhu J, et al. Molecular dynamics simulation of the unfolding of the human prion protein domain under low pH and high temperature conditions[J]. Biophysical Chemistry, 2003,104:79-94.
    [18]
    Tang L, Liu H Y. A comparative molecular dynamics study of thermophilic and mesophilic ribonuclease HI enzymes[J]. J Biomol Struct Dyn, 2007,24:379-392.
    [19]
    Dong M H, Liu H Y. Origins of the different metal preferences of E. coli peptide deformylase and Bacillus Thermoproteolyticus thermolysin: a comparative QM/MM study[J]. J Phys Chem B, 2008(in press).
    [20]
    Cisnero G A, Liu H Y, Zhang Y K, et al. Ab initio QM/MM study shows there is no general acid in the reaction catalyzed by 4-oxalocrotonate tautomerase[J]. J Am Chem Soc, 2003, 125:10 384-10 393.
    [21]
    Li Q, Liu H Y. Fragment-based local statistical potentials derived by combining an alphabet of protein local structures with secondary structures and solvent accessibilities[J]. Proteins, 2008(in press).
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    [1]
    Van Gunsteren W F, Bakowies D, Baron R, et al. Biomolecular modelling: goals, problems, perspectives[J]. Angew Chem Int Ed Eng, 2006, 45:4 064-4 092.
    [2]
    Ding H S，Yang Y Ｄ，Zhang J H, et al. Structural basis for SUMO-E2 interaction revealed by a complex model using docking approach in combination with NMR data[J]. Proteins, 2005,61:1 050-1 058.
    [3]
    Liu H Y, Duan Z H, Luo Q M, et al. Structure-based ligand design by dynamically assembling molecular building blocks at binding site[J]. Proteins, 1999, 36:462-470.
    [4]
    Zhu J, Shi Y Y, Liu H Y. Parametrization of a generalized Born/solvent-accessible surface area model and applications to the simulation of protein dynamics[J]. J Phys Chem B, 2002, 106:4 844-4 853.
    [5]
    Zhu J, Zhu Q Q, Shi Y Y, et al. How well can we predict native contacts in proteins based on decoy structures and their energies[J]. Proteins, 2003,52:598-608.
    [6]
    Xie L, Liu H Y. The treatment of solvation by a generalized Born model and a self-consistent charge-density functional theory-based tight-binding method[J]. J Comput Chem, 2002, 23:1 404-1 415.
    [7]
    Wang J, Gu Y, Liu H Y. Determination of conformational free energies of peptides by multidimensional adaptive umbrella sampling[J]. J Chem Phys, 2006,125:094907.
    [8]
    Cao Z X, Lin Z X, Liu H Y. Refining the description of peptide backbone conformations improves protein simulations using the GROMOS 53A6 force field[J]. J Comput Chem, 2008(in press).
    [9]
    Xu C， Wang J， Liu H Y. A Hamiltonian replica exchange approach and its application to the study of side chain type and neighbor effects on peptide backbone conformations[J]. J Chem Theo Comput, 2008(in press).
    [10]
    Cao Z X, Liu H Y. Using free energy perturbation to predict effects of changing force field parameters on computed conformational equilibriums of peptides[J]. J Chem Phys, 2008(in press).
    [11]
    Zhang Z Y, Shi Y Y, Liu H Y. Molecular dynamics simulations of peptides and proteins with amplified collective motions[J]. Biophys J, 2003, 84:3 583-3 593.
    [12]
    He J B，Zhang Z Y，Shi Y Y， et al. Efficiently explore the energy landscape of proteins in molecular dynamics simulations by amplifying collective motions[J]. J Chem Phys, 2003, 119:4 005-4 017.
    [13]
    Yang Y D, Liu H Y. Genetic algorithms for protein conformation sampling and optimization in a discrete backbone dihedral angle space[J]. J Comput Chem, 2006, 27:1 593-1 602.
    [14]
    Cheng S M, Yang Y D, Wang W R, et al. Transition state ensemble for the folding of B domain of protein A: A comparison of distributed molecular dynamics simulations with experiments[J]. J Phys Chem B, 2005,109:23 645-23 654.
    [15]
    Xie L, Liu H Y, Yang W T. Adapting the nudged elastic band method for determining minimum-energy paths of chemical reactions in enzymes[J]. J Chem Phys, 2004, 120:8 039-8 052.
    [16]
    Liu H Y, Lu Z Y, Cisneros G A, et al. Parallel iterative reaction path optimization in ab initio quantum mechanical/molecular mechanical modeling of enzyme reactions[J]. J Chem Phys, 2004, 121:697-706.
    [17]
    Gu W, Wang T T, Zhu J, et al. Molecular dynamics simulation of the unfolding of the human prion protein domain under low pH and high temperature conditions[J]. Biophysical Chemistry, 2003,104:79-94.
    [18]
    Tang L, Liu H Y. A comparative molecular dynamics study of thermophilic and mesophilic ribonuclease HI enzymes[J]. J Biomol Struct Dyn, 2007,24:379-392.
    [19]
    Dong M H, Liu H Y. Origins of the different metal preferences of E. coli peptide deformylase and Bacillus Thermoproteolyticus thermolysin: a comparative QM/MM study[J]. J Phys Chem B, 2008(in press).
    [20]
    Cisnero G A, Liu H Y, Zhang Y K, et al. Ab initio QM/MM study shows there is no general acid in the reaction catalyzed by 4-oxalocrotonate tautomerase[J]. J Am Chem Soc, 2003, 125:10 384-10 393.
    [21]
    Li Q, Liu H Y. Fragment-based local statistical potentials derived by combining an alphabet of protein local structures with secondary structures and solvent accessibilities[J]. Proteins, 2008(in press).
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