Reviews in Computational Chemistry / Reviews in Computational Chemistry, Volume 23

Name: Reviews in Computational Chemistry / Reviews in Computational Chemistry, Volume 23
Brand: Wiley-VCH
Price: 199.99 EUR
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Kenny B. Lipkowitz Tom Cundari Donald B. Boyd(Herausgeber*in)

Wiley-VCH (Verlag)

Erschienen am 22. August 2007

376 Seiten

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Intro
Reviews in Computational Chemistry Volume 23
Preface
Contents
Contributors
Contributors to Previous Volumes
1. Linear-Scaling Methods in Quantum Chemistry
Introduction
Some Basics of SCF Theory
Direct SCF Methods and Two-Electron Integral Screening
Schwarz Integral Estimates
Multipole-Based Integral Estimates (MBIE)
Calculation of Integrals via Multipole Expansion
A First Example
Derivation of the Multipole Expansion
The Fast Multipole Method: Breaking the Quadratic Wall
Fast Multipole Methods for Continuous Charge Distributions
Other Approaches
Exchange-Type Contractions
The Exchange-Correlation Matrix of KS-DFT
Avoiding the Diagonalization Step-Density Matrix-Based SCF
General Remarks
Tensor Formalism
Properties of the One-Particle Density Matrix
Density Matrix-Based Energy Functional
''Curvy Steps'' in Energy Minimization
Density Matrix-Based Quadratically Convergent SCF (D-QCSCF)
Implications for Linear-Scaling Calculation of SCF Energies
SCF Energy Gradients
Molecular Response Properties at the SCF Level
Vibrational Frequencies
NMR Chemical Shieldings
Density Matrix-Based Coupled Perturbed SCF (D-CPSCF)
Outlook on Electron Correlation Methods for Large Systems
Long-Range Behavior of Correlation Effects
Rigorous Selection of Transformed Products via Multipole-Based Integral Estimates (MBIE)
Implications
Conclusions
References
2. Conical Intersections in Molecular Systems
Introduction
General Theory
The Born-Oppenheimer Approximation and its Breakdown: Nonadiabatic Processes
Adiabatic-Diabatic Representation
The Noncrossing Rule
The Geometric Phase Effect
Conical Intersections and Symmetry
The Branching Plane
Characterizing Conical Intersections: Topography
Derivative Coupling
Electronic Structure Methods for Excited States
Multiconfiguration Self-Consistent Field (MCSCF)
Multireference Configuration Interaction (MRCI)
Complete Active Space Second-Order Perturbation Theory (CASPT2)
Single Reference Methods
Choosing Electronic Structure Methods for Conical Intersections
Locating Conical Intersections
Dynamics
Applications
Conical Intersections in Biologically Relevant Systems
Beyond the Double Cone
Three-State Conical Intersections
Spin-Orbit Coupling and Conical Intersections
Conclusions and Future Directions
Acknowledgments
References
3. Variational Transition State Theory with Multidimensional Tunneling
Introduction
Variational Transition State Theory for Gas-Phase Reactions
Conventional Transition State Theory
Canonical Variational Transition State Theory
Other Variational Transition State Theories
Quantum Effects on the Reaction Coordinate
Practical Methods for Quantized VTST Calculations
The Reaction Path
Evaluation of Partition Functions
Harmonic and Anharmonic Vibrational Energy Levels
Calculations of Generalized Transition State Number of States
Quantum Effects on Reaction Coordinate Motion
Multidimensional Tunneling Corrections Based on the Adiabatic Approximation
Large Curvature Transmission Coefficient
The Microcanonically Optimized Transmission Coefficient
Building the PES from Electronic Structure Calculation
Direct Dynamics with Specific Reaction Parameters
Interpolated VTST
Dual-Level Dynamics
Reactions in Liquids
Ensemble-Averaged Variational Transition State Theory
Gas-Phase Example: H + CH(4)
Liquid-Phase Example: Menshutkin Reaction
Concluding Remarks
Acknowledgments
References
4. Coarse-Grain Modeling of Polymers
Introduction
Defining the System
Choice of Model
Interaction Sites on the Coarse-Grained Scale
Static Mapping
Single-Chain Distribution Potentials
Simplex
Iterative Structural Coarse-Graining
Mapping Onto Simple Models
Dynamic Mapping
Mapping by Chain Diffusion
Mapping through Local Correlation Times
Direct Mapping of the Lennard-Jones Time
Coarse-Grained Monte Carlo Simulations
Reverse Mapping
A Look Beyond Polymers
Conclusions
Acknowledgments
References
5. Analysis of Chemical Information Content Using Shannon Entropy
Introduction
Shannon Entropy Concept
Descriptor Comparison
Influence of Boundary Effects
Extension of SE Analysis for Profiling of Chemical Libraries
Information Content of Organic Molecules
Shannon Entropy in Quantum Mechanics, Molecular Dynamics, and Modeling
Examples of SE and DSE Analysis
Conclusions
References
6. Applications of Support Vector Machines in Chemistry
Introduction
A Nonmathematical Introduction to SVM
Pattern Classification
The Vapnik-Chervonenkis Dimension
Pattern Classification with Linear Support Vector Machines
SVM Classification for Linearly Separable Data
Linear SVM for the Classification of Linearly Non-Separable Data
Nonlinear Support Vector Machines
Mapping Patterns to a Feature Space
Feature Functions and Kernels
Kernel Functions for SVM
Hard Margin Nonlinear SVM Classification
Soft Margin Nonlinear SVM Classification
?-SVM Classification
Weighted SVM for Imbalanced Classification
Multi-class SVM Classification
SVM Regression
Optimizing the SVM Model
Descriptor Selection
Support Vectors Selection
Jury SVM
Kernels for Biosequences
Kernels for Molecular Structures
Practical Aspects of SVM Classification
Predicting the Mechanism of Action for Polar and Nonpolar Narcotic Compounds
Predicting the Mechanism of Action for Narcotic and Reactive Compounds
Predicting the Mechanism of Action from Hydrophobicity and Experimental Toxicity
Classifying the Carcinogenic Activity of Polycyclic Aromatic Hydrocarbons
Structure-Odor Relationships for Pyrazines
Practical Aspects of SVM Regression
SVM Regression QSAR for the Phenol Toxicity to Tetrahymena pyriformis
SVM Regression QSAR for Benzodiazepine Receptor Ligands
SVM Regression QSAR for the Toxicity of Aromatic Compounds to Chlorella vulgaris
SVM Regression QSAR for Bioconcentration Factors
Review of SVM Applications in Chemistry
Recognition of Chemical Classes and Drug Design
QSAR
Genotoxicity of Chemical Compounds
Chemometrics
Sensors
Chemical Engineering
Text Mining for Scientific Information
SVM Resources on the Web
SVM Software
Conclusions
References
7. How Computational Chemistry Became Important in the Pharmaceutical Industry
Introduction
Germination: The 1960s
Gaining a Foothold: The 1970s
Growth: The 1980s
Gems Discovered: The 1990s
Final Observations
Acknowledgments
References
Author Index
Subject Index

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