Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- Section one Overviews
- Section two Molecules for Chemical Genomics
- Section Three Basics of High-Throughput Screening
- Section Four Chemical Genomics Assays and Screens
- Chapter 12 Basics of HTS Assay Design and Optimization
- Chapter 13 Molecular Sensors for Transcriptional and Post-Transcriptional Assays
- Chapter 14 Time-Resolved Fluorescence Resonance Energy Transfer Technologies in HTS
- Chapter 15 Compound Profiling with High-Content Screening Methodology
- Chapter 16 Use of Transgenic Zebrafish in a Phenotypic Screen for Angiogenesis Inhibitors
- Chapter 17 Flow Cytometry Multiplexed Screening Methodologies
- Chapter 18 Label-Free Biosensor Technologies in Small Molecule Modulator Discovery
- Chapter 19 Basic Principles and Practices of Computer-Aided Drug Design
- Chapter 20 Computational Approach for Drug Target Identification
- Section five Chemical Genomics and Medicine
- Index
- References
Chapter 19 - Basic Principles and Practices of Computer-Aided Drug Design
from Section Four - Chemical Genomics Assays and Screens
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Contributors
- Preface
- Section one Overviews
- Section two Molecules for Chemical Genomics
- Section Three Basics of High-Throughput Screening
- Section Four Chemical Genomics Assays and Screens
- Chapter 12 Basics of HTS Assay Design and Optimization
- Chapter 13 Molecular Sensors for Transcriptional and Post-Transcriptional Assays
- Chapter 14 Time-Resolved Fluorescence Resonance Energy Transfer Technologies in HTS
- Chapter 15 Compound Profiling with High-Content Screening Methodology
- Chapter 16 Use of Transgenic Zebrafish in a Phenotypic Screen for Angiogenesis Inhibitors
- Chapter 17 Flow Cytometry Multiplexed Screening Methodologies
- Chapter 18 Label-Free Biosensor Technologies in Small Molecule Modulator Discovery
- Chapter 19 Basic Principles and Practices of Computer-Aided Drug Design
- Chapter 20 Computational Approach for Drug Target Identification
- Section five Chemical Genomics and Medicine
- Index
- References
Summary
Technological advances in pharmaceutical research during the past few decades have transformed drug discovery and development from empirical trial-and-error methods to development of mechanism-based compounds, often referred to as targeted therapy. In the targeted therapy approach, the scientific endeavor is to find drugs that can act on specific targets, the majority of which are proteins. Functions, or more typically dysfunctions, of these targeted cellular proteins typically underlie diseases. The therapeutic concept assumes that binding of drugs to the target proteins can alter the proteins’ function in the pathological states of cells. A favorable outcome of drug administration is to nullify or at least mitigate the disease. Development of a drug for treatment of a disease requires many resources as well as much time and collaborative effort of scientists from different disciplines, including chemistry, biology, and pharmacology. In the past decade, the computer has emerged as a powerful tool that can facilitate drug discovery and development. The initial step in the process calls for a correlation of the structures of known compounds with their activities in order to begin the search for new classes of molecules with the requisite activity. In recent years, more sophisticated computational molecular modeling methods have been developed and applied to the development of drugs, from initial discovery of hits and lead optimization to prediction of absorption, distribution, metabolism, and excretion (ADME) properties to toxicity (TOX) evaluation. In this chapter, we focus on the well-established computational methods applied to the identification and optimization of lead compounds. We first discuss the computational methodologies currently used in drug discovery. The strategies used for discovery and optimization of novel ligands by combining different computational tools are described next, and we then present case studies in which computational methods have been employed in drug design. We conclude by highlighting the current challenges and future perspectives of computer-aided drug design (CADD).
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- Information
- Chemical Genomics , pp. 259 - 278Publisher: Cambridge University PressPrint publication year: 2012