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Force Field of Biological System

Force Field of Biological System. 中国科学院理论物理研究所 张小虎. 研究生院 《 分子建模与模拟导论 》 课堂 2009 年 10 月 21 日. Why do we need force field?. 1. Force Fields. Classical Newtonian Dynamics Electrons are in the ground state Force fields are approximate

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Force Field of Biological System

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  1. Force Field of Biological System 中国科学院理论物理研究所 张小虎 研究生院《分子建模与模拟导论》课堂 2009年10月21日

  2. Why do we need force field?

  3. 1. Force Fields • Classical Newtonian Dynamics • Electrons are in the ground state • Force fields are approximate • Nonbonded force fields for biological systems are effective pair potentials • No Explicit term for hydrogen bonding References • H. J. C. Berendsen, et al, Gromacs User Manual version 4.0 • A. D. MacKerell, Jr. , et al, "Comparison of Protein Force Fields for Molecular Dynamics Simulations“ • A. D. Mackerell, Jr. , et al, "Empirical Force Fields for Biological Macromolecules: Overview and Issues“ • J. W. Ponder, et al, "FORCE FIELDS FOR PROTEIN SIMULATIONS“ • Takao Yoda, et al, “Comparisons of force field for proteins by generalized-ensemble simulations”

  4. 2. Commonly used force fields • Amber: Assisted Model Building with Energy Refinement • CHARMM: Chemistry at HARvard Macromolecular Mechanics • OPLS-AA: Optimized Potentials for Liquid Simulations- All Atom • GROMOS: GROningen MOlecular Simulation References • W. D. Cornell, et al (1995) ”A second generation force field for the simulation of proteins, nucleic acids, and organic molecules” • A. D. MacKerell, et al (1998) ”All-atom empirical potential for molecular modeling and dynamics studies of proteins” • W. L. Jorgensen, et al (1996) ” Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids” • C. Oostenbrink, et al (2004) “A biomolecular force field based on the free enthalpy of hydration and solvation: The GROMOS force-field parameter sets 53A5 and 53A6”

  5. 3. Functional forms Basic functionals

  6. 4. Differences for bonded interactions Valence Angles Improper Dihedral Angles • AMBER: • CHARMM: + • OPLS-AA: • GROMOS: maintain chirality or planarity Urey- Bradly angle term • AMBER: + • CHARMM: + • OPLS-AA: + • GROMOS: +

  7. 5. Differences for nonbonded interactions • Handling of 1,4-nonbonded interactions between A, D in dihedral A-B-C-D • AMBER: LJ ½ Coulomb 1/1.2 • CHARMM: not scaling except some special pairs • OPLS-AA: LJ ½ Coulomb ½ • GROMOS: case by case

  8. 6. How to construct a force field? Adjusting parameter values until the force field is able to reproduce a set of target data to within a prescribed threshold ; name bond_type mass charge ptype sigma epsilon amber99_0 H0 0.0000 0.0000 A 2.47135e-01 6.56888e-02 amber99_1 BR 0.0000 0.0000 A 0.00000e+00 0.00000e+00 amber99_2 C 0.0000 0.0000 A 3.39967e-01 3.59824e-01 amber99_3 CA 0.0000 0.0000 A 3.39967e-01 3.59824e-01 amber99_4 CB 0.0000 0.0000 A 3.39967e-01 3.59824e-01 amber99_5 CC 0.0000 0.0000 A 3.39967e-01 3.59824e-01 amber99_6 CK 0.0000 0.0000 A 3.39967e-01 3.59824e-01 amber99_7 CM 0.0000 0.0000 A 3.39967e-01 3.59824e-01

  9. Target data • Experimental: vibrational spectra; heats of vaporization; densities; solvation free energies; microwave, electron, or X-ray diffraction structure; and relative conformational energies and barrier heights. • QM: vibrational spectra; minimum energy geometries; dipole moments; conformational energies and barrier heights; electrostatic potentials; and dimerization energies • The Amber, CHARMM, GROMOS, and OPLS-AA force field for proteins each target a different subset of the possible experimental and QM data, although there is substantial overlap between the subsets.

  10. AMBER • AMBER84: Polar hydrogens + united atoms ( hydrogens bonded to carbon) • AMBER86: All- atom model • Based on experimental with gas phase simulation • Key ideas: • ESP partial charge ( qi , qj ) • ( Kb , b0 , Ksita , Sita0 ) from crystal structures, match NMF for peptide fragments • VDW fits amide crystal data • Dihedral match torsional barriers from experiments and quantum calculations

  11. AMBER94: Aimed to better perform Condensed phase simulations • Partial charges: • Dependency on environments: RESP • Dependency on conformations: fit simultaneously with multiple configurations • More accurate electron correlation method and larger basis set to determine torsional terms • AMBER96,99 • Account long-range effects • Fit tetrapeptide + dipeptide • AMBER03 • More accurate electron correlation method and larger basis set to determine torsional terms and partial charges • Continuum solvent models instead of vacuum

  12. CHARMM • Key idea: • Balancing water-protein, water-water, and protein-protein interaction energies in the condensed phase • Difference: • Dimerization energies, molecule-water minimum-energy distances OPLS-AA GROMOS

  13. 6. Comparison of force field in realization Favor • Alpha-helix: Amber 94, 99 • Beta-hairpin: GROMOS96 • Intermediate: CHARMM22, AMBER96, OPLS-AA/L Experimental agreement • Alpha-helix: • Remarkable agreement: Amber 99, CHARMM22 • Consistent with some experiments: AMBER96, OPLS-AA/L • Disagreement: AMBER94, GROMOS96 • Beta-hairpin: • Remarkable agreement: OPLS-AA/L, GROMOS96 • Consistent with some experiments: AMBER96 • Disagreement: AMBER94, AMBER99, CHARMM22

  14. THANK YOU

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