A Pharmacology Primer : Techniques for More Effective and Strategic Drug Discovery

FIGURE 1.1 Pioneers of pharmacology. (A) Paul Ehrlich (1854e915). Born in Silesia, Ehrlich graduated from Leipzig University to go on to a distinguished career as head of institutes in Berlin and Frankfurt. His studies with dyes and bacteria formed the basis of early ideas regarding recognition of biological substances by chemicals. (B) John Newport Langley (1852e926). Though he began reading mathematics and history in Cambridge in 1871, Langley soon took to physiology. He succeeded the great physiologist M. Foster to the chair of physiology in Cambridge in 1903 and branched out into pharmacological studies of the autonomic nervous system. These pursuits led to germinal theories of receptors. (C) Alfred J. Clark (1885e941). Beginning as a demonstrator in pharmacology in King's College (London), Clark went on to become Professor of pharmacology at University College London. From there he took the chair of pharmacology in Edinburgh. Known as the originator of modern receptor theory, Clark applied chemical laws to biological phenomena. His books on receptor theory formed the basis of modern pharmacology. What is pharmacology? Chapter | 1 3 FIGURE 1.3 Schematic diagram of potential drug targets. Molecules can affect the function of numerous cellular components both in the cytosol and on the membrane surface. There are many families of receptors that traverse the cellular membrane and allow chemicals to communicate with the interior of the cell. What is pharmacology? Chapter | 1 5 What is pharmacology? Chapter | 1 7 FIGURE 1.6 Depiction of the structure of seven transmembrane domain receptors, one of the most if not the most important therapeutic targets available in the human genome. Chemicals access the receptor through the extracellular space by binding to the extracellular domains of the protein. This causes a conformational change in the protein that alters the interaction of signaling proteins in the cell cytosol. This latter process results in the initiation of cellular signaling. HTU A Pharmacology Primer Copyright Dedication Preface to sixth edition 1. What is pharmacology? 1.1 About this book 1.2 What is pharmacology? 1.3 The receptor concept 1.4 Pharmacological test systems 1.5 The nature of drug receptors 1.6 From the snapshot to the movie 1.7 Pharmacological intervention and the therapeutic landscape 1.8 System-independent drug parameters: affinity and efficacy 1.9 What is affinity? 1.10 The Langmuir adsorption isotherm 1.11 What is efficacy? 1.12 Dose–response curves 1.12.1 Potency and maximal response 1.12.2 P-scales and the representation of potency 1.13 Chapter summary and conclusions 1.14 Derivations: conformational selection as a mechanism of efficacy References 2. How different tissues process drug response 2.1 The ‘eyes to see’: pharmacologic assays 2.2 The biochemical nature of stimulus–response cascades 2.3 The mathematical approximation of stimulus–response mechanisms 2.4 Influence of stimulus–response cascades on dose–response curve slopes 2.5 System effects on agonist response: full and partial agonists 2.6 Differential cellular response to receptor stimulus 2.6.1 Choice of response pathway 2.6.2 Augmentation or modulation of stimulus pathway 2.6.3 Differences in receptor density 2.6.4 Target-mediated trafficking of stimulus 2.7 Receptor desensitization and tachyphylaxis 2.8 The measurement of drug activity 2.9 Advantages and disadvantages of different assay formats 2.10 Drug concentration as an independent variable 2.10.1 Dissimulation in drug concentration 2.10.2 Free concentration of drug 2.11 Chapter summary and conclusions 2.12 Derivations 2.12.1 Series hyperbolae can be modeled by a single hyperbolic function 2.12.2 Successive rectangular hyperbolic equations necessarily lead to amplification 2.12.3 Saturation of any step in a stimulus cascade by two agonists leads to identical maximal final responses for the two agonists 2.12.4 Procedure to measure free drug concentration in the receptor compartment References 3. Drug–receptor theory 3.1 About this chapter 3.2 Drug–receptor theory 3.3 The use of mathematical models in pharmacology 3.4 Some specific uses of models in pharmacology 3.5 Mass action building blocks 3.6 Classical model of receptor function 3.7 The operational model of receptor function 3.8 Two-state theory 3.9 The ternary complex model 3.10 The extended ternary complex model 3.11 Constitutive receptor activity and inverse agonism 3.12 The cubic ternary complex model 3.13 Multistate receptor models and probabilistic theory 3.14 Chapter summary and conclusions 3.15 Derivations 3.15.1 Radioligand binding to receptor dimers demonstrating cooperative behavior 3.15.2 Effect of variation in an HIV-1 binding model 3.15.3 Derivation of the operational model 3.15.4 Operational model forcing function for variable slope 3.15.5 Derivation of two-state theory 3.15.6 Derivation of the extended ternary complex model 3.15.7 Dependence of constitutive activity on receptor density 3.15.8 Derivation of the cubic ternary complex model References 4. Pharmacological assay formats: binding 4.1 The structure of this chapter 4.2 Binding theory and experiment 4.2.1 Saturation binding 4.2.2 Displacement binding 4.2.3 Kinetic binding studies 4.3 Complex binding phenomena: agonist affinity from binding curves 4.4 Experimental prerequisites for correct application of binding techniques 4.4.1 The effect of protein concentration on binding curves 4.4.2 The importance of equilibration time for equilibrium between two ligands 4.5 Binding in allosteric systems 4.6 Chapter summary and conclusions 4.7 Derivations 4.7.1 Displacement binding: competitive interaction 4.7.2 Displacement binding: noncompetitive interaction 4.7.3 Displacement of a radioligand by an allosteric antagonist 4.7.4 Relationship between IC50 and KI for competitive antagonists 4.7.5 Maximal inhibition of binding by an allosteric antagonist 4.7.6 Relationship between IC50 and KI for allosteric antagonists 4.7.7 Two-stage binding reactions 4.7.8 Effect of G-Protein coupling on observed agonist affinity 4.7.9 Effect of excess receptor in binding experiments: saturation binding curve 4.7.10 Effect of excess receptor in binding experiments: displacement experiments 4.7.11 Derivation of an allosteric binding model References 5. Drug targets and drug-target molecules 5.1 Defining biological targets 5.2 Specific types of drug targets 5.2.1 G-protein-coupled receptors 5.2.2 Ion channels 5.2.3 Enzymes 5.2.4 Nuclear receptors 5.2.5 Nucleotide-based drug targets 5.2.5.1 DNA targets 5.2.5.2 RNA targets 5.3 Small drug-like molecules 5.3.1 Hybrid molecules 5.3.2 Chemical sources for potential drugs 5.4 Biologics 5.4.1 Replacement proteins 5.4.2 Eliminating ‘undruggable’ proteins through PROTACs 5.4.3 Peptides 5.4.4 Antibodies 5.4.5 Immunotherapy 5.4.6 Vaccines 5.4.7 Nucleic acid–based drug species 5.4.7.1 DNA (gene therapy) 5.4.7.2 CRISPR 5.4.7.3 Messenger RNA 5.5 Summary and conclusions References Further reading 6. Agonists: the measurement of affinity and efficacy in functional assays 6.1 Functional pharmacological experiments 6.2 The choice of functional assays 6.3 Recombinant functional systems 6.4 Functional experiments: dissimulation in time 6.5 Experiments in real time versus stop-time 6.6 Quantifying agonism: the Black–Leff operational model of agonism 6.6.1 Affinity-dependent versus efficacy-dependent agonist potency 6.6.2 Secondary and tertiary testing of agonists 6.7 Biased signaling 6.7.1 Receptor selectivity 6.8 Null analyses of agonism 6.8.1 Partial agonists 6.8.2 Full agonists 6.9 Comparing full and partial agonist activities: Log(max/EC50) 6.10 Chapter summary and conclusions 6.11 Derivations 6.11.1 Relationship between the EC50 and affinity of agonists 6.11.2 Method of Barlow, Scott, and Stephenson for affinity of partial agonists 6.11.3 Maximal response of a partial agonist is dependent on efficacy 6.11.4 System independence of full agonist potency ratios 6.11.5 Measurement of agonist affinity: method of Furchgott 6.11.6 Agonism as a positive allosteric modulation of receptor–signaling protein interaction to derive ΔLog(max/EC50) ratios References 7. Orthosteric drug antagonism 7.1 Introduction 7.2 Kinetics of drug–receptor interaction 7.3 Surmountable competitive antagonism 7.3.1 Schild analysis 7.3.2 Patterns of Dose–Response curves that preclude schild analysis 7.3.3 Best practice for the use of schild analysis 7.3.4 Analyses for inverse agonists in constitutively active receptor systems 7.3.5 Analyses for partial agonists 7.3.6 The method of Lew and Angus: nonlinear regression analysis 7.4 Noncompetitive antagonism 7.5 Agonist–antagonist hemiequilibria 7.6 Resultant analysis 7.7 Antagonism in vivo 7.7.1 Antagonists with efficacy in vivo 7.7.2 Kinetics of target coverage 7.7.3 Kinetics of dissociation 7.7.4 Estimating antagonist dissociation with hemiequilibria 7.8 Blockade of indirectly acting agonists 7.9 Irreversible antagonism 7.10 Chemical antagonism 7.11 Chapter summary and conclusions 7.12 Derivations 7.12.1 Derivation of the Gaddum equation for competitive antagonism 7.12.2 Derivation of the Gaddum equation for noncompetitive antagonism 7.12.3 Derivation of the schild equation 7.12.4 Functional effects of an inverse agonist with the operational model 7.12.5 pA2 measurement for inverse agonists 7.12.6 Functional effects of a partial agonist with the operational model 7.12.7 pA2 measurements for partial agonists 7.12.8 Method of Stephenson for partial agonist affinity measurement 7.12.9 Derivation of the Method of Gaddum for noncompetitive antagonism 7.12.10 Relationship of pA2 and pKB for insurmountable orthosteric antagonism 7.12.11 Resultant analysis 7.12.12 Blockade of indirectly acting agonists 7.12.13 Chemical antagonism: abstraction of agonist concentration 7.12.14 Chemical antagonism: abstraction of antagonist concentration References 8. Allosteric modulation 8.1 Introduction 8.2 The nature of receptor allosterism 8.3 Unique effects of allosteric modulators 8.4 Functional study of allosteric modulators 8.4.1 Phenotypic allosteric modulation profiles 8.4.2 Allosteric agonism 8.4.3 Affinity of allosteric modulators 8.4.4 Negative allosteric modulators 8.4.5 Positive allosteric modulators 8.4.6 Quantifying PAM activity in vivo 8.4.7 NAM/PAM induced agonist bias 8.4.8 Optimal assays for allosteric function 8.5 Functional allosteric model with constitutive activity 8.6 Internal checks for adherence to the allosteric model 8.7 Methods for detecting allosterism 8.8 Chapter summary and conclusions 8.9 Derivations 8.9.1 Allosteric model of receptor activity 8.9.2 Effects of allosteric ligands on response: changing efficacy 8.9.3 Schild analysis for allosteric antagonists 8.9.4 Application of Log(Max/R50) values from R50 curves to quantify the effects of PAMs 8.9.5 Quantifying allosterically mediated induced bias in agonism 8.9.6 Functional allosteric model with constitutive receptor activity References 9. The optimal design of pharmacological experiments 9.1 Introduction 9.2 The optimal design of pharmacological experiments 9.2.1 Drug efficacy 9.2.2 Affinity 9.2.3 Orthosteric versus allosteric mechanisms 9.3 Null experiments and fitting data to models 9.4 Interpretation of experimental data 9.5 Predicting therapeutic activity in all systems 9.5.1 Predicting agonism 9.5.2 Predicting binding 9.5.3 Drug combinations in vivo 9.6 Summary and conclusions 9.7 Derivations 9.7.1 IC50 Correction Factors: competitive antagonists 9.7.2 Relationship of pA2 and pKB for Insurmountable Orthosteric antagonism 9.7.3 Relationship of pA2 and pKB for Insurmountable Allosteric Antagonism References 10. Pharmacokinetics 10.1 Introduction 10.2 Biopharmaceutics 10.3 The chemistry of “drug-like” character 10.4 Pharmacokinetics 10.4.1 Drug absorption 10.4.2 Route of drug administration 10.4.3 General pharmacokinetics 10.4.4 Metabolism 10.4.5 Clearance 10.4.6 Volume of distribution and half-life 10.4.7 Renal clearance 10.4.8 Bioavailability 10.5 Nonlinear pharmacokinetics 10.6 Multiple dosing 10.7 Modifying pharmacokinetics through medicinal chemistry 10.8 Practical pharmacokinetics 10.8.1 Allometric scaling 10.9 Placement of pharmacokinetic assays in discovery and development 10.10 The pharmacokinetics of biologics 10.10.1 Absorption 10.10.2 Duration of action 10.10.3 Antibody PK 10.10.4 mRNA PK 10.11 Summary and conclusions References 11. Safety pharmacology 11.1 Safety pharmacology 11.2 Hepatotoxicity 11.2.1 Drug–drug interactions 11.2.2 Direct hepatotoxicity 11.2.3 Hepatotoxicity in context in vivo 11.3 Cytotoxicity 11.4 Mutagenicity 11.5 hERG activity and Torsades de Pointes 11.6 Autonomic receptor profiling and off-target effects 11.7 General pharmacology 11.8 Clinical testing and drug toxicity 11.9 Summary and conclusions References 12. The drug-discovery process 12.1 Some challenges for modern drug discovery 12.2 The drug-discovery process 12.3 Target-based drug discovery 12.3.1 Target validation and the use of chemical tools 12.3.2 Recombinant systems 12.4 Systems-based drug discovery 12.5 High-throughput screening 12.5.1 Structure-based drug design and virtual screening 12.5.2 Phenotypic screening 12.6 The lead optimization process 12.7 Drug effectiveness 12.7.1 Clinical testing 12.7.2 Determining detailed profiles of candidate efficacy 12.7.3 Assays in context 12.7.4 Characterization of candidate efficacies 12.8 Summary and conclusions References Further reading 13. Selected pharmacological methods 13.1 Binding experiments 13.1.1 Saturation binding 13.1.2 Displacement binding 13.2 Functional assays 13.2.1 Determination of equiactive concentrations on Dose–Response curves 13.2.2 Method of Barlow, Scott, and Stephenson for measurement of the affinity of a partial agonist 13.2.3 Method of Furchgott for the measurement of the affinity of a full agonist 13.2.4 Schild analysis for the measurement of competitive antagonist affinity 13.2.5 Method of Stephenson for measurement of partial agonist affinity 13.2.6 Method of Gaddum for measurement of noncompetitive antagonist affinity 13.2.7 Method for estimating affinity of insurmountable antagonist (dextral displacement observed) 13.2.8 Resultant analysis for measurement of affinity of competitive antagonists with multiple properties 13.2.9 Measurement of the affinity and maximal allosteric constant for allosteric modulators producing surmountable effects 13.2.10 Method for estimating affinity of insurmountable antagonist (no dextral displacement observed): detection of allosteric effect 13.2.11 Measurement of pKB for competitive antagonists from a pIC50 13.2.12 Statistical assessment of selectivity 13.2.13 Measurement of surmountable allosteric antagonism 13.2.14 Measurement of insurmountable allosteric antagonism (second method) 13.2.15 Measurement of PAM activity Reference Statistics A.1 Structure of this appendix A.2 Introduction A.3 Descriptive statistics: comparing sample data A.3.1 Gaussian distribution A.3.2 Populations and samples A.3.3 Confidence intervals A.3.4 Paired data sets A.3.5 One-way analysis of variance A.3.6 Two-way analysis of variance A.3.7 Regression and correlation A.3.8 Detection of single versus multiple populations A.4 How consistent is experimental data with models? A.4.1 Comparison of data to models: choice of model A.4.2 Curve fitting: good practice A.4.3 Outliers and weighting data points A.4.4 Overextrapolation of data A.4.5 Hypothesis testing: examples with dose-response curves A.4.6 One curve or two? detection of differences in curves A.4.7 Asymmetrical dose-response curves A.4.8 Comparison of data to linear models A.4.9 Is a given regression linear? A.4.10 One or more regression lines? analysis of covariance A.5 Comparison of samples to ``standard values'' A.5.1 Comparison of means by two methods or in two systems A.5.2 Comparing assays/methods with a range of ligands A.6 Experimental design and quality control A.6.1 Detection of difference in samples A.6.2 Power analysis A2.7 Chapter summary and conclusions References Further reading Index A B C D E F G H I K L M N O P R S T U V W Z A Pharmacology Primer: Techniques for More Effective and Strategic Drug Discovery, Sixth Edition features the latest research surrounding the application of pharmacology in drug discovery in an effort to equip readers with a deeper understanding of complex and rapid changes in this field. Written by well-respected pharmacologist, Terry P. Kenakin, this primer is an indispensable resource for anyone involved in drug discovery. This edition has been reorganized for better flow and clarity and includes material on new technologies for screening (virtual, DNA encoded libraires, fragment-based) and a major section on phenotypic (target agnostic) screening for new leads and determination of drug targets. With full color illustrations as well as new examples throughout, this book remains a top reference for all industry and academic scientists and students directly involved in drug discovery or pharmacologic research. New material includes a discussion of the determination of target engagement, including numerous new ways to demonstrate the physical interaction of molecules with drug targets and new drug candidates such a mRNA, gene therapy, antibodies and information on CRISPR and genomics. Highlights changes surrounding the strategy of drug discovery, providing a comprehensive reference with advances in the methods involved in lead optimization and more effective drug discovery Includes multiple new sections on screening, phenotypic (target agnostic) screening for new leads, and determination of new drug targets Illustrates the application of rapid, inexpensive assays to predict activity in the therapeutic setting, showing data outcomes and the limitations inherent in interpreting this data Includes test questions and answers