Recent Advances of the Fragment Molecular Orbital Method: Enhanced Performance and Applicability

Foreword
Preface by Editors
Contents
Positioning of FMO
Fragment Molecular Orbital Method as Cluster Expansion
1 Introduction
2 Cluster Expansion
3 Green's Function Approach
4 Concluding Remarks
References
Comparison of Various Fragmentation Methods for Quantum Chemical Calculations of Large Molecular Systems
1 Introduction
2 Various Fragmentation Methods
3 Pros and Cons: Cost, Accuracy, Viability, and Versatility
3.1 Disturbance of Electronic States
3.2 Environmental Effects
3.3 Utility and Extension
3.4 Cost and Accuracy
4 Perspective
5 Conclusion
References
Programs
Recent Development of the Fragment Molecular Orbital Method in GAMESS
1 Introduction
2 FMO Methodology
2.1 Outline of FMO
2.2 Decomposition of Properties
2.3 Solvation Models for FMO in GAMESS
2.4 Reduction of Memory Requirements in FMO
2.5 Electrostatic Embedding
2.6 Summary of the FMO Functionality in GAMESS
3 Conclusions and Outlook
References
The ABINIT-MP Program
1 Introduction
2 Energy Calculation
3 Energy Gradient Calculation
4 Property Evaluation
5 Analysis Tool
6 Utility
7 Demonstrative Application
8 Future Development
9 Summary
References
PAICS: Development of an Open-Source Software of Fragment Molecular Orbital Method for Biomolecule
1 Introduction
2 RI-MP2 and MP3 with FMO Method
3 Benchmark Calculation of FMO-RI-MP2 and MP3
4 Summary
References
Open-Architecture Program of Fragment Molecular Orbital Method for Massive Parallel Computing (OpenFMO) with GPU Acceleration
1 Introduction
2 Capabilities
3 Workflow of FMO
4 Master-Worker Execution Model
5 GPU Acceleration
6 Concluding Remarks
References
Pharmaceutical Activities
How to Perform FMO Calculation in Drug Discovery
1 Introduction
2 Brief Description of the FMO Method for Use in Protein–Ligand System
2.1 FMO Energy
2.2 ESP Approximation and Dimer-es Approximation
3 Preparation for FMO Calculation
3.1 Modeling of Structure
3.2 Fragmentation
3.3 Selection of Theoretical Method
4 Evaluation of Protein–Ligand Binding
4.1 Ligand-Binding Affinity Prediction
4.2 Interaction Energy Analysis
4.3 High-Resolution Interaction Analysis for SBDD
5 Electron Density and Related Analysis
5.1 Population Analysis
5.2 Electrostatic Potential Analysis
5.3 Electron Density Analysis
6 Conclusion Remarks
References
FMO Drug Design Consortium
1 About the FMO Drug Design Consortium (FMODD)
2 The Kinase WG
3 The Protease WG
4 The Nuclear Receptor WG
4.1 VDR
4.2 AR
4.3 Retinoic Acid Receptor-Related Orphan Receptor γt
4.4 ER
5 WG on Protein–Protein Interactions
5.1 MDM2-p53 Interaction Inhibitor
5.2 β-Secretase 1 Inhibitor
6 The FMODD-KBDD WG
7 The Development WG
7.1 Auto-FMO Protocol
7.2 FMO Database
7.3 Structure Refinement by FMO
7.4 Data Preparation for FMO-Based Partial Charge and Force Field AI Models
7.5 Future Perspectives for the “FMO Drug Design Platform”
References
Development of an Automated FMO Calculation Protocol to Construction of FMO Database
1 Introduction
2 Workflow of the Auto-FMO Protocol
3 Validation of the Auto-FMO Protocol Data for ERα and P38α
3.1 Validation Data Sets of ERα and P38α MAP Kinase
3.2 Completion Rate of FMO Calculation
3.3 Comparison of Ligand Binding Interaction Energy
3.4 Issues to Be Solved in the Auto-FMO Protocol
3.5 Construction of FMO Database with the Auto-FMO Protocol
4 Conclusion
References
Application of FMO to Ligand Design: SBDD, FBDD, and Protein–Protein Interaction
1 Introduction
2 Computational Method
2.1 Structure Preparation
2.2 CH/π Interaction and CHPI Analysis
3 Application of FMO to SBDD
3.1 Abstract
3.2 Lck Kinase
3.3 Interpretation of Ligand and Protein Interaction
3.4 Conclusions
4 Application of FMO to FBDD
4.1 Abstract
4.2 Fragment-Based Drug Design (FBDD)
4.3 Protein–Protein Interaction (PPI) and Bromodomain
4.4 FMO Calculations for H4K5acK8ac, a Peptide Ligand Containing Two εAc-Lys
4.5 Analysis of Fragment Optimization Process in Tetrahydroquinazoline-6-yl-benzensulfonamide Derivatives
4.6 Insight into FBDD Process
4.7 Evaluation of High-Affinity Ligands
4.8 Consideration of Water in the Ligand Binding Site
4.9 Conclusions
5 Importance of CH/π Interactions in Recognition of Core Motif in Proline-Recognition Domains
5.1 Abstract
5.2 FMO Calculations for SH3 Domain
5.3 CH/π Interactions in Proline-Recognition Domains
5.4 Conclusions
6 General Trend of CH/π Interactions
6.1 Additivity of CH/π Interactions
6.2 CH/π interaction Energies for Obtaining Each Aromatic Amino Residue
7 Conclusion
References
Drug Discovery Screening by Combination of X-ray Crystal Structure Analysis and FMO Calculation
1 X-ray Crystallographic Analysis of the Complex of VDR-LBD and Various Ligands
1.1 Structure of the Ligand-Binding Domain of RatVDR in Complex with a Non-Secosteroidal Vitamin D3 YR301
1.2 Structure of the Ligand-Binding Domain of hVDR in Complex with 14-Epi-19-Nortachysterol
1.3 Structure of the Ligand-Binding Domain of hVDR in Complex with 2α-Heteroarylalkyl Active Vitamin D3
2 FMO Calculations for Vitamin D Receptor Ligand-Binding Domain and Ligand Complexes
2.1 Subjects and Conditions of FMO Calculations
2.2 Interaction Energy Between VDR-LBD and VD3 Derivatives
2.3 Specific Interactions Between VDR-LBD and VD3 Derivatives
3 For the Design of New Active Ligands Effective for VDR-LBD
References
Cooperative Study Combining X-ray Crystal Structure Analysis and FMO Calculation: Interaction Analysis of FABP4 Inhibitors
1 Introduction
2 Methods
2.1 Discovery of Potent FABP4 Inhibitors
2.2 Biological Evaluation (FABP4 Binding Assay)
2.3 Crystallization and Structural Determination
2.4 FMO Analysis
3 Results and Discussion
3.1 Structures and Activities of Inhibitors
3.2 Crystallographic Structures
3.3 FMO Analysis
4 Conclusion
References
Application of FMO for Protein–ligand Binding Affinity Prediction
1 Introduction
2 Ensemble FMO
2.1 Computational Method
2.2 Application of Ensemble FMO
2.3 Discussion
3 Bandit Ensemble FMO
3.1 General Concept of Bandit Ensemble FMO
3.2 Computational Method
3.3 Application of Bandit Ensemble FMO
3.4 Discussion
4 Conclusion and Perspective
References
Recent Advances of In Silico Drug Discovery: Integrated Systems of Informatics and Simulation
1 Introduction
2 Merging of Informatics and Simulation in In Silico Drug Discovery Technology
3 Applications to Drug Discovery Targets
4 From In Silico Drug Discovery to AI Drug Discovery
References
Pharmaceutical Industry—Academia Cooperation
1 Background
1.1 Pharmaceutical Industry
1.2 Academia
1.3 Challenges
2 Examples of Academia-Evotec Ltd. (Industry, Drug Discovery Company) Collaborations
2.1 Molecular Interactions Identified by the Fragment Molecular Orbital Method
2.2 Computer-Aided Drug Design and the Hierarchical GPCR Modelling Protocol (HGMP)
2.3 Residence Time and Improved Clinical Efficacy
3 Conclusions and Solutions
References
Elucidating the Efficacy of Clinical Drugs Using FMO
1 Introduction
2 Theoretical Background and Methods
3 Sample Cases
3.1 Case 1: DPP-4 Inhibitors
3.2 Case 2: PPARα Modulators
4 Concluding Remarks
References
Application of Fragment Molecular Orbital Calculations to Functional Analysis of Enzymes
1 Introduction
2 Determining the Basis of Stereoselectivity for Artificially Designed R-Selective Amine Oxidase by Mutating Two Residues in Pig Kidney D-Amino Acid Oxidase (pkAOx)
3 Reaction Mechanism of Highly Specific L-threonine 3-dehydrogenase Belonging to the Short-Chain Dehydrogenase/Reductase Family
4 Summary
References
AnalysisFMO Toolkit: A PyMOL Plugin for 3D-Visualization of Interaction Energies in Proteins (3D-VIEP) Calculated by the FMO Method
1 Introduction
2 AnalysisFMO Toolkit
2.1 Environment Construction to Run AnalysisFMO Toolkit to Achieve the 3D-VIEP
2.2 Overview of AnalysisFMO Toolkit
2.3 RbAnalysisFMO Tool—Conversion of Output File from Any FMO Package into a CSV File
2.4 PyMOL Plugins: The “All-Pairs” Mode
2.5 PyMOL Plugins: The “Selected-Pairs” Mode
3 Application Examples
3.1 Interaction Energy Analysis for Fucose-Binding Lectin, BC2LC
3.2 Predicted Metal Coordination Mechanism of Bilirubin Oxidase
4 Summary
References
New Methods and Applications
FMO Interfaced with Molecular Dynamics Simulation
1 FMO-MD
1.1 Methodology
1.2 Applications
2 FMO-QM/MM-MD
2.1 Theory
2.2 Implementation
2.3 Applications
3 MM-MD/FMO
4 Perspective
References
Linear Combination of Molecular Orbitals of Fragments (FMO-LCMO) Method: Its Application to Charge Transfer Studies
1 Introduction
2 FMO-LCMO
2.1 Formulation
2.2 Accuracy Tests
3 Electron Transfer Analysis
3.1 Theory
3.2 Usage Example
4 Triplet-Triplet Annihilation
5 Concluding Remarks
References
Modeling of Solid and Surface
1 Introduction
2 Applications for Nano-Bio Interfaces
2.1 FMO Analysis of Peptides Specifically Adsorbed on a Silica Surface
2.2 FMO Analysis of Peptides Specifically Adsorbed on a Hydroxyapatite Surface
2.3 Analysis of Osteoblast Hydroxyapatite by Raman Spectroscopy and the FMO Method
2.4 FMO Analysis of Peptides Specifically Adsorbed on the Calcite Surface
3 Applications for General Organic–inorganic Interfaces
3.1 Analysis of Small Molecules and the AFM Tip Model on an NaCl Surface
3.2 Interaction Analysis Between Rubber Polymer and Silica Filler
4 Summary
References
Development of the Analytic Second Derivatives for the Fragment Molecular Orbital Method
1 Introduction
2 Mathematical Formulation
2.1 Analytic Gradient in FMO
2.2 Second Derivatives in FMO
2.3 Simulation of Spectra
3 Applications of Second Derivatives
3.1 IR Spectra
3.2 Raman Spectra
3.3 Localization of Normal Modes
3.4 IR and Raman Spectra of Radicals Using FMO-UDFT
3.5 Mapping Chemical Reaction Paths
4 Conclusion
References
The FMO-DFTB Method
1 Introduction
2 Basics of the DFTB Method
2.1 DFTB1
2.2 DFTB2
2.3 DFTB3
2.4 Long-Range Corrected DFTB
2.5 Parameters
3 Basics of the FMO-DFTB Method
3.1 Formalism of FMO-DFTB: Energy
3.2 Formalism of FMO-DFTB: Gradient
3.3 Implementation Notes
3.4 Computational Efficiency of FMO-DFTB
4 Selected Applications
4.1 Molecular Dynamics Simulations
4.2 Proteins
4.3 Chemoinformatics
4.4 Vibrational Frequency Analysis
4.5 Charge Transport Materials
5 Conclusion and Outlook
References
Self-Consistent Treatment of Solvation Structure with Electronic Structure Based on 3D-RISM Theory
1 Introduction
2 The 3D-RISM Theory
2.1 Formalism of the 3D-RISM Theory
2.2 Computational Scheme of the 3D-RISM Theory
3 Hybrid of 3D-RISM and Electronic Structure Theories
3.1 Basics of the 3D-RISM-SCF Method
3.2 Variational Condition of 3D-RISM-SCF
3.3 Computational Scheme of 3D-RISM-SCF
4 The FMO/3D-RISM Method
4.1 Formalism of the FMO/3D-RISM Method
4.2 Variational Condition of the FMO/3D-RISM Method
4.3 Efficient Computation of the Electrostatic Potential in the FMO/3D-RISM Method
4.4 Assessment of the FMO/3D-RISM Method
5 Summary and Perspective
References
New Methodology and Framework
New Methodology and Framework Information Science-Assisted Analysis of FMO Results for Drug Design
1 Necessity of Information Science-Assisted Analysis
2 What is AI?
2.1 Definition of AI, Machine Learning, and Data Mining.
3 Various Machine Learning Methods
3.1 Supervised Learning
3.2 Unsupervised Learning
4 Application Examples of Machine Learning Methods to FMO Docking Studies
4.1 β-secretase Inhibitors
5 PCA Results
5.1 Data
References
Extension to Multiscale Simulations
1 Construction of a Coarse-Grained Simulation Parameter Calculation Scheme
2 Applications Using the FMO-DPD Method
2.1 DPD Simulation
2.2 Percolation Analysis of the Polymer Electrolyte Membrane
2.3 Analysis of Lipid Membranes
3 Detailed Analysis Using a Reverse Map
3.1 Reverse Map Scheme
3.2 Test Examples
4 Summary
References
FMO-Based Investigations of Excited-State Dynamics in Molecular Aggregates
1 Introduction
2 Electronic Couplings and Model Hamiltonians
2.1 FMO-LCMO Method for CT Couplings
2.2 MLFMO-CIS Method for EET Couplings
2.3 Model Hamiltonians for Molecular Aggregates
3 Implementation in ABINIT-MP
4 Wavepacket Dynamics
5 Applications to Organic Electronic Materials
5.1 DNTT Thin Film
5.2 Pentacene/C60 Interface
6 Conclusions
References
Application of the Fragment Molecular Orbital Method to Organic Charge Transport Materials in Xerography: A Feasibility Study and a Charge Mobility Analysis
1 Introduction
1.1 Importance of Analyzing the Electronic Structure of Charge Transport Materials
1.2 Computation of Charge Mobility
1.3 The Objective of This Study
2 Validation of FMO for Organic Charge Transport Materials
2.1 Fragmentation of Organic Charge Transport Molecules
2.2 Validation of Fragmentations
2.3 Results of the FMO Validation
2.4 Summary of the FMO Feasibility Study
3 Calculation of Charge Mobility
3.1 Charge Mobility Based on the Marcus Theory
3.2 Simulation of the Charge Transport Rate Constant and Charge Mobility
3.3 Results Obtained with the Diffusion Model
3.4 Results Obtained with the KMC Model
4 Conclusion
References
Group Molecular Orbital Method and Python-Based Programming Approach
1 Introduction
2 Group Molecular Orbital Method
3 Implementation of the Algorithm Using Python
3.1 Binding Techniques
3.2 Implementation Based on Boost.Python
3.3 Implementation Based on Cython
3.4 Python-Based Rapid Development
4 Calculation Results
4.1 Python-Based Calculations
4.2 GMO Calculations
5 Summary
References
Multi-Level Parallelization of the Fragment Molecular Orbital Method in GAMESS
1 Introduction
2 Generalized Distributed Data Interface
2.1 Original Two-Layer Generalized Distributed Data Interface
3 Extension of GDDI into an Arbitrary Number of Layers
3.1 Parallel Load Balancing
4 OpenMP Parallelization
4.1 Parallelization on the K-Computer
4.2 OpenMP Parallelization on Theta
5 Conclusions
References