ImplicitSolvationModels Overview Solvation and Macromolecular Structure The structure and dynamics of biological macromolecules are strongly influenced by water: Electrostatic effects: charges are screened by water molecules and counterions. Hydrophobic effect: Entropic forces favor conformations that sequester non-polar hydrophobic domains within the interior of the molecule. Hydrodynamic effects: collision with solvent molecules imparts kinetic energy to macromolecules. JayTaylor (ASU) APM530-Lecture6 Fall2010 1/32 ImplicitSolvationModels Overview Solvation of Nucleic Acids Solvent effects on DNA and RNA are especially pronounced: Screening of the negatively-charged phosphates by water and counterions stabilizes helical and other tertiary structural motifs. ∼76% of the charge is reduced by water; ∼24% is reduced by divalent counterions. The transition between A-form and B-form DNA is partly controlled by hydration: B-DNA has 18-30 waters per nucleotide. A-DNA has 10-15 waters per nucleotide. DNA bending is promoted by hydration of the phosphates. JayTaylor (ASU) APM530-Lecture6 Fall2010 2/32 ImplicitSolvationModels Overview DNA is surrounded by multiple layers of water. Water density is increased up to six-fold in the first layer, especially around the phosphates and in the minor and major groove. A less stable second hydration shell extends out to 10˚A. A spine of hydration runs through the minor groove. JayTaylor (ASU) APM530-Lecture6 Fall2010 3/32 ImplicitSolvationModels Overview Explicit Solvation Models Solvent effects must also be included in molecular simulations. One approach is to explicitly include a large number of solvent molecules surrounding the macromolecule. Boundary conditions are usually periodic. Counterions can also be explicitly modeled. A large number of solvent molecules is generally required: Approximately 3000 waters are needed in a simulation of a 10 bp DNA duplex. Solvent viscosity leads to slower sampling of conformational space. JayTaylor (ASU) APM530-Lecture6 Fall2010 4/32 ImplicitSolvationModels Overview Implicit Solvation Models Implicit solvent models represent the solvent and counterions as a continuous medium. Implicit simulations can usually be run more quickly than explicit simulations. We are usually not interested in the distribution of individual water molecules in the solvent-solute interface. Residence times of water in DNA vary from hundreds of picoseconds to nanoseconds in the minor groove of A-tracts. Several methods are available: Solvent accessible surface area models Poisson-Boltzmann equation Generalized Born models JayTaylor (ASU) APM530-Lecture6 Fall2010 5/32 ImplicitSolvationModels SASAmodels Solvent Accessible Surface Area SASA models express the free energy of solvation as a sum (cid:88) ∆Gsolv = σ ASA i i i where the sum is over all atoms in the macromolecule; ASA is the surface area of atom i accessible to the solvent; i σ is an atom-specific surface tension parameter. i The parameters σ have been estimated from empirical hydration free i energies for various organic compounds in water. JayTaylor (ASU) APM530-Lecture6 Fall2010 6/32 ImplicitSolvationModels SASAmodels Accessible Surface Area Calculations Atoms and solvent molecules are both modeled as spheres. The ASA of an atom is the area of those points on the surface of a sphere of radius R which can contact the center of a spherical solvent molecule that intersects no other atoms. R is the sum of the van der Walls radius of the atom and the radius of the solvent molecule (1.4˚A for water). JayTaylor (ASU) APM530-Lecture6 Fall2010 7/32 ImplicitSolvationModels SASAmodels Shrake-Rupley Algorithm The Shrake-Rupley algorithm (1973) uses a discretization of the molecular surface to estimate ASA: 92 points are distributed uniformly along a sphere centered at each atom with radius R (defined on the previous slide). The ASA is estimated by calculating the proportion of points that can be contacted by a solvent molecule that intersects no other atoms. Related methods approximate the surface using polyhedra. Gradients of discretized ASA-estimates must be evaluated numerically. JayTaylor (ASU) APM530-Lecture6 Fall2010 8/32 ImplicitSolvationModels SASAmodels Linear Combination of Pairwise Overlaps Weiser et al. (1999) proposed an approximate analytical expression for the ASA based on an inclusion-exclusion-like formula: (cid:88) (cid:88) A ≈ P S +P A + (P +P A )A i 1 i 2 ij 3 4 ij jk j∈N(i) j,k∈N(i) k(cid:54)=j S is the surface area of atom i. i A is the surface area of sphere i buried inside sphere j. ij N(i) is the neighbor list of atom i. P - P were calculated using least squares regression. 1 4 The relative error is in the range 0.1−7.8%. The resulting formula can be differentiated. JayTaylor (ASU) APM530-Lecture6 Fall2010 9/32 ImplicitSolvationModels SASAmodels Limitations of SASA Models SASA models have several important limitations: Solvation free energies are not linearly related to surface area, e.g., SASA overestimates hydration free energies of cyclic alkanes. The solvation free energy calculated using SASA ignores the electrostatic effects of the solvent. SASA does not account for interactions between the solvent and polar atoms that are buried in the interior of the macromolecule. JayTaylor (ASU) APM530-Lecture6 Fall2010 10/32
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