Computer-Aided Drug Discovery Methods: A Brief Introduction explores the cutting-edge field at the intersection of computational science and medicinal chemistry. This comprehensive volume navigates from foundational concepts to advanced methodologies, illuminating how computational tools accelerate the discovery of new therapeutics.
Beginning with an overview of drug discovery principles, the book explains topics such as pharmacophore modeling, molecular dynamics simulations, and molecular docking. It discusses the application of density functional theory and the role of artificial intelligence in therapeutic development, showcasing successful case studies and innovations in COVID-19 research.
Ideal for undergraduate and graduate students, as well as researchers in academia and industry, this book serves as a vital resource in understanding the complex landscape of modern drug discovery. It emphasizes the synergy between computational methods and experimental validation, shaping the future of pharmaceutical sciences toward more effective and targeted therapies.
Readership
- Undergraduate/Graduate and Research
Table of Contents
CONTENTS
PREFACE
CHAPTER 1 DRUG DISCOVERY
INTRODUCTION
- Introduction to Drug Discovery
- Target Identification
- Lead Generation
- Lead Optimization
- Preclinical Development
- Clinical Development
- Regulatory Approval
- Post-Marketing Surveillance
- Challenges and Advancements
- Target and Lead Identification: Unveiling the Path to Therapeutic Success
- Target Identification
- Genetic Approaches
- Proteomic Approaches
- Chemical Biology Approaches
- Lead Identification
- High-Throughput Screening (HTS)
- Virtual Screening
- Natural Product Screening
- Challenges and Advancements
- Drug Solubility: Unlocking Formulation Challenges for Effective Therapeutics
- Importance of Drug Solubility
- Bioavailability
- Formulation Development
- Drug Delivery Systems
- Drug Likeness: Guiding Principles in Drug Design and Discovery
- Importance of Drug Likeness
- Factors Influencing Drug Likeness
- Drug Databases: Empowering Drug Discovery and Knowledge Integration
- Importance of Drug Databases
- Key Components of Drug Databases
- Impact of Drug Databases
- Drug ADME: Understanding the Journey of a Drug in the Body
- Absorption
- Distribution
- Metabolism
- Excretion
- Implications for Drug Development
- Bioavailability and Efficacy
- Safety and Toxicity
- Drug-Drug Interactions
- CONCLUSION
REFERENCES
CHAPTER 2 MOLECULAR DYNAMICS IN COMPUTER-AIDED DRUG DISCOVERY: UNVEILING INSIGHTS INTO BIOMOLECULAR INTERACTIONS
INTRODUCTION
- Principles of Molecular Dynamics Simulations
- Newton's equations of motion
- Methodologies and Techniques
- System Setup and Preparation
- System Definition
- Force Field Selection
- Initial Conditions
- Simulation Box and Boundary Conditions
- Solvent or Environment Setup
- Energy Minimization and Equilibration
- Solvent Models and Boundary Conditions
- Treatment of Long-range Electrostatics
- Force Field Parameterization and Validation
- Applications of Molecular Dynamics in Drug Discovery
- Protein-ligand Binding and Stability
- Protein-protein Interactions
- System Setup
- Force Field Selection
- Simulation Protocol
- Binding Mechanism and Recognition
- Allosteric Effects and Conformational Changes
- Role of Water and Solvent Effects
- Protein Dynamics and Conformational Changes
- Membrane Protein Simulations
- Membrane Model Selection
- Force Field Selection
- System Setup
- Simulation Protocol
- Lipid Dynamics and Protein-Lipid Interactions
- Protein Conformational Changes and Function
- Membrane Protein Dynamics and Allosteric Communication
- Solvent Effects and Drug Permeability
- Solvent Representation
- Drug-Solvent Interactions
- Membrane Permeability Studies
- Free Energy Calculations
- Transporter and Channel Interactions
- Solvent Effects on Drug Binding
- Enhanced Sampling Methods
- Importance of Enhanced Sampling Techniques
- Replica Exchange Molecular Dynamics (REMD)
- Meta-dynamics and Biasing Potentials
- Markov State Models (MSMs)
- Allosteric Modulation and Binding Site Identification
- Allosteric Modulation of Protein Function
- Allosteric Site Identification and Characterization
- Drug Design Targeting Allosteric Sites
- Drug Optimization and Binding Free Energy Calculation
- Free Energy Calculations in Drug Discovery
- Ligand Binding Affinity Estimation
- Free Energy Perturbation (FEP) and Thermodynamic Integration (TI)
- Challenges and Limitations of Binding Free Energy Calculations
- Drug Resistance and Target Flexibility
- Understanding Drug Resistance Mechanisms
- Simulating Drug-resistant Mutants
- Flexibility in Target Proteins and its Implications
- Flexible Docking and Hybrid Approaches
- Integration with Experimental Techniques
- Advancements and Future Directions
- Accelerating MD Simulations with GPU Computing
- Hybrid Methods: QM/MM and MD Simulations
- Challenges and Outlook
- Computational Cost and Scalability
- Accuracy and Limitations of Force Fields
CONCLUSION
REFERENCES
CHAPTER 3 PHARMACOPHORE MODELLING AND VIRTUAL SCREENING
INTRODUCTION
- Pharmacophore Modelling: Unveiling the Key to Drug Design
- Understanding Pharmacophore Modelling
- Process and Techniques
- Significance in Drug Design
- Applications in the Pharmaceutical Industry
- Recent Advancements
- Virtual Screening
- Principles of Virtual Screening
- Virtual Screening Approaches
- Applications of Virtual Screening in Drug Discovery
- Challenges in Virtual Screening
- Integration of Virtual Screening with Experimental Approaches
- Advancements in Virtual Screening
- Future Perspectives
- QSAR Methods in Computer-Aided Drug Discovery
- Principles of QSAR
- Development of QSAR Models
- Applications of QSAR in Drug Discovery
- Challenges and Limitations
- Future Perspectives
- 3D QSAR: Enhancing Drug Discovery through Three-Dimensional Quantitative Structure-
- Activity Relationship Analysis
- Importance of 3D QSAR
- Principles of 3D QSAR
- Applications of 3D QSAR
- Force Fields in Computer-Aided Drug Discovery: Unleashing the Power of Molecular Simulations
- Understanding Force Fields
- Force Field Components
- Parameterization and Validation
- Applications in Computer-Aided Drug Discovery
- Challenges and Future Perspectives
CONCLUSION
REFERENCES
CHAPTER 4 MOLECULAR DOCKING IN COMPUTER-AIDED DRUG DISCOVERY: A POWERFUL TOOL FOR TARGETED THERAPEUTICS
INTRODUCTION
- Principles of Molecular Docking
- Protein-ligand Interaction
- Docking Algorithms
- Scoring Functions
- Validation and Accuracy Assessment
- Methodologies and Techniques
- Structure-based Drug Design
- Ligand-based Drug Design
- Virtual Screening
- Applications of Molecular Docking
- Target Identification and Validation
- Target Identification
- Target Validation
- Lead Optimization and Hit-to-Lead Development
- Hit-to-Lead Development
- Lead Optimization
- De Novo Drug Design
- Advancements in Molecular Docking
- Enhanced Scoring Functions
- Fragment-based Docking
- Solvent Effects and Explicit Water Modeling
- Challenges and Limitations
- Future Perspectives and Outlook
- Integration of Machine Learning and AI
- Multi-Target Docking and Polypharmacology
- Incorporation of Dynamics and Flexibility
- Improved Scoring Functions and Binding Free Energy Calculations
- Integration of Structural and Experimental Data
- Application to New Therapeutic Areas and Target Classes
- Combination with Experimental High-Throughput Screening
CONCLUSION
REFERENCES
CHAPTER 5 THE USE OF DENSITY FUNCTIONAL THEORY IN COMPUTER-AIDED DRUG DISCOVERY
INTRODUCTION
- Principles of Density Functional Theory
- Electron Density
- Kohn-Sham Equations
- Exchange-Correlation Functional
- Approximations
- Energy and Property Calculations
- Applications
- Application of Density Functional Theory in Drug Discovery
- Molecular Structure and Conformation
- Electronic Properties and Spectroscopy
- Reaction Energetics and Mechanisms
Author
- Manos C. Vlasiou
