In silico drug design : repurposing techniques and methodologies /

In Silico Drug Design: Repurposing Techniques and Methodologies explores the application of computational tools that can be utilized for this approach. The book covers theoretical background and methodologies of chem-bioinformatic techniques and network modeling and discusses the various applied str...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Roy, Kunal, 1971- (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London ; San Diego, CA : Academic Press, [2019]
Temas:
Drugs > Design > Methodology.
Drugs > Design > Data processing.
Drug development > Methodology.
Pharmaceutical chemistry.
Chemistry, Pharmaceutical
Drug Development > methods
M�edicaments > Conception > M�ethodologie.
M�edicaments > Conception > Informatique.
M�edicaments > D�eveloppement > M�ethodologie.
Chimie pharmaceutique.
MEDICAL > Pharmacology.
Pharmaceutical chemistry
Drugs > Design > Data processing
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover; In Silico Drug Design: Repurposing Techniques and Methodologies; Copyright; Dedication; Contents; Contributors; About the Editor; Preface; Section 1: Introduction; Chapter 1: Drug Repositioning: New Opportunities for Older Drugs; 1. Introduction; 2. The Fundamentals for Drug Repositioning; 3. Different Approaches to the Development of New Indications for Old Drugs; 3.1. Serendipity and Text Mining; 3.2. Observation of Unexpected Side Effects; 3.3. Detection of a New Role for the Existing Targets; 3.4. Identification of New Drug-Target Interactions
  • 3.5. Drug Repositioning for Specific Disease Phenotypes4. Conclusions; Acknowledgment; References; Chapter 2: Computational Drug Design Methods-Current and Future Perspectives; 1. Introduction; 2. Overview of Current Approaches Used in Computer-Aided Drug Design; 2.1. Classification of Computer-Aided Drug Design Methods; 2.1.1. Structure-Based Methods; 2.1.2. Ligand-Based Methods; 2.1.3. Hybrid Methods and Methods Based on End-Points; 2.2. Main Applications of Computer-Aided Drug Design; 2.2.1. Hit Finding; 2.2.2. Lead Optimization
  • 3. Case Studies: Successful Applications of Computer-Aided Drug Design4. Trending Concepts and Technologies; 4.1. Big Data; 4.2. Web Servers; 4.3. Workflows; 4.4. Machine Learning; 4.4.1. Applications of Machine Learning in Drug Discovery; 4.4.2. Deep Learning; 4.4.3. Artificial Intelligence; 4.5. Molecular Dynamics; 4.5.1. General Aspects of Molecular Dynamics; 4.5.2. Applications of Molecular Dynamics in Drug Discovery; 5. Challenges and Emerging Problems in Computer-Aided Drug Design; 5.1. Integration With Other Techniques
  • 5.2. Absorption, Distribution, Metabolism, and Excretion, and Toxicity Prediction5.3. Difficult and Emerging Targets; 5.4. Neglected Diseases; 5.5. Chemical Space; 5.6. Advance Multitarget Drug Discovery and Polypharmacology; 5.7. Training, Teaching, and Divulgation; 6. Conclusions; Acknowledgments; References; Further Reading; Section 2: Theoretical Background and Methodologies; Chapter 3: In Silico Drug Design Methods for Drug Repurposing; 1. Drug Repurposing; 2. Computational Approaches for Drug Repositioning; 2.1. Target-Based Methods; 2.2. Knowledge-Based Methods
  • 2.3. Signature-Based Methods2.4. Network-Based Methods; 2.5. Target Mechanism-Based Methods; 3. Examples of Successful Drug Repositioning; 4. Opportunities and Limitations of In Silico Drug Repositioning; References; Further Reading; Chapter 4: Computational Drug Repurposing for Neurodegenerative Diseases; 1. Neurodegenerative Diseases; 2. Drug Repurposing; 3. Activity-Based Drug Repurposing; 3.1. Phenotypic Screening Approach; 3.2. Target-Based Screening; 4. Computational Drug Repurposing; 4.1. Structure-Based Virtual Screening (Molecular Docking); 4.2. Ligand-Based Methods

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