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Fragmentation : Toward Accurate Calculations on Complex Molecular Systems.

By: Material type: TextTextPublisher: Newark : John Wiley & Sons, Incorporated, 2017Copyright date: ©2017Edition: 1st edDescription: 1 online resource (376 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119129257
Subject(s): Genre/Form: Additional physical formats: Print version:: Fragmentation: Toward Accurate Calculations on Complex Molecular SystemsLOC classification:
  • QD281.F7.F734 2017
Online resources:
Contents:
Intro -- Fragmentation -- Contents -- List of Contributors -- Preface -- 1 Explicitly Correlated Local Electron Correlation Methods -- 1.1 Introduction -- 1.2 Benchmark Systems -- 1.3 Orbital-Invariant MP2 Theory -- 1.4 Principles of Local Correlation -- 1.5 Orbital Localization -- 1.6 Local Virtual Orbitals -- 1.6.1 Pseudo-Canonical Pair-Specific Orbitals -- 1.6.2 Projected Atomic Orbitals -- 1.6.3 Pair Natural Orbitals -- 1.6.4 Linear Scaling PNO Generation -- 1.6.5 Orbital-Specific Virtuals (OSVs) -- 1.7 Choice of Domains -- 1.8 Approximations for Distant Pairs -- 1.8.1 Bipolar Multipole Approximations of Electron Repulsion Integrals -- 1.8.2 Approximations of Distant Pair Energies -- 1.9 Local Coupled-Cluster Methods (LCCSD) -- 1.9.1 Weak Pair Approximations -- 1.9.2 Long-Range Cancellations of Terms in the LCCSD Equations -- 1.9.3 Projection Approximations -- 1.10 Triple Excitations -- 1.11 Local Explicitly Correlated Methods -- 1.11.1 PNO-LMP2-F12 -- 1.11.2 PNO-LCCSD-F12 -- 1.12 Technical Aspects -- 1.12.1 Local Density Fitting -- 1.12.2 Parallelization -- 1.13 Comparison of Local Correlation and Fragment Methods -- 1.14 Summary -- Appendix A: The LCCSD Equations -- Appendix B: Derivation of the Interaction Matrices -- References -- 2 Density and Potential Functional Embedding: Theory and Practice -- 2.1 Introduction -- 2.2 Theoretical Background -- 2.3 Density Functional Embedding Theory -- 2.3.1 Basic Theory -- 2.3.1.1 Definition of the Embedding Potential -- 2.3.1.2 Optimization Procedure -- 2.3.2 Embedding Potential Construction-Implementations in Planewave Codes -- 2.3.2.1 Implementation with Pseudopotentials in ABINIT -- 2.3.2.2 Implementation with PAW in VASP -- 2.3.2.3 Penalty Functions-Damping the Unphysical Oscillations -- 2.3.2.4 Illustrative Example -- 2.3.3 Embedded Cluster Calculations.
2.3.3.1 Calculation of Embedding Integrals -- 2.3.3.2 Evaluation of the Total Energy -- 2.3.3.3 Examples -- 2.4 Potential Functional EmbeddingTheory -- 2.4.1 Basic Theories and Technical Details -- 2.4.1.1 Definition of Energies -- 2.4.1.2 Optimized Effective Potential (OEP) Scheme for Exact Kinetic Energy -- 2.4.1.3 Energy Gradient -- 2.4.1.4 Summary of the Code Structure -- 2.4.2 Illustrative Examples -- 2.4.2.1 AlP Diatomic -- 2.4.2.2 H2O on MgO (001) -- 2.5 Summary and Outlook -- Acknowledgments -- References -- 3 Modeling and Visualization for the Fragment Molecular Orbital Method with the Graphical User Interface FU, and Analyses of Protein-Ligand Binding -- 3.1 Introduction -- 3.2 Overview of FMO -- 3.3 Methodology -- 3.3.1 FMO/PCM Formulation in the Presence of Dummy Atoms -- 3.3.2 New Analyses Defining the Desolvation Penalty in the Protein-Ligand Binding -- 3.3.2.1 Asymmetric Binding Analysis (ABA) -- 3.3.2.2 Symmetric Binding Analysis (SBA) -- 3.3.2.3 Symmetric Binding Analysis with Separated Cavitation (SBAC) -- 3.3.2.4 Fragment-Wise Elaboration of SBA in FMO -- 3.3.2.5 Fragment-Wise Elaboration of SBAC -- 3.3.3 Application of Analyses to Protein-Ligand Binding -- 3.4 GUI Development -- 3.4.1 Outline of FU -- 3.4.2 Modeling and Result Visualization -- 3.4.2.1 Modeling of an FKBP Protein Complex -- 3.4.2.2 Creating FMO Input -- 3.4.2.3 Running FMO in GAMESS -- 3.4.2.4 Visualizing FMO Results -- 3.4.3 An Overview of Using FU for a Complex System -- 3.4.4 Examples of Scripting in FU -- 3.4.4.1 Converting Multiple PDB Files into Z-matrix Files -- 3.4.4.2 Drawing Dipole Moments with Arrows -- 3.5 Conclusions -- Acknowledgments -- References -- 4 Molecules-in-Molecules Fragment-Based Method for the Accurate Evaluation of Vibrational and Chiroptical Spectra for Large Molecules -- 4.1 Introduction -- 4.2 Computational Methods and Theory.
4.3 Results and Discussion -- 4.3.1 MIM Method for Geometry Optimization -- 4.3.2 MIM Method for Evaluating IR Spectra (MIM-IR) -- 4.3.3 MIM Method for Evaluating Raman Spectra (MIM-Raman) -- 4.3.4 MIM Method for Evaluating VCD Spectra (MIM-VCD) -- 4.3.5 MIM Method for Evaluating ROA Spectra (MIM-ROA) -- 4.3.6 Two-Step-MIM Scheme for Evaluating Raman and ROA Spectra -- 4.4 Summary -- 4.5 Conclusions -- Acknowledgments -- References -- 5 Effective Fragment Molecular Orbital Method -- 5.1 Introduction -- 5.1.1 Effective Fragment Potentials -- 5.1.2 Fragment Molecular Orbital Method -- 5.2 Effective Fragment Molecular Orbital Method -- 5.2.1 Correlation Energies in the EFMO Method -- 5.2.2 The EFMO Gradient -- 5.2.3 Timings and Computational Efficiency -- 5.2.4 Biochemistry with EFMO -- 5.2.5 Fully Integrated EFMO -- 5.2.6 Remarks, Notes, and Comments -- 5.3 Summary and Future Developments -- References -- 6 Effective Fragment Potential Method: Past, Present, and Future -- 6.1 Overview of the EFP Method -- 6.2 Milestones in the Development of the EFP Method -- 6.2.1 EFP1 Water Model -- 6.2.2 EFP (EFP2) General Model -- 6.3 Present: Chemistry at Interfaces and Photobiology -- 6.3.1 OH Radical Solvated inWater -- 6.3.2 EFP for Macromolecules and Polymers -- 6.4 Future Directions and Outlook -- References -- 7 Nucleation Using the Effective Fragment Potential and Two-Level Parallelism -- 7.1 Introduction -- 7.2 Methods -- 7.2.1 Brief Overview of DNTMC -- 7.2.2 Brief Overview of EFP -- 7.2.3 Overview of the Two-Level Parallelism Approach -- 7.3 Results -- 7.3.1 Evaporation Rate of Water Hexamer Cluster at 243K -- 7.3.2 Ion Mediated Nucleation -- 7.3.3 Evaporation Rate of Sulfuric Acid from Neutral Sulfuric Acid Dimer Clusters -- 7.3.4 Two-Level Parallel DNTEFP Performance Analysis -- 7.4 Conclusions -- Acknowledgments -- References.
8 Five Years of Density Matrix Embedding Theory -- 8.1 Quantum Entanglement -- 8.2 Density Matrix EmbeddingTheory -- 8.3 Bath Orbitals from a Slater Determinant -- 8.4 The Embedding Hamiltonian -- 8.5 Self-Consistency -- 8.6 Green's Functions -- 8.7 Overview of the Literature -- 8.8 The One-Band Hubbard Model on the Square Lattice -- 8.9 Dissociation of a Linear Hydrogen Chain -- 8.10 Summary -- Acknowledgments -- References -- 9 Ab initio Ice, Dry Ice, and Liquid Water -- 9.1 Introduction -- 9.2 Computational Method -- 9.2.1 Internal Energy -- 9.2.2 Structure and Phonons -- 9.2.3 Spectra -- 9.2.4 Pressure Effects -- 9.2.5 Temperature Effects -- 9.2.6 Born-Oppenheimer Molecular Dynamics -- 9.3 Case Studies -- 9.3.1 Ice-Ih -- 9.3.2 Ice-HDA -- 9.3.3 Ice-VIII -- 9.3.4 Liquid Water -- 9.3.5 CO2-I: Pressure Tuning of Fermi Resonance -- 9.3.6 CO2-I and III: Solid-Solid Phase Transition -- 9.3.7 CO2-I: Thermal Expansion -- 9.4 Concluding Remarks -- 9.5 Disclaimer -- Acknowledgments -- References -- 10 A Linear-Scaling Divide-and-Conquer Quantum Chemical Method for Open-Shell Systems and Excited States -- 10.1 Introduction -- 10.2 Theories for the Divide-and-Conquer Method -- 10.2.1 Review of DC-SCF and DC-Based Correlation Theories -- 10.2.1.1 DC-HF/DFT -- 10.2.1.2 DC-Based Correlation Theory -- 10.2.1.3 Dual-Buffer DC-Based Correlation Method -- 10.2.2 Linear-Scaling Divide-and-Conquer Method for Open-Shell Systems -- 10.2.2.1 DC-USCF and DC-UMP2 -- 10.2.2.2 Expected Value of the Squared Spin Operator ̂S2 -- 10.2.3 Linear-Scaling Divide-and-Conquer Method for Excited-State Calculations -- 10.2.3.1 DC-CIS/TDDFT -- 10.2.3.2 DC-SAC/SACCI -- 10.3 Assessment of the Divide-and-Conquer Method -- 10.3.1 Divide-and-Conquer Calculations for Open-Shell Systems -- 10.3.1.1 DC-USCF and DC-UMP2 -- 10.3.2 Excited-State Calculations based on the Divide-and-Conquer Method.
10.3.2.1 Conjugated Aldehyde -- 10.3.2.2 Photoactive Yellow Protein -- 10.4 Conclusion -- References -- 11 MFCC-Based Fragmentation Methods for Biomolecules -- 11.1 Introduction -- 11.2 Theory and Applications -- 11.2.1 The MFCC Approach -- 11.2.2 Electron Density and Total Energy -- 11.2.3 The EE-GMFCC Method for Energy Calculation -- 11.2.4 The EE-GMFCC-CPCM Method for Protein Solvation Energy -- 11.2.5 The EE-GMFCC-CPCM Method for Protein-Ligand Binding Energy -- 11.2.6 The EE-GMFCC Method for Geometry Optimization and Vibrational Spectrum of Proteins -- 11.2.7 The EE-GMFCC-Based Ab Initio Molecular Dynamics for Proteins -- 11.3 Conclusion -- Acknowledgments -- References -- Index -- EULA.
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Intro -- Fragmentation -- Contents -- List of Contributors -- Preface -- 1 Explicitly Correlated Local Electron Correlation Methods -- 1.1 Introduction -- 1.2 Benchmark Systems -- 1.3 Orbital-Invariant MP2 Theory -- 1.4 Principles of Local Correlation -- 1.5 Orbital Localization -- 1.6 Local Virtual Orbitals -- 1.6.1 Pseudo-Canonical Pair-Specific Orbitals -- 1.6.2 Projected Atomic Orbitals -- 1.6.3 Pair Natural Orbitals -- 1.6.4 Linear Scaling PNO Generation -- 1.6.5 Orbital-Specific Virtuals (OSVs) -- 1.7 Choice of Domains -- 1.8 Approximations for Distant Pairs -- 1.8.1 Bipolar Multipole Approximations of Electron Repulsion Integrals -- 1.8.2 Approximations of Distant Pair Energies -- 1.9 Local Coupled-Cluster Methods (LCCSD) -- 1.9.1 Weak Pair Approximations -- 1.9.2 Long-Range Cancellations of Terms in the LCCSD Equations -- 1.9.3 Projection Approximations -- 1.10 Triple Excitations -- 1.11 Local Explicitly Correlated Methods -- 1.11.1 PNO-LMP2-F12 -- 1.11.2 PNO-LCCSD-F12 -- 1.12 Technical Aspects -- 1.12.1 Local Density Fitting -- 1.12.2 Parallelization -- 1.13 Comparison of Local Correlation and Fragment Methods -- 1.14 Summary -- Appendix A: The LCCSD Equations -- Appendix B: Derivation of the Interaction Matrices -- References -- 2 Density and Potential Functional Embedding: Theory and Practice -- 2.1 Introduction -- 2.2 Theoretical Background -- 2.3 Density Functional Embedding Theory -- 2.3.1 Basic Theory -- 2.3.1.1 Definition of the Embedding Potential -- 2.3.1.2 Optimization Procedure -- 2.3.2 Embedding Potential Construction-Implementations in Planewave Codes -- 2.3.2.1 Implementation with Pseudopotentials in ABINIT -- 2.3.2.2 Implementation with PAW in VASP -- 2.3.2.3 Penalty Functions-Damping the Unphysical Oscillations -- 2.3.2.4 Illustrative Example -- 2.3.3 Embedded Cluster Calculations.

2.3.3.1 Calculation of Embedding Integrals -- 2.3.3.2 Evaluation of the Total Energy -- 2.3.3.3 Examples -- 2.4 Potential Functional EmbeddingTheory -- 2.4.1 Basic Theories and Technical Details -- 2.4.1.1 Definition of Energies -- 2.4.1.2 Optimized Effective Potential (OEP) Scheme for Exact Kinetic Energy -- 2.4.1.3 Energy Gradient -- 2.4.1.4 Summary of the Code Structure -- 2.4.2 Illustrative Examples -- 2.4.2.1 AlP Diatomic -- 2.4.2.2 H2O on MgO (001) -- 2.5 Summary and Outlook -- Acknowledgments -- References -- 3 Modeling and Visualization for the Fragment Molecular Orbital Method with the Graphical User Interface FU, and Analyses of Protein-Ligand Binding -- 3.1 Introduction -- 3.2 Overview of FMO -- 3.3 Methodology -- 3.3.1 FMO/PCM Formulation in the Presence of Dummy Atoms -- 3.3.2 New Analyses Defining the Desolvation Penalty in the Protein-Ligand Binding -- 3.3.2.1 Asymmetric Binding Analysis (ABA) -- 3.3.2.2 Symmetric Binding Analysis (SBA) -- 3.3.2.3 Symmetric Binding Analysis with Separated Cavitation (SBAC) -- 3.3.2.4 Fragment-Wise Elaboration of SBA in FMO -- 3.3.2.5 Fragment-Wise Elaboration of SBAC -- 3.3.3 Application of Analyses to Protein-Ligand Binding -- 3.4 GUI Development -- 3.4.1 Outline of FU -- 3.4.2 Modeling and Result Visualization -- 3.4.2.1 Modeling of an FKBP Protein Complex -- 3.4.2.2 Creating FMO Input -- 3.4.2.3 Running FMO in GAMESS -- 3.4.2.4 Visualizing FMO Results -- 3.4.3 An Overview of Using FU for a Complex System -- 3.4.4 Examples of Scripting in FU -- 3.4.4.1 Converting Multiple PDB Files into Z-matrix Files -- 3.4.4.2 Drawing Dipole Moments with Arrows -- 3.5 Conclusions -- Acknowledgments -- References -- 4 Molecules-in-Molecules Fragment-Based Method for the Accurate Evaluation of Vibrational and Chiroptical Spectra for Large Molecules -- 4.1 Introduction -- 4.2 Computational Methods and Theory.

4.3 Results and Discussion -- 4.3.1 MIM Method for Geometry Optimization -- 4.3.2 MIM Method for Evaluating IR Spectra (MIM-IR) -- 4.3.3 MIM Method for Evaluating Raman Spectra (MIM-Raman) -- 4.3.4 MIM Method for Evaluating VCD Spectra (MIM-VCD) -- 4.3.5 MIM Method for Evaluating ROA Spectra (MIM-ROA) -- 4.3.6 Two-Step-MIM Scheme for Evaluating Raman and ROA Spectra -- 4.4 Summary -- 4.5 Conclusions -- Acknowledgments -- References -- 5 Effective Fragment Molecular Orbital Method -- 5.1 Introduction -- 5.1.1 Effective Fragment Potentials -- 5.1.2 Fragment Molecular Orbital Method -- 5.2 Effective Fragment Molecular Orbital Method -- 5.2.1 Correlation Energies in the EFMO Method -- 5.2.2 The EFMO Gradient -- 5.2.3 Timings and Computational Efficiency -- 5.2.4 Biochemistry with EFMO -- 5.2.5 Fully Integrated EFMO -- 5.2.6 Remarks, Notes, and Comments -- 5.3 Summary and Future Developments -- References -- 6 Effective Fragment Potential Method: Past, Present, and Future -- 6.1 Overview of the EFP Method -- 6.2 Milestones in the Development of the EFP Method -- 6.2.1 EFP1 Water Model -- 6.2.2 EFP (EFP2) General Model -- 6.3 Present: Chemistry at Interfaces and Photobiology -- 6.3.1 OH Radical Solvated inWater -- 6.3.2 EFP for Macromolecules and Polymers -- 6.4 Future Directions and Outlook -- References -- 7 Nucleation Using the Effective Fragment Potential and Two-Level Parallelism -- 7.1 Introduction -- 7.2 Methods -- 7.2.1 Brief Overview of DNTMC -- 7.2.2 Brief Overview of EFP -- 7.2.3 Overview of the Two-Level Parallelism Approach -- 7.3 Results -- 7.3.1 Evaporation Rate of Water Hexamer Cluster at 243K -- 7.3.2 Ion Mediated Nucleation -- 7.3.3 Evaporation Rate of Sulfuric Acid from Neutral Sulfuric Acid Dimer Clusters -- 7.3.4 Two-Level Parallel DNTEFP Performance Analysis -- 7.4 Conclusions -- Acknowledgments -- References.

8 Five Years of Density Matrix Embedding Theory -- 8.1 Quantum Entanglement -- 8.2 Density Matrix EmbeddingTheory -- 8.3 Bath Orbitals from a Slater Determinant -- 8.4 The Embedding Hamiltonian -- 8.5 Self-Consistency -- 8.6 Green's Functions -- 8.7 Overview of the Literature -- 8.8 The One-Band Hubbard Model on the Square Lattice -- 8.9 Dissociation of a Linear Hydrogen Chain -- 8.10 Summary -- Acknowledgments -- References -- 9 Ab initio Ice, Dry Ice, and Liquid Water -- 9.1 Introduction -- 9.2 Computational Method -- 9.2.1 Internal Energy -- 9.2.2 Structure and Phonons -- 9.2.3 Spectra -- 9.2.4 Pressure Effects -- 9.2.5 Temperature Effects -- 9.2.6 Born-Oppenheimer Molecular Dynamics -- 9.3 Case Studies -- 9.3.1 Ice-Ih -- 9.3.2 Ice-HDA -- 9.3.3 Ice-VIII -- 9.3.4 Liquid Water -- 9.3.5 CO2-I: Pressure Tuning of Fermi Resonance -- 9.3.6 CO2-I and III: Solid-Solid Phase Transition -- 9.3.7 CO2-I: Thermal Expansion -- 9.4 Concluding Remarks -- 9.5 Disclaimer -- Acknowledgments -- References -- 10 A Linear-Scaling Divide-and-Conquer Quantum Chemical Method for Open-Shell Systems and Excited States -- 10.1 Introduction -- 10.2 Theories for the Divide-and-Conquer Method -- 10.2.1 Review of DC-SCF and DC-Based Correlation Theories -- 10.2.1.1 DC-HF/DFT -- 10.2.1.2 DC-Based Correlation Theory -- 10.2.1.3 Dual-Buffer DC-Based Correlation Method -- 10.2.2 Linear-Scaling Divide-and-Conquer Method for Open-Shell Systems -- 10.2.2.1 DC-USCF and DC-UMP2 -- 10.2.2.2 Expected Value of the Squared Spin Operator ̂S2 -- 10.2.3 Linear-Scaling Divide-and-Conquer Method for Excited-State Calculations -- 10.2.3.1 DC-CIS/TDDFT -- 10.2.3.2 DC-SAC/SACCI -- 10.3 Assessment of the Divide-and-Conquer Method -- 10.3.1 Divide-and-Conquer Calculations for Open-Shell Systems -- 10.3.1.1 DC-USCF and DC-UMP2 -- 10.3.2 Excited-State Calculations based on the Divide-and-Conquer Method.

10.3.2.1 Conjugated Aldehyde -- 10.3.2.2 Photoactive Yellow Protein -- 10.4 Conclusion -- References -- 11 MFCC-Based Fragmentation Methods for Biomolecules -- 11.1 Introduction -- 11.2 Theory and Applications -- 11.2.1 The MFCC Approach -- 11.2.2 Electron Density and Total Energy -- 11.2.3 The EE-GMFCC Method for Energy Calculation -- 11.2.4 The EE-GMFCC-CPCM Method for Protein Solvation Energy -- 11.2.5 The EE-GMFCC-CPCM Method for Protein-Ligand Binding Energy -- 11.2.6 The EE-GMFCC Method for Geometry Optimization and Vibrational Spectrum of Proteins -- 11.2.7 The EE-GMFCC-Based Ab Initio Molecular Dynamics for Proteins -- 11.3 Conclusion -- Acknowledgments -- References -- Index -- EULA.

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