There has been a great surge in the usage of computational drug design techniques over the past 20 years. Filling the need for an easily understood, nonmathematical text on drug design, Computational Drug Designexplores the wide range of computational techniques available for the drug design process, and puts them in the framework of the drug design process. This valuable learning source provides students, computational chemists, organic, medicinal and pharmaceutical chemists, and biochemists with a solid perspective on the entire breadth of the field.
Helps you choose the right computational tools and techniques to meet your drug design goals
Preface.
Acknowledgments.
Symbols used in this book.
1. Introduction.
1.1 A Difficult Problem.
1.2 An Expensive Problem.
1.3 Where Computational Techniques are Used.
Bibliography.
PART I: THE DRUG DESIGN PROCESS.
2. Properties That Make a Molecule a Good Drug.
2.1 Compound Testing.
2.1.1 Biochemical Assays.
2.1.2 Cell-based Assays.
2.1.3 Animal Tests.
2.1.4 Human Clinical Trials.
2.2 Molecular Structure.
2.2.1 Activity.
2.2.2 Bioavailability and Toxicity.
2.2.3 Drug Side Effects.
2.2.4 Multiple Drug Interactions.
2.3 Metrics for Drug-Likeness.
2.4 Exceptions to the Rules.
Bibliography.
3. Target Identification.
3.1 Primary Sequence and Metabolic Pathway.
3.2 Crystallography.
3.3 2D NMR.
3.4 Homology Models.
3.5 Protein Folding.
Bibliography.
4. Target Characterization.
4.1 Analysis of Target Mechanism.
4.1.1 Kinetics & Crystallography.
4.1.2 Automated Crevice Detection.
4.1.3 Transition Structures and Reaction Coordinates.
4.1.4 Molecular Dynamics Simulations.
4.2 Where the Target is Expressed.
4.3 Pharmacophore Identification.
4.4 Choosing an Inhibitor Mechanism.
Bibliography.
5. The Drug Design Process for a Known Protein Target.
5.1 The Structure-based Design Process.
5.2 Initial Hits.
5.3 Compound Refinement.
5.4 ADMET.
5.5 Drug Resistance.
Bibliography.
6. The Drug Design Process for an Unknown Target.
6.1 The Ligand-based Design Process.
6.2 Initial Hits.
6.3 Compound Refinement.
6.4 ADMET.
Bibliography.
7. Drug Design for Other Targets.
7.1 DNA Binding.
7.2 RNA as a Target.
7.3 Allosteric Sites.
7.4 Receptor Targets.
7.5 Steroids.
7.6 Targets Inside of Cells.
7.7 Targets within the Central Nervous System.
7.8 Irreversibly binding inhibitors.
7.9 Up-regulating Target Activity.
Bibliography.
8. Compound Library Design.
8.1 Targeted Libraries vs. Diverse Libraries.
8.2 From Fragments vs. From Reactions.
8.3 Non-enumerative Techniques.
8.4 Drug-likeness and Synthetic Accessibility.
8.5 Analyzing Chemical Diversity and Spanning Known Chemistries.
8.6 Compound Selection Techniques.
Bibliography.
PART II: COMPUTATIONAL TOOLS AND TECHNIQUES.
9. Homology Model Building.
9.1 How much Similarity is Enough?
9.2 Steps for Building a Homology Model.
9.2.1 Step 1. Template identification.
9.2.1 Step 2. Alignment between the unknown and the template.
9.2.3 Step 3. Manual adjustments to the alignment.
9.2.4 Step 4. Replace template side chains with model side chains.
9.2.5 Step 5. Adjust model for insertions and deletions.
9.2.6 Step 6. Optimization of the model.
9.2.7 Step 7. Model validation.
9.2.8 Step 8. If errors are found, iterate back to previous steps.
9.3 Reliability of Results.
Bibliography.
10. Molecular Mechanics.
10.1 Introduction to the Underlying Model.
10.2 Implications of the Model.
10.3 Molecular Dynamics.
10.4 Monte Carlo Methods.
Bibliography.
11. Protein Folding.
11.1 The Difficulty of the Problem.
11.2 Algorithms.
11.3 Reliability of Results.
11.4 Conformational Analysis.
Bibliography.
12. Docking.
12.1 Introduction.
12.2 Search Algorithms.
12.2.1 Searching the Entire Space.
12.2.1 Grid Potentials vs. Full Force Field.
12.2.2 Flexible Active Sites.
12.2.3 Ligands Covalently Bound to the Active Site.
12.2.4 Hierarchical Docking Algorithms.
12.3 Scoring.
12.3.1 Energy Expressions and Consensus Scoring.
12.3.2 Binding Free Energies.
12.3.3 Solvation.
12.3.4 Ligands Covalently Bound to Active Site.
12.3.5 Metrics for Goodness of Fit.
12.4 Validation of Results.
12.5 Comparison of Existing Search & Scoring Methods.
12.6 Special Systems.
12.7 The Docking Process.
12.7.1. Protein preparation..
12.7.2. Building the ligand..
12.7.3. Setting the bounding box..
12.7.4. Docking options..
12.7.5. Running the docking calculation..
12.7.6. Analysis of results..
Bibliography.
13. Pharmacophore Models.
13.1 Components of a Pharmacophore Model.
13.2 Creating a Pharmacophore Model from Active Compounds.
13.3 Creating a Pharmacophore Model from the Active Site.
13.4 Searching compound databases.
13.5 Reliability of Results.
Bibliography.
14. QSAR.
14.1 Conventional QSAR vs. 3D-QSAR.
14.2 The QSAR Process.
14.3 Descriptors.
14.4 Automated QSAR Programs.
14.5 QSAR vs. Other Fitting Methods.
Bibliography.
15. 3D-QSAR.
15.1 The 3D-QSAR Process.
15.2 3D-QSAR Software Packages.
15.3 Summary.
Bibliography.
16. Quantum Mechanics in Drug Design.
16.1 Quantum Mechanics Algorithms and Software.
16.2 Modeling Systems with Metal Atoms.
16.3 Increased Accuracy.
16.4 Computing Reaction Paths.
16.5 Computing Spectra.
Bibliography.
17. De Novo and Other AI Techniques.
17.1 De Novo Building of Compounds.
17.2 Non-quantitative Predictions.
17.3 Quantitative Predictions.
Bibliography.
18. Cheminformatics.
18.1 SMILES, SLN, and Other Chemical Structure Representations.
18.2 Similarity & Substructure Searching.
18.3 2D to 3D Structure Generation.
18.4 Clustering Algorithms.
18.5 Screening Results Analysis.
18.6 Database Systems.
Bibliography.
19. ADMET.
19.1 Oral Bioavailability.
19.2 Drug Half-life in the Blood Stream.
19.3 Blood-brain Barrier Permeability.
19.4 Toxicity.
Bibliography.
20. Multiobjective Optimization.
Bibliography.
21. Automation of Tasks.
PART III. RELATED TOPICS.
22. Bioinformatics.
Bibliography.
23. Simulations at the Cellular and Organ Level..
23.1 Cellular Simulations.
23.2 Organ Simulations.
Bibliography.
24. Synthesis Route Prediction.
Bibliography.
25. Proteomics.
Bibliography.
26. Prodrug Approaches.
Bibliography.
27. Future Developments in Drug Design.
27.1 Individual Patient Genome Sequencing.
27.2 Analysis of the Entire Proteome.
27.3 Drugs Customized for an Ethnic Group or Individual Patient.
27.4 Genetic Manipulation.
27.5 Cloning.
27.6 Stem Cells.
27.7 Longevity.
Bibliography.
Appendix A. About the CD.
Glossary.
Index.