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Title: Electrostatics: DebyeHckel Theory and Computational Methods


1
Electrostatics Debye-Hückel Theory and
Computational Methods
  • Bio 5312
  • March 14-18, 2005
  • Nathan Baker
  • (baker_at_biochem.wustl.edu)

2
Biomolecular charge distributions proteins
  • Amphoteric range of titratable groups
  • Range of isoelectric points (calculated)
  • End result zwitterionic with a wide range of
    charge densities

3
Biomolecular charge distributions nucleic acids
  • dsDNA
  • Approx. linear form
  • Close phosphate spacing
  • B-form phosphate spacing 3.4 Å
  • RNA
  • Structural diversity
  • Dense phosphate packing

11 bp B-form DNA (1AGH)
23s rRNA (1FFZ)
4
Biomolecular charge distributions other
molecules
  • Sugars
  • Glycosaminoglycans (GAGs)
  • Cellular matrix
  • Cell surface co-receptors
  • Potentially high charge density
  • Proteoglycans GAGs attached to proteins by
    glycosylation
  • Membranes
  • Phospholipids
  • Zwitterionic (phosphatidyl-choline,
    phosphatidyl-ethanolamine, sphingo-myelin)
  • Anionic (phosphatidyl-serine)
  • Other components

Dermatan sulfate. (Picture from Alberts et al)
Electrostatic potential of POPC membrane.
5
How solvent interacts with biomolecules
  • Water properties
  • Dipolar solvent (1.8 D)
  • Hydrogen bond donor and acceptor
  • Polarizable
  • Functional behavior
  • Bulk polarization
  • Site binding or specific solvation
  • Preferential hydration
  • Acid/base chemistry

Carbonic anhydrase reaction mechanism (Stryer,
Biochemistry)
Spine of hydration in DNA minor groove (Kollman
et al)
6
How ions interact with biomolecules
  • Non-specific screening effects
  • Depends only on ionic strength (not species)
  • Results of damped electrostatic potential
  • Described by Debye-Hückel and Poisson-Boltzmann
    theory for low concentration
  • Influences
  • Described throughout these lectures
  • Binding constants
  • Rates??

Electrostatic potential of AChE at 0 mM and 150
mM NaCl. Rate and binding affinity decrease with
NaCl has been attributed to screening effects
although species-dependent influences have been
observed. Radic Z, Kirchhoff PD, Quinn DM,
McCammon JA, Taylor P. 1997. J Biol Chem 272
(37) 23265-23277.
7
How ions interact with biomolecules
  • Site-specific binding
  • Ion-specific
  • Site geometry, electrostatics, coordination, etc.
    enables favorable binding
  • Influences co-factors, allosteric activation,
    folding (RNA)

Site of sodium-specific binding in thrombin.
Sodium binding converts thrombin to a
procoagulant form by allosterically enhancing the
rate and changing substrate specificity. Pineda
AO, Carrell CJ, Bush LA, Prasad S, Caccia S, Chen
ZW, Mathews FS, Di Cera E. 2004. J Biol Chem 279
(30) 31842-53.
8
How ions interact with biomolecules
  • Non-specific screening effects
  • Depends only on ionic strength (not species)
  • Results of damped electrostatic potential
  • Described by Debye-Hückel and Poisson-Boltzmann
    theory for low concentration
  • Site-specific binding
  • Ionic specific (concentration of specific ion,
    not necessarily ionic strength)
  • Site geometry, electrostatics, coordination, etc.
    enables favorable binding
  • Influences
  • Co-factors
  • Allosteric activation
  • Folding (RNA)
  • Hofmeister effects (preferential hydration)
  • Partitioning of ions between water and
    non-specific sites on biomolecule
  • Dependent on ion type (solvation energy, etc.)
  • Dominate at high salt concentrations
  • Influences
  • Protein stability
  • Membrane structure and surface potentials
  • Protein-protein interactions

9
MODELS OF SOLVENT
  • Explicit
  • Quantum mechanical
  • Polarizable
  • Monte Carlo and molecular dynamics
  • Integral equations
  • RISM
  • 3D HNC
  • DFT
  • Implicit solvent
  • Coulombs law
  • Poisson equation
  • Phenomenological
  • Generalized Born
  • Modified Coulomb

Level of detail or Computational cost
10
Coulombs law
Charge magnitudes (C)
  • Every model uses Coulombs law (somewhere)
  • Phenomenological model circa 1785 for
    charge-charge interactions in a vacuum
  • Relates potential to charge for homogeneous
    dielectric materials
  • Provides superposition of potentials
  • Assumptions
  • Homogeneous dielectric
  • Point charges
  • No mobile ions
  • Infinite boundaries

Solvent dielectric (unitless)
Distance (m)
Vacuum permittivity (8.85410-12 C2 J-1 m-1)
11
Coulombs law
Point charge
Laplacian
  • Actually a Green function
  • Solution to a PDE with
  • Particular boundary conditions (infinite)
  • Delta function source
  • Can be used to find potentials for arbitrary
    charge distributions

Boundary condition
12
Coulombs law energies
  • Energy is the integral of the potential with the
    charge distribution
  • The Green function provides the interaction
    kernel
  • Point charges are particularly easy
  • Self energies are usually removed

13
Bjerrum length fundamental length scale for
Coulombs law
  • What is the distance at which two unit charges
    interact with kT of energy? Bjerrum length
  • A useful length scale for determining when
    electrostatic interactions are on the same order
    as thermal energy
  • Approximately 7 Å for water (e 80) at 298 K

Boltzmanns constant (1.3810-23 J K-1)
Electron charge (1.6010-19 C)
14
Explicit solvent simulations
  • Sample the configuration space of the system
  • Ions
  • Atomically-detailed water
  • Solute
  • Simulation performed under particular macroscopic
    conditions
  • Constant number/chemical potential
  • Constant pressure/volume
  • Constant temperature/energy
  • Algorithms
  • Molecular dynamics integrate equations of
    motion
  • Monte Carlo randomly sample coordinates

15
Electrostatics in explicit solvent simulations
  • Charge descriptions
  • Fixed monopoles (dipoles, quadrupoles, etc.)
  • Polarization induced charge
  • Observables
  • Average potential, energy, etc. over simulation
  • Potentials of mean force interaction averaged
    over a reaction coordinate

16
Boundary conditions in explicit solvent
simulations
  • Electrostatic interactions have infinite range
  • Simulations can only include a finite number of
    degrees of freedom
  • What happens outside the simulation box?
  • Periodic boundaries
  • Pro Infinite system
  • Con Artificial order
  • Finite simulation domain
  • Pro No artificial order
  • Con Boundary effects

17
Explicit solvent simulations pros and cons
  • Advantages
  • High levels of detail
  • Easy inclusion of additional degrees of freedom
  • All interactions considered explicitly
  • Disadvantages
  • No simple theories available
  • Slow (and uncertain) convergence
  • Time-consuming
  • Boundary effects
  • Poor scaling to larger systems
  • Some effects still not considered in many force
    fields

18
Distribution theories
  • Provide average information what is the
    probability of finding a molecule at a specific
    position with a given configuration?
  • Example what is the probability of finding
    argon a certain distance from a hard sphere?
  • Example what is the probability of finding a
    (rigid) water molecule 3 Å from a spherical ion
    with its dipole pointing toward the ion?

19
Distribution theories
  • Offer static information about molecular
    distributions
  • Solvent density and polarization
  • Ion density
  • Average forces, free energies, potentials of mean
    force
  • Very complicated formulations
  • Integral equations (hard to solve)
  • Statistical mechanics
  • Approximate
  • Difficult to include dynamic information

20
Poisson equation
  • Can be derived from distribution theories
  • Assume dipolar hard sphere solvent for water no
    quadrupole moment, hydrogen bonding, or
    shape-dependent packing
  • Assume local response to applied field no
    water-water correlations
  • Assume linear response to applied field
    infinitely-small water, no dielectric saturation
  • Can be derived from standard free energy
    functionals identify dielectric coefficient as
    response function for potential
  • Probably easier to think of based on Coulombs
    law
  • Generalize to inhomogeneous dielectric coefficient

21
Dielectric coefficients
22
Molecular dielectric functions
  • A heterogeneous molecule like a biomolecule
    shouldnt really be represented by a continuum
    dielectric
  • however, that doesnt keep people from trying
  • Multiple dielectric values
  • 1 vacuum
  • 2-4 atomic polarizability (solid)
  • 4-10 some libration, minor sidechain
    rearrangement
  • 10-20 significant internal rearrangement
  • Multiple surface definitions
  • van der Waals
  • Splines
  • Molecular surface

23
Poisson equation
  • Describes electrostatic potential due to
  • Inhomogeneous dielectric
  • Charge distribution
  • Assumes
  • Linear and local solvent response
  • No mobile ions

24
Poisson equation energies
  • Total energies obtained from
  • Integral of polarization energy
  • Sum of charge-potential interactions

25
Poisson equation energies
  • Total energies obtained from
  • Integral of polarization energy
  • Sum of charge-potential interactions
  • Numerically-calculated energies contain
    self-interaction terms
  • Infinite (for analytic solution)
  • Very unstable (for numerical solution)
  • Self-interactions must be removed

26
The reaction field
  • The potential due to inhomogeneous polarization
    of the solvent
  • The difference of potentials with
  • Inhomogeneous dielectric
  • Homogeneous dielectric
  • Implicitly removes terms due to
    self-interactions
  • Non-singular
  • Numerically-stable
  • Not available via simpler models

Reaction field
27
Solvation energy
  • Solvation energies obtained directly from
    reaction field
  • Difference of
  • Homogeneous
  • Inhomogeneous
  • dielectric calculations
  • Self-energies removed in this process
  • Numerical stability
  • Non-infinite results

28
Born ion
  • What is the energy of transferring a
    non-polarizable ion from vacuum to solvent?
  • We could use the energy formulas shown earlier
  • but its easier to consider this as a charging
    process
  • Free energy for charging/discharging sphere in
    solvent/vacuum
  • No polar energy for transferring uncharged sphere
    to solvent

29
Born ion
  • Integrate polarization for dielectric media
  • Assume ion is non-polarizable
  • Subtract energies between media

30
A continuum descriptionof ion desolvation
  • Two Born ions at varying separations
  • Solve Poisson equation at each separation
  • Increase in energy as water is squeezed out of
    interface
  • Desolvation effect
  • Less volume of polarized water
  • Important points
  • Non-superposition of Born ion potentials
  • Reaction field causes repulsion at short
    distances
  • Dielectric medium focuses field

31
A continuum descriptionof ion desolvation
32
From last time
  • Notes available on class web site
  • Does everybody know what these are?
  • Accidentally deleted Born ion example (its OK.
    though well see it later today)

33
MODELS OF IONS
  • Primitive solvent models
  • Ions included explicitly
  • Ions included as distribution functions
  • Continuum models
  • Debye-Hückel
  • Manning-Oosawa
  • Possion-Boltzmann

34
Debye-Hückel theory
  • Suppose we have several species of ions with
    different charges in an external field or
    potential
  • Assume a Boltzmann-like probability for finding
    an ion at a specific position
  • Given this probability, what is the charge
    density due to all the ions?
  • What if the charge-potential interaction energy
    is very small?

35
Debye-Hückel theory
  • Now assume the system of ions is electroneutral
  • Consider these system of ions in the presence of
  • homogeneous dielectric
  • fixed charge distribution one that does not
    respond to potential changes
  • Use the Poisson equation from above
  • Factor out the Debye parameter

36
Debye-Hückel theory
  • The resulting equation is a Helmholtz equation
  • For point charges, the solution is the
    superposition of Helmholtz Green functions
  • The solutions decay much more rapidly due to
    ionic screening

37
Debye-Hückel theory
  • The energies are calculated in the usual way
  • We can also infer ion number and charge
    distributions

38
Debye length fundamental length scale for
Debye-Hückel theory
Avogadros (6.021023 mol-1)
Electron charge (1.6010-19 C)
Species charge (e)
Species concentration (M)
Ionic strength (M)
For water (e80) at 298 K
  • Debye parameter represents effective screening of
    potential
  • Inverse parameter is Debye length

39
Debye length fundamental length scale for
Debye-Hückel theory
  • Introduces a characteristic length
  • Also gives the maximum for the charge density
    distribution

40
Chemical potential a review
  • Measures the change in free energy upon a change
    in particle number
  • Given with respect to a standard state
  • Ideal chemical potential
  • Non-interacting components
  • Uses concentrations or mole fractions
  • Excess chemical potential
  • Measures non-ideality
  • Uses activities
  • Activity coefficient measures deviation from
    ideality

41
DH theory and thermodynamics
  • DH theory describes activity coefficients for
  • Simple electrolytes
  • At low ionic strengths (I lt10-3 M)
  • When only non-specific electrostatics matters
  • Need to solve for the electrostatic potential for
    a finite size ion (radius a) in electrolyte
    solution
  • Write solution as
  • Contribution from central ion
  • Contribution from electrolyte solution

Surface potential due to electrolyte solution
42
DH theory and thermodynamics
  • What is the energy of inserting an ion into
    solution? Chemical potential
  • Guntelberg charging calculate the energy due to
    mobile counterions for
  • Creating the cavity (zero in this model)
  • Charging the cavity
  • Result single-ion activity coefficients

43
DH theory and thermodynamics
  • Unfortunately, single ion activities cant be
    measured
  • However, we can use the property of chemical
    potentials at equilibrium to relate individual
    species activities to salt
  • This defines a mean activity coefficient for the
    salt

44
Debye-Hückel activity coefficients
  • Mean activity coefficient can be determined by
  • Approximating the single-ion coefficients by DH
    theory
  • Approximately equal ionic radii
  • Enforcing electroneutrality

Monovalents
Divalents
45
Limitations of Debye-Hückel
  • Remember this works best for low ionic
    strengths where ion-ion and ion-solvent
    interactions dont matter

Meissner HP, Tester JW. Activity coefficients of
strong electrolytes in aqueous solutions. Ind.
Eng. Chem. Process Des. Develop. 11 (1) 128-133,
1972.
46
APPLICATION TO BIOLOGY
  • Provides simple model for interpreting
    non-specific salt effects on
  • Solubility
  • Binding constants
  • Rate constants
  • Wide range of other applications
  • Virial coefficients
  • Solution osmotic pressure
  • Ionic conductances (Debye-Hückel-Onsager)
  • Keep theorists busy

Be careful is the effect really due to ionic
strength independent of valency or species?
47
Solubility
  • Solubility products can be written in terms of
    mean activities (activity of solid 1)
  • Inert strong electrolytes
  • Decrease mean activities according to DH theory
  • Leave solubility coefficient unchanged
  • Therefore aqueous concentrations increase with
    inert electrolyte concentration (until DH
    limits) salting in

48
Solubility
  • However, activity coefficients dont necessary
    decrease for all concentrations of inert
    electrolyte
  • DH range of concentrations predict salting in
  • Larger concentrations may cause salting out

Salting in
Salting out
Reference solubility
49
Binding constants
  • Similar arguments as solubility
  • Care must be taken to identify an inert salt
  • Only works for very simple, non-specific binding
    models
  • Extensions possible with more complicated models
    (Poisson-Boltzmann, etc.)

50
MORE COMPLICATED MODELS
  • Primitive solvent, explicit ion simulations
  • Integral equation theories
  • Manning-Oosawa models of counterion condensation
  • Explict ion-ion correlations
  • Anything from plasma physics

51
COMPUTATIONAL APPROACHES
Computation
Theory
52
Why is theory useful?
  • Interpretation of data models
  • Map observations onto physical principles
  • Generate models of system behavior
  • Better understanding
  • Prediction of response to change
  • Engineering
  • Ask why instead of what
  • The best theories are simple
  • Theories do not require theoreticians

53
Why is computation necessary?
  • Although the model might be simple and contain
    few parameters, solving the model for
    observations can be difficult
  • Examples
  • Schrödinger equation
  • Classical force fields and partition functions
  • Differential equations
  • Polymer models of folding

54
Explicit particle simulation recap
  • All atoms treated explicitly
  • Electrostatic interactions handled at Coulombs
    Law level
  • Lots of detail
  • All observables from continuum simulations
  • plus atomic-level information
  • Issues with finite system size
  • Very time-consuming
  • Limits system size
  • Limits accuracy (convergence)

55
CONTINUUM SIMULATIONS
  • The remainder of these lectures applies exactly
    the same principles discussed earlier to systems
    where analytical results are not available
  • We will consider two types of models
  • Simple phenomenological models (modified Coulomb,
    etc.) where there is no obvious way to predict
    the error in the model
  • Poisson-Boltzmann models which rely on similar
    principles to Debye-Hückel and therefore have the
    same limitations
  • These models include detailed structural
    information into the calculation of electrostatic
    interaction energies and forces

56
Simple analytic models
  • Usually phenomenological generalization of
    Poisson or Debye-Hückel models
  • Include
  • Generalized Born (coming up)
  • Distance-modified dielectrics (not a good idea)
  • Surface-based models
  • Coulombs law (often in conjuction with surface
    terms)
  • Most models for apolar contributions are
    phenomenological and/or heuristic

57
Apolar solvation
Figures from Dill KA, Truskett TM, Vlachy V,
Hribar-Lee B. 2005. Modeling water, the
hydrophobic effect, and ion solvation. Annu Rev
Biophys Biomol Struct. Experiments Ar gas ?
water transfer.
  • All of the models we have discussed so far only
    describe polar solvation
  • Interaction of solute with water dipoles
  • Interaction of solute with ions
  • Experimental observations
  • Solubility has temperature minimum
  • Large positive heat capacity
  • Temperature-sensitive (negative) entropy
    structuring of water

58
Apolar solvation
  • What should be included in a model
  • Cavity terms the probability of finding a
    hole (or inert species of a given size) in the
    solvent
  • Weak interactions dispersive and repulsive
    interactions between solute and solvent
  • Careful explicit solvent simulations will include
    these details

Figure from Levy RM, Zhang LY, Gallichio E,
Felts AK. 2003. J Am Chem Soc 125 (31) 9523-9530.
59
Apolar solvation
  • What do we do for implicit solvent models?
  • Cavity terms
  • Scaled particle theory
  • Apolar free energy surface area times surface
    tension coefficient
  • Surface tension coefficient between 25 to 50 cal
    mol-1 (model-dependent)
  • Spolar RS, Ha JH, Record MT, Jr. 1989. Proc Natl
    Acad Sci USA 86 (21) 8382-8385 Sitkoff D, Sharp
    KA, Honig B. 1994. Biophys Chem 51 (2-3)
    397-409.
  • Dispersion/repulsion terms
  • Hard solute
  • Integral of attractive potential over accessible
    space
  • Levy RM, Zhang LY, Gallichio E, Felts AK. 2003. J
    Am Chem Soc 125 (31) 9523-9530.
  • Not widely used!!

60
Generalized Born
  • Used to calculate solvation energies (forces)
  • Modification of Born ion solvation energy
  • Adjust effective radii of atoms based on
    environment
  • Differences between buried and exposed atoms
  • Fast to evaluate
  • Lots of variations
  • Very sensitive to parmeterziation
  • Good parmeterization can give results comparable
    to Poisson-Boltzmann
  • Parameterization should change with conformation

Figure from Onufriev A, Bashford D, Case DA.
2000. J Phys Chem B 104 (15) 3712-3720.
61
Poisson-Boltzmann
  • Same basic principles as Debye-Hückel theory
  • Continuum dielectric (Poisson equation)
  • Non-interacting mobile ions (mean field
    approximation)
  • Same limitations
  • Low ion concentration
  • Low ion valency
  • No specific interactions solute-solvent,
    solute-ion, ion-solvent, ion-ion

62
Poisson-Boltzmann derivation step 1
  • Start with Poisson equation to describe solvation
  • Supplement biomolecular charge distribution with
    mobile ion term

Dielectric function
Biomolecular charge distribution
Mobile charge distribution
63
Poisson-Boltzmann derivation step 2
  • Choose mobile ion charge distribution form
  • Boltzmann distribution ? no explicit ion-ion
    interaction
  • No detailed structure for atom (de)solvation

Ion charges
Ion bulk densities
Ion-protein steric interactions
64
Poisson-Boltzmann derivation step 3
  • Substitute mobile charge distribution back into
    Poisson equation
  • Result Nonlinear partial differential equation

65
Poisson-Boltzmann special cases
  • 11 electrolyte (NaCl)
  • Assume similar steric interactions for each
    species with protein
  • Simplify two-term series to hyperbolic sine

Modified screening coefficient zero inside
biomolecule
11 electrolyte charge distribution
66
Poisson-Boltzmann special cases
  • 11 electrolyte (NaCl)
  • Assume similar steric interactions for each
    species with protein
  • Simplify two-term series to hyperbolic sine
  • Small charge-potential interaction
  • Linearized Poisson-Boltzmann
  • Homogeneous dielectric PB ? Debye-Hückel

67
Poisson-Boltzmann energies
  • Similar to Poisson equation
  • Functional integral over solution domain
  • Solution extremizes free energy
  • Basis for calculating forces
  • Charge-field
  • Dielectric boundary
  • Osmotic pressure

Fixed charge- potential interactions
Dielectric polarization
Mobile charge energy
68
Solving the PE or PBE
  • Determine the coefficients based on the
    biomolecular structure
  • Discretize the problem
  • Solve the resulting linear or nonlinear algebraic
    equations

69
Equation coefficients charge distribution
  • Charges are delta functions hard to model
  • Often discretized as splines to smooth the
    problem
  • What about higher-order charge distributions?

70
Equation coefficients mobile ion distribution
  • Provides
  • Bulk ionic strength
  • Ion accessibility
  • Usually constructed based on inflated van der
    Waals radii

71
Equation coefficients dielectric function
  • Describes change in dielectric response
  • Low dielectric interior (2-20)
  • High dielectric solvent (80)
  • Many definitions
  • Molecular (solid line)
  • Solvent-accessible (dotted line)
  • van der Waals (gray circles)
  • Inflated van der Waals (previous slide)
  • Smoothed definitions (spline-based and Gaussian)
  • Results can be very sensitive to the choice of
    surface!!!

72
Discretization
  • Choose your problem domain finite or infinite?
  • Usually finite domain
  • Requires relatively large domain
  • Uses asymptotically-correct boundary condition
    (e.g., Debye-Hückel, Coulomb, etc.)
  • Infinite domain requires appropriate basis
    functions
  • Choose your basis functions global or local?
  • Usually local map problem onto some sort of
    grid or mesh
  • Global basis functions (e.g. spherical harmonics)
    can cause numerical difficulties

73
Discretization local methods
  • Polynomial basis functions (defined on interval)
  • Locally supported on a few grid points
  • Only overlap with nearest-neighbors ? sparse
    matrices

Boundary element (Surface discretization)
Finite element (Volume discretization)
Finite difference (Volume discretization)
74
Discretization pros cons
  • Finite difference
  • Sparse numerical systems and efficient solvers
  • Handles linear and nonlinear PBE
  • Easy to setup and analyze
  • Non-adaptive representation of problem
  • Finite element
  • Sparse numerical systems
  • Handles linear and nonlinear PBE
  • Adaptive representation of problem
  • Not easy to setup and analyze
  • Less efficient solvers
  • Boundary element
  • Very adaptive representation of problem
  • Surface discretization instead of volume
  • Not easy to setup and analyze
  • Less efficient solvers
  • Dense numerical system
  • Only handles linear PBE

75
Basic numerical solution
  • Iteratively solve matrix equations obtained by
    discretization
  • Linear multigrid
  • Nonlinear Newtons method and multigrid
  • Multigrid solvers offer optimal solution
  • Accelerate convergence
  • Fine ? coarse projection
  • Coarse problems converge more quickly
  • Big systems are still difficult
  • High memory usage
  • Long run-times
  • Need parallel solvers

76
Errors in numerical solutions
  • Electrostatic potentials are very sensitive to
    discretization
  • Grid spacings lt 0.5 Å
  • Smooth surface discretizations
  • Errors most pronounced next to biomolecule
  • Large potential and gradients
  • High multipole order
  • Errors decay with distance
  • Approximately follow multipole expansion behavior
  • Coarse grid spacings will correctly resolve
    electrostatics far away from molecule

77
Sequential focusing
  • Finite difference
  • What should we do if were only interested in a
    part of the protein?
  • Use a coarse mesh for the whole domain
  • Use a fine mesh for the region of interest
  • Coarse mesh solution sets fine mesh boundary
    conditions
  • Sequential focusing algorithm
  • Useful for site-specific calculations (binding,
    pKa, etc.)
  • Uses multipole behavior of error

78
Parallel focusing
  • Finite difference
  • Extension of sequential focusing to large systems
  • Parallel runs of sequential focusing
  • Focus to overlapping finer grids
  • Provide coverage for all or subset of domain
  • Energies obtained from disjoint partitions
  • Details
  • Good parallel scaling
  • Easy implementation
  • Amenable to dynamics

79
Electrostatics Software
80
APPLICATIONS OF CONTINUUM ELECTROSTATICS
  • Thermodynamics
  • Basic concepts
  • Solvation energies
  • Binding energies
  • Acid dissociation constants
  • Equilibrium ion distributions
  • Kinetics
  • Rate constant calculations
  • Molecular dynamics simulation
  • Other
  • Structural analysis
  • Classification

81
PB energy calculations
  • Beware self energies!
  • Energies calculated with PB equation contain
    self-interaction terms
  • These terms tend toward infinity for small grid
    spacings
  • These terms are very sensitive to the system
    setup artifacts
  • Solution
  • Perform reference calculation with the same
    grid setup, etc.
  • This removes the self-energy artifacts by
    cancellation
  • The most natural reference calculation is a
    solvation energy

82
Solvation energy
  • Physical model transfer solute from dielectric
    of 1 (vacuum) to 80 (water)
  • Computational model transfer solute from
    homogeneous dielectric to inhomogeneous
    dielectric eliminate self-interaction terms
  • Two models can be reconciled through free energy
    cycle set the reference state

83
Solvation energy two Born ions
  • Water dielectric
  • Two ions
  • 3 Å radii
  • Internal dielectric of 1
  • Opposite charges of 1 e
  • Basic calculation
  • Calculate solvation energies of isolated ions
  • Calculate solvation energy of complex
  • Subtract solvation energies
  • Add in Coulombs law attraction

84
Binding energy
  • This calculation assumes no conformational
    change!
  • Separate calculation into two steps
  • Calculate electrostatic interaction in
    homogeneous dielectric (Coulombs law)
  • Calculate solvation energy change upon binding
    (Poisson or Poisson-Boltzmann equation)
  • Self-interactions are removed in solvation energy
    calculation

85
Binding energy example
  • Protein kinase A inhibition by balanol
  • Wong CF, Hunenberger PH, Akamine P, Narayana N,
    Diller T, McCammon JA, Taylor S, Xuong NH. 2001.
    J Med Chem 44 (10) 1530-1539.
  • Continuum electrostatics predicts binding
    affinities of several inhibitors for 400 kinases

86
Binding energy example
  • Zero (low) ionic strength, dielectric
    coefficients of 2 and/or 80, molecular surface
    definition (sensitivity!)
  • No structural rearrangement (based on X-ray
    structure)
  • Procedure
  • Calculate solvation and Coulombic energy of
    inhibitor
  • Calculate solvation and Coulombic energy of PKA
  • Calculate solvation and Coulombic energy of
    complex
  • Results show good trend with experimental
    measurements
  • Used to parameterize QSAR model


87
Conformational changes
  • Same concepts as binding energy calculation
  • Calculate electrostatic energy due to
    configuration change in homogeneous dielectric
    (Coulombs law)
  • Calculate electrostatic energy due to change in
    solvation between configurations (Poisson or
    Poisson-Boltzmann)

88
pKa calculations
89
pKa calculations
  • Want acid dissociation constant for residues in a
    particular structural context
  • Use model pKas for amino acids
  • Calculate pKa from two binding calculations
  • Binding of unprotonated residue
  • Binding of protonated residue
  • Consider two conformational distributions for
    protein?

90
Force calculations
  • Energy gradients can be obtained from PB
    calculations
  • Useful for
  • Structure minimization
  • Docking
  • Dynamics
  • Obtained by functional differentiation of PB
    free energy with respect to atom positions

Animation from Dave Sept.
Charge-field interaction
Dielectric boundary force
Osmotic pressure
91
Application to microtubules
  • Important cytoskeletal components structure,
    transport, motility, division
  • Typically 250-300 Å in diameter and up to
    millimeters in length
  • Computationally difficult due to size (1,500
    atoms/Å ) and charge (-4.5 e/Å)
  • Solved LPBE at 150 mM ionic strength on 686
    processors for 600 Å-long, 1.2-million-atom
    microtubule
  • Resolution to 0.54 Å for largest calculation
    quantitative accuracy

92
Application to microtubules
93
Application to microtubules
94
Microtubule stability and assembly
  • Performed series of calculations on tubulin
    dimers and protofilament pairs
  • Poisson-Boltzmann electrostatics and SASA apolar
    energies
  • Observed 7 kcal/mol stronger interactions between
    protofilaments than within
  • Determined energetics for helix properties
    predict correct minimum for experimentally-observe
    d A (52 Å) and B (8-9 Å) lattices

95
Microtubule stability and assembly
96
Microtubule stability and assembly
97
Quantitative analysis of electrostatic potentials
  • Do electrostatic potentials tell us anything
    about biomolecular function?
  • Ligand binding sites?
  • Biomolecular binding sites?
  • Active sites or shifted pKas?
  • Structural destabilization?
  • Are we learning anything that couldnt be learned
    from structure or sequence analysis methods?

98
Breakdown of implicit solvent models
  • Is the water near a zwitterionic bilayer a
    featureless dielectric continuum?
  • Examine behavior of TIP3P water around POPC
    bilayer using molecular dynamics
  • Systematically replace each layer of explicit
    solvent with dielectric continuum and calculate
    potential
  • Average results over MD trajectory
  • Determine
  • Nature of water at membrane surface
  • Discrepancies between implicit and explicit
    electrostatics

99
Water around membrane systems results
  • 4 layers of water significantly different than
    bulk
  • Dielectric response (orientational fluctuations)
    of water near membrane much lower
  • Membrane potential dramatically affected by water
    polarization
  • Conclusion Water near membrane has
    significantly different structure and response
    properties from bulk
  • Future work non-neutral membranes and mobile
    ions

100
Breakdown of the implicit ion model
  • Canonical electrostatics test case
    non-polarizable hard sphere with point charge
  • Mild test of continuum electrostatics (no
    condensation, etc.)
  • Good agreement with mean-field results at low
    mobile ion concentrations
  • Agreement deteriorates with
  • Increasing macroion charge
  • Increasing mobile ion concentration

101
Breakdown of the implicit ion model
102
Ions around DNA
  • NPBE simulations predict 2000 M Mg near DNA
    surface for 20 mM MgCl2, 150 mM NaCl solution
  • Ran GCMC calculations for similar conditions
    around 20 bp D-DNA
  • Observe max density of 10 M Mg in GCMC
    simulations
  • Much lower than PBE results
  • Implicit solvent model questionable
  • Reproduce expected condensation behavior
  • 88 charge compensation at 17 Å radius
  • Divalent cations affect charge screening

103
Ions around DNA
104
Ions around DNA
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