
- •Foreword
- •Preface
- •Contents
- •Introduction
- •Oren M. Becker
- •Alexander D. MacKerell, Jr.
- •Masakatsu Watanabe*
- •III. SCOPE OF THE BOOK
- •IV. TOWARD A NEW ERA
- •REFERENCES
- •Atomistic Models and Force Fields
- •Alexander D. MacKerell, Jr.
- •II. POTENTIAL ENERGY FUNCTIONS
- •D. Alternatives to the Potential Energy Function
- •III. EMPIRICAL FORCE FIELDS
- •A. From Potential Energy Functions to Force Fields
- •B. Overview of Available Force Fields
- •C. Free Energy Force Fields
- •D. Applicability of Force Fields
- •IV. DEVELOPMENT OF EMPIRICAL FORCE FIELDS
- •B. Optimization Procedures Used in Empirical Force Fields
- •D. Use of Quantum Mechanical Results as Target Data
- •VI. CONCLUSION
- •REFERENCES
- •Dynamics Methods
- •Oren M. Becker
- •Masakatsu Watanabe*
- •II. TYPES OF MOTIONS
- •IV. NEWTONIAN MOLECULAR DYNAMICS
- •A. Newton’s Equation of Motion
- •C. Molecular Dynamics: Computational Algorithms
- •A. Assigning Initial Values
- •B. Selecting the Integration Time Step
- •C. Stability of Integration
- •VI. ANALYSIS OF DYNAMIC TRAJECTORIES
- •B. Averages and Fluctuations
- •C. Correlation Functions
- •D. Potential of Mean Force
- •VII. OTHER MD SIMULATION APPROACHES
- •A. Stochastic Dynamics
- •B. Brownian Dynamics
- •VIII. ADVANCED SIMULATION TECHNIQUES
- •A. Constrained Dynamics
- •C. Other Approaches and Future Direction
- •REFERENCES
- •Conformational Analysis
- •Oren M. Becker
- •II. CONFORMATION SAMPLING
- •A. High Temperature Molecular Dynamics
- •B. Monte Carlo Simulations
- •C. Genetic Algorithms
- •D. Other Search Methods
- •III. CONFORMATION OPTIMIZATION
- •A. Minimization
- •B. Simulated Annealing
- •IV. CONFORMATIONAL ANALYSIS
- •A. Similarity Measures
- •B. Cluster Analysis
- •C. Principal Component Analysis
- •REFERENCES
- •Thomas A. Darden
- •II. CONTINUUM BOUNDARY CONDITIONS
- •III. FINITE BOUNDARY CONDITIONS
- •IV. PERIODIC BOUNDARY CONDITIONS
- •REFERENCES
- •Internal Coordinate Simulation Method
- •Alexey K. Mazur
- •II. INTERNAL AND CARTESIAN COORDINATES
- •III. PRINCIPLES OF MODELING WITH INTERNAL COORDINATES
- •B. Energy Gradients
- •IV. INTERNAL COORDINATE MOLECULAR DYNAMICS
- •A. Main Problems and Historical Perspective
- •B. Dynamics of Molecular Trees
- •C. Simulation of Flexible Rings
- •A. Time Step Limitations
- •B. Standard Geometry Versus Unconstrained Simulations
- •VI. CONCLUDING REMARKS
- •REFERENCES
- •Implicit Solvent Models
- •II. BASIC FORMULATION OF IMPLICIT SOLVENT
- •A. The Potential of Mean Force
- •III. DECOMPOSITION OF THE FREE ENERGY
- •A. Nonpolar Free Energy Contribution
- •B. Electrostatic Free Energy Contribution
- •IV. CLASSICAL CONTINUUM ELECTROSTATICS
- •A. The Poisson Equation for Macroscopic Media
- •B. Electrostatic Forces and Analytic Gradients
- •C. Treatment of Ionic Strength
- •A. Statistical Mechanical Integral Equations
- •VI. SUMMARY
- •REFERENCES
- •Steven Hayward
- •II. NORMAL MODE ANALYSIS IN CARTESIAN COORDINATE SPACE
- •B. Normal Mode Analysis in Dihedral Angle Space
- •C. Approximate Methods
- •IV. NORMAL MODE REFINEMENT
- •C. Validity of the Concept of a Normal Mode Important Subspace
- •A. The Solvent Effect
- •B. Anharmonicity and Normal Mode Analysis
- •VI. CONCLUSIONS
- •ACKNOWLEDGMENT
- •REFERENCES
- •Free Energy Calculations
- •Thomas Simonson
- •II. GENERAL BACKGROUND
- •A. Thermodynamic Cycles for Solvation and Binding
- •B. Thermodynamic Perturbation Theory
- •D. Other Thermodynamic Functions
- •E. Free Energy Component Analysis
- •III. STANDARD BINDING FREE ENERGIES
- •IV. CONFORMATIONAL FREE ENERGIES
- •A. Conformational Restraints or Umbrella Sampling
- •B. Weighted Histogram Analysis Method
- •C. Conformational Constraints
- •A. Dielectric Reaction Field Approaches
- •B. Lattice Summation Methods
- •VI. IMPROVING SAMPLING
- •A. Multisubstate Approaches
- •B. Umbrella Sampling
- •C. Moving Along
- •VII. PERSPECTIVES
- •REFERENCES
- •John E. Straub
- •B. Phenomenological Rate Equations
- •II. TRANSITION STATE THEORY
- •A. Building the TST Rate Constant
- •B. Some Details
- •C. Computing the TST Rate Constant
- •III. CORRECTIONS TO TRANSITION STATE THEORY
- •A. Computing Using the Reactive Flux Method
- •B. How Dynamic Recrossings Lower the Rate Constant
- •IV. FINDING GOOD REACTION COORDINATES
- •A. Variational Methods for Computing Reaction Paths
- •B. Choice of a Differential Cost Function
- •C. Diffusional Paths
- •VI. HOW TO CONSTRUCT A REACTION PATH
- •A. The Use of Constraints and Restraints
- •B. Variationally Optimizing the Cost Function
- •VII. FOCAL METHODS FOR REFINING TRANSITION STATES
- •VIII. HEURISTIC METHODS
- •IX. SUMMARY
- •ACKNOWLEDGMENT
- •REFERENCES
- •Paul D. Lyne
- •Owen A. Walsh
- •II. BACKGROUND
- •III. APPLICATIONS
- •A. Triosephosphate Isomerase
- •B. Bovine Protein Tyrosine Phosphate
- •C. Citrate Synthase
- •IV. CONCLUSIONS
- •ACKNOWLEDGMENT
- •REFERENCES
- •Jeremy C. Smith
- •III. SCATTERING BY CRYSTALS
- •IV. NEUTRON SCATTERING
- •A. Coherent Inelastic Neutron Scattering
- •B. Incoherent Neutron Scattering
- •REFERENCES
- •Michael Nilges
- •II. EXPERIMENTAL DATA
- •A. Deriving Conformational Restraints from NMR Data
- •B. Distance Restraints
- •C. The Hybrid Energy Approach
- •III. MINIMIZATION PROCEDURES
- •A. Metric Matrix Distance Geometry
- •B. Molecular Dynamics Simulated Annealing
- •C. Folding Random Structures by Simulated Annealing
- •IV. AUTOMATED INTERPRETATION OF NOE SPECTRA
- •B. Automated Assignment of Ambiguities in the NOE Data
- •C. Iterative Explicit NOE Assignment
- •D. Symmetrical Oligomers
- •VI. INFLUENCE OF INTERNAL DYNAMICS ON THE
- •EXPERIMENTAL DATA
- •VII. STRUCTURE QUALITY AND ENERGY PARAMETERS
- •VIII. RECENT APPLICATIONS
- •REFERENCES
- •II. STEPS IN COMPARATIVE MODELING
- •C. Model Building
- •D. Loop Modeling
- •E. Side Chain Modeling
- •III. AB INITIO PROTEIN STRUCTURE MODELING METHODS
- •IV. ERRORS IN COMPARATIVE MODELS
- •VI. APPLICATIONS OF COMPARATIVE MODELING
- •VII. COMPARATIVE MODELING IN STRUCTURAL GENOMICS
- •VIII. CONCLUSION
- •ACKNOWLEDGMENTS
- •REFERENCES
- •Roland L. Dunbrack, Jr.
- •II. BAYESIAN STATISTICS
- •A. Bayesian Probability Theory
- •B. Bayesian Parameter Estimation
- •C. Frequentist Probability Theory
- •D. Bayesian Methods Are Superior to Frequentist Methods
- •F. Simulation via Markov Chain Monte Carlo Methods
- •III. APPLICATIONS IN MOLECULAR BIOLOGY
- •B. Bayesian Sequence Alignment
- •IV. APPLICATIONS IN STRUCTURAL BIOLOGY
- •A. Secondary Structure and Surface Accessibility
- •ACKNOWLEDGMENTS
- •REFERENCES
- •Computer Aided Drug Design
- •Alexander Tropsha and Weifan Zheng
- •IV. SUMMARY AND CONCLUSIONS
- •REFERENCES
- •Oren M. Becker
- •II. SIMPLE MODELS
- •III. LATTICE MODELS
- •B. Mapping Atomistic Energy Landscapes
- •C. Mapping Atomistic Free Energy Landscapes
- •VI. SUMMARY
- •REFERENCES
- •Toshiko Ichiye
- •II. ELECTRON TRANSFER PROPERTIES
- •B. Potential Energy Parameters
- •IV. REDOX POTENTIALS
- •A. Calculation of the Energy Change of the Redox Site
- •B. Calculation of the Energy Changes of the Protein
- •B. Calculation of Differences in the Energy Change of the Protein
- •VI. ELECTRON TRANSFER RATES
- •A. Theory
- •B. Application
- •REFERENCES
- •Fumio Hirata and Hirofumi Sato
- •Shigeki Kato
- •A. Continuum Model
- •B. Simulations
- •C. Reference Interaction Site Model
- •A. Molecular Polarization in Neat Water*
- •B. Autoionization of Water*
- •C. Solvatochromism*
- •F. Tautomerization in Formamide*
- •IV. SUMMARY AND PROSPECTS
- •ACKNOWLEDGMENTS
- •REFERENCES
- •Nucleic Acid Simulations
- •Alexander D. MacKerell, Jr.
- •Lennart Nilsson
- •D. DNA Phase Transitions
- •III. METHODOLOGICAL CONSIDERATIONS
- •A. Atomistic Models
- •B. Alternative Models
- •IV. PRACTICAL CONSIDERATIONS
- •A. Starting Structures
- •C. Production MD Simulation
- •D. Convergence of MD Simulations
- •WEB SITES OF INTEREST
- •REFERENCES
- •Membrane Simulations
- •Douglas J. Tobias
- •II. MOLECULAR DYNAMICS SIMULATIONS OF MEMBRANES
- •B. Force Fields
- •C. Ensembles
- •D. Time Scales
- •III. LIPID BILAYER STRUCTURE
- •A. Overall Bilayer Structure
- •C. Solvation of the Lipid Polar Groups
- •IV. MOLECULAR DYNAMICS IN MEMBRANES
- •A. Overview of Dynamic Processes in Membranes
- •B. Qualitative Picture on the 100 ps Time Scale
- •C. Incoherent Neutron Scattering Measurements of Lipid Dynamics
- •F. Hydrocarbon Chain Dynamics
- •ACKNOWLEDGMENTS
- •REFERENCES
- •Appendix: Useful Internet Resources
- •B. Molecular Modeling and Simulation Packages
- •Index

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Figure 4 Free energy surfaces of triiodide ion in various solutions. Contours correspond to isoenergy lines of 1kBT, 2kBT, and 3kBT, respectively.
in the figure, contributions from ∆T pKw,δµ and ∆T pKvacw,elec are very large, but they compensate for each other. The final temperature dependence of pKw is determined by an interplay of several contributions with different physical origins. It is also interesting that the temperature dependence is dominated by ∆T pKw,reorg after the compensation for the largest contributions. The theoretical results for temperature dependence of the ionic product show fairly good agreement with experiments and also demonstrate the importance of polarization effects.
C. Solvatochromism*
The molecular properties of the triiodide ion (I3 ) in polar liquids have been studied by many techniques, motivated in part by the expected strong coupling between the solute I3 electronic structure and the environment. Interestingly, Raman and resonance Raman spectra in several solvents show a weak band corresponding to the antisymmetrical stretch mode, which is expected to be symmetry-forbidden [19], whereas the infrared spectra of many triiodide complexes with cations were also reported to show a band corresponding to the symmetrical stretching mode, which again should be symmetry-forbidden. Ab initio MO calculations for the solvated triiodide ion had been impracticable because of the difficulties in dealing with the character of the solvation, which is strongly coupled with solute electronic structure.
Computed free energy surfaces of the triiodide ion in its ground state in acetonitrile, methanol, and aqueous solution are presented in Figure 4, in which the two IEI bond
* This discussion is based on Ref. 18.

RISM-SCF/MCSCF for Processes in Solutions |
427 |
lengths (R1 and R2) are taken as coordinates. Note that the free energy surface in solution does not correspond to the potential energy surface but governs the relative population of different structures in solution. It would be misleading to estimate vibrational frequencies from the curvature of the surfaces. Contours in the figures represent isoenergy lines of 1 kBT at room temperature, 298.15 K, showing how large a population of triiodide ions exists in the different structures. The free energy profiles in solution strongly depend on the solvent. The profiles in acetonitrile solution are very localized and similar to those in the gas phase, consistent with resonance Raman experimental results in which the symme- try-forbidden band does not appear. The free energy surface in aqueous solution is markedly different and indicates a dramatically enhanced probability of structures with lower symmetry. The observation of nominally symmetry-forbidden bands in vibrational spectra is attributed to these species.
D.Conformational Equilibrium*
The acidity or basicity of organic acids and bases such as carboxylic acid and amines is governed by many factors: solvent, substitution, conformation, and so forth. Among those factors, the effect of conformational change is of special interest in terms of its significance in biological systems. In bimolecular systems such as protein, the acidity or basicity of related functional groups depends sensitively upon the molecular conformations; due to such sensitivity, the property is sometimes exploited to detect the conformational change of protein [21].
A prototype of such phenomena can be seen in even the simplest carboxylic acid, acetic acid (CH3CHOOH). Acidity is determined by the energy or free energy difference between the dissociated and nondissociated forms, whose energetics usually depend significantly on their conformation, e.g., the syn/anti conformational change of the carboxylate group in the compound substantially affects the acid–base equilibrium. The coupled conformation and solvent effects on acidity is treated in Ref. 20.
Potential and potential of mean force curves along the torsional angle θ (HEOECEC) is illustrated in Figure 5. In the gas phase the syn-acetic acid (θ 180°) is more stable than the anti conformer by 6.9 kcal/mol, and the barrier height of rotation between these conformers is estimated as 13.2 kcal/mol. In aqueous solution, the calculated free energy difference is significantly reduced to 1.7 kcal/mol. The rotational barrier also becomes lower than that in the gas phase, 10.3 kcal/mol. The reduction of the free energy gap indicates that the pKa difference between the two conformers is drastically changed from 5.1 to 1.2 on transferring from the gas phase to aqueous solution at room temperature.
Stabilization of the syn conformer in the gas phase is explained rather intuitively in terms of the extra stabilization due to increased interactions between the H atom in the OH group and the O atom in CCO group. As one can see in Figure 5, the extra stabilization in the anti conformer in aqueous solution arises from the solvation energy, especially at the carbonyl oxygen site.
The change in the electronic redistribution on transferring the molecule from the gas phase to aqueous solution is another interesting issue. Analysis of the computed Mulliken charge population demonstrates a substantial change on the hydrogen and oxygen in
* This discussion is based on Ref. 20.

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Figure 5 Calculated potential and potential of mean force of acetic acid along the torsional angle of θ(HEOECEC). The left-hand side shows the total energies and the components, and the righthand side shows the decomposed ∆µ into the site.
the OH group: for the anti-conformer, the partial charges are altered from 0.355 (H) and0.428 (O) to 0.377 (H) and 0.434 (O) upon transfering from the gas to the aqueous solution phases, and for the syn conformer, from 0.373 (H) and 0.463 (O) to 0.395 (H) and 0.476 (O), respectively. One can notice that the character of the proton increases on the hydrogen in the OH group when it is immersed into aqueous solution. (Note that these values are evaluated at the optimized geometry in aqueous solution. Geometrical changes from the gas to aqueous phases should also contribute to the modification of the electron density.)
E.Acid–Base Equilibrium
In this section, we review three studies on the coupled substitution and solvent effects on basicity and acidity.
1. Basicity of the Methylamines in Aqueous Solution*
Basicity and acidity are fundamental and familiar concepts in chemistry and biochemistry. Quantum chemistry has provided a theoretical understanding of the phenomena as far as the gas phase in concerned. However, it is known that in solution reactivity is seriously affected by solvents. One example of such a well-known phenomenon is that the basicity
* This discussion is based on Ref. 22 and Ref. 23.
RISM-SCF/MCSCF for Processes in Solutions |
429 |
of the methylamines increases monotonically with successive methyl substitutions in the gas phase,
NH3 (CH3)NH2 (CH3)2NH (CH3)3N
while the order reverses at the trimethylamine in an aqueous environment [24],
NH3 (CH3)NH2 (CH3)2NH (CH3)3N
The monotonic increase in basicity in the gas phase has been explained in terms of the ‘‘negative induction’’ or the polarization effect due to the methyl groups. Essentially two important factors are considered responsible for the solvent effect on the proton affinity: the solvation free energy and the energy change associated with the electron reorganization upon solvation. The solvation free energy in turn consists of the solute–solvent interaction energy and the free energy change associated with the solvent reorganization.
Let us define the respective basicity by ∆Gg in the gas phase and ∆Gs in aqueous solution. For discussions concerning the relative strength in basicity of a series of methylamines, only the relative magnitudes of these quantities are needed. Thus the free energy changes associated with the protonation of the methylamines relative to those of ammonia are defined as
∆∆G298i [(CH3)nNH3 n] ∆G298i [(CH3)nNH3 n] ∆G298i [NH3], n 1, 2, 3 (22)
Computed values are plotted in Figure 6 against the number of methyl groups. Note that these components include the electronic contributions (net contribution for isolated mole-
Figure 6 Free energy changes of methylamines in aqueous solution upon protonation referred to NH3.

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cule and Ereorg), solvation energy (∆ ) described above, and kinetic contributions evaluated from the elementary statistical mechanics of ideal systems. The contribution from solute itself, ∆∆G298s (solute), exhibits similar monotonic behavior with the gas phase result (∆∆Gg298), which is in good agreement with the experimental data. The difference between ∆∆Gs298(solute) and ∆∆Gg298 is due essentially to the electron reorganization energy. The solvation free energy ∆∆G298s (solvent) shows the monotonic increase with successive methyl substitution. The sum of the two contributions produces an inversion in the overall free energy change ∆∆Gs298, which is in qualitative accord with the experimental result.
2. Acidities of Haloacetic Acids in Aqueous Solution*
Another example is the acidities of a series of carboxylic acids. It is known that the substitution effect on these compounds also depends on the environment. The behavior of the halo-substituted acetic acids is one of the prototype problems for the solvent effect on acidity: The order in strength of the haloacetic acids in the gas phase is
CH3COOH CH2FCOOH CH2ClCOOH CH2BrCOOH
whereas in aqueous solution it is drastically altered [27] to
CH3COOH CH2FCOOH CH2ClCOOH CH2BrCOOH
The observed acidities in the gas phase are interpreted in terms of the negative induction effect of the halo substituents; however, the microscopic picture of the solvent effects in addition to such induction effects of the solute have not been clarified.
Procedures to compute acidities are essentially similar to those for the basicities discussed in the previous section. The acidities in the gas phase and in solution can be calculated as the free energy changes ∆Gg and ∆Gs upon proton release of the isolated and solvated molecules, respectively. To discuss the relative strengths of acidity in the gas and aqueous solution phases, we only need the magnitude of ∆Gg and ∆Gs for haloacetic acids relative to those for acetic acids. Thus the free energy calculations for acetic acid, haloacetic acids, and each conjugate base are carried out in the gas phase and in aqueous solution.
In Figure 7, ∆Gs and its components, ∆Gs(solute) and ∆Gs(solvent), are plotted. ∆Gs(solute) contributes to the increase in the net free energy upon proton release or to the acidity, which is similar to ∆Gg in the gas phase. ∆Gs(solvent) is positive relative to acetic acid and contributes to hinder the proton release and to decrease the acidity. The net increase in ∆Gs(solvent) from the fluoro derivative to the chloro derivative is caused by the greater destabilization of the negative ions compared to that of the neutral molecules. The essential difference between the ionic and neutral species lies in the electrostatic interactions, which play an important role in determining the order of the acidities in solution. The inversion in the acidities from the fluoro substitution to the chloro substitution is due to the greater increase in the electrostatic contribution in the solvation free energy compared to the decrease in the contribution from the change in the solute electronic structure. As shown in Figure 7, agreement with respect to the relative order in acidity is obtained in aqueous solution as well as in the gas phase.
* This discussion is based on Ref. 25 and Ref. 26.

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431 |
Figure 7 Free energy changes of halo-substituted carboxyl acid in aqueous solution upon deprotonation referred to acetic acid.
3. Acid Strength of the Hydrogen Halides in Aqueous Solution*
It is known that the order of acidity of hydrogen halides (HX, where X F, Cl, Br, I) in the gas phase can be successfully predicted by quantum chemical considerations, namely, F Cl Br I. However, in aqueous solution, whereas hydrogen chloride, bromide, and iodide completely dissociate in aqueous solutions, hydrogen fluoride shows a small dissociation constant. This phenomenon is explained by studying free energy changes associated with the chemical equilibrium HX H2O s X H3O in the solution phase for a series of hydrogen halides. In this study, the species in the equilibrium reaction, HX, X , H2O, and H3O , are regarded as ‘‘solute’’ in the infinitely dilute solution. Thus the free energy difference in aqueous solution can be obtained in terms of the free energy difference associated with the reaction in vacuo and solvation free energy.
Figure 8 shows the PCF between the halogen site in HX and the hydrogen site in
˚
solvent water. The fluoride shows a distinct peak at 1.82 A. There is no corresponding peak in the other XEH correlation functions. From other PCFs and geometrical considerations, we can conclude that hydrogen bonds between solute hydrogen and solvent oxygen are strong and are found in all the hydrogen halides and that only hydrogen fluoride forms a distinct FEH (solvent water) hydrogen bond. The liquid structure around HF is expected to be markedly different from those around the other hydrogen halides.
The free energy difference is mainly governed by the subtle balance of the two energetic components, the formation energies of hydrogen halides and the solvation ener-
* This discussion is based on Ref. 28.