Comprehensive Medicinal Chemistry II book cover

Comprehensive Medicinal Chemistry II

Volume 4: COMPUTER-ASSISTED DRUG DESIGN

Computer-assisted Drug Design (CADD) reviews the use of computational methods and how these can aid the drug discovery process. Experts review in-silico approaches for the design and improvement of drug properties. Techniques for modelling, analysing and optimization of properties including potency, selectivity and ADMET are presented. Methods discussed include the Quantitative Structure Activity Relationship (QSAR), ligand and structure-based, lead discovery and new directions. Ideal for students and researchers in chemistry, biochemistry, medicinal chemistry and pharmacology and scientists working in the pharmaceutical industries.

Audience
For students and researchers in chemistry, biochemistry, medicinal chemistry and pharmacology and scientists working in the pharmaceutical industries.

Hardbound, 881 Pages

Published: November 2006

Imprint: Elsevier

ISBN: 978-0-08-044517-5

Contents

  • Volume 4 Computer-Assisted Drug Design
    Introduction to Computer-Assisted Drug Design
    4.01 Introduction to the Volume and Overview of Computer-Assisted Drug Design in the Drug Discovery Process
    4.02 Introduction to Computer-Assisted Drug Design – Overview and Perspective for the Future
    4.03 Quantitative Structure–Activity Relationship – A Historical Perspective and the Future
    4.04 Structure-Based Drug Design – A Historical Perspective and the Future
    Core Concepts and Methods – Ligand-Based
    4.05 Ligand-Based Approaches: Core Molecular Modeling
    4.06 Pharmacophore Modeling: 1 – Methods
    4.07 Predictive Quantitative Structure–Activity Relationship Modeling
    4.08 Compound Selection Using Measures of Similarity and Dissimilarity
    Core Concepts and Methods – Target Structure-Based
    4.09 Structural, Energetic, and Dynamic Aspects of Ligand–Receptor Interactions
    4.10 Comparative Modeling of Drug Target Proteins
    4.11 Characterization of Protein-Binding Sites and Ligands Using Molecular Interaction Fields
    4.12 Docking and Scoring
    4.13 De Novo Design
    Core Methods and Applications – Ligand and Structure-Based
    4.14 Library Design: Ligand and Structure-Based Principles for Parallel and Combinatorial Libraries
    4.15 Library Design: Reactant and Product-Based Approaches
    4.16 Quantum Mechanical Calculations in Medicinal Chemistry: Relevant Method or a Quantum Leap Too Far?
    Applications to Drug Discovery – Lead Discovery
    4.17 Chemogenomics in Drug Discovery – The Druggable Genome and Target Class Properties
    4.18 Lead Discovery and the Concepts of Complexity and Lead-Likeness in the Evolution of Drug Candidates
    4.19 Virtual Screening
    4.20 Screening Library Selection and High-Throughput Screening Analysis/Triage
    Applications to Drug Discovery – Ligand-Based Lead Optimization
    4.21 Pharmacophore Modeling: 2 – Applications
    4.22 Topological Quantitative Structure–Activity Relationship Applications: Structure Information Representation in Drug Discovery
    4.23 Three-Dimensional Quantitative Structure–Activity Relationship: The State of the Art
    Applications to Drug Discovery – Target Structure-Based
    4.24 Structure-Based Drug Design – The Use of Protein Structure in Drug Discovery
    4.25 Applications of Molecular Dynamics Simulations in Drug Design
    4.26 Seven Transmembrane G Protein-Coupled Receptors: Insights for Drug Design from Structure and Modeling
    4.27 Ion Channels: Insights for Drug Design from Structure and Modeling
    4.28 Nuclear Hormone Receptors: Insights for Drug Design from Structure and Modeling
    4.29 Enzymes: Insights for Drug Design from Structure
    New Directions
    4.30 Multiobjective/Multicriteria Optimization and Decision Support in Drug Discovery
    4.31 New Applications for Structure-Based Drug Design
    4.32 Biological Fingerprints

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