Translational Medicine E-Book

• Herausgeber: Wiley-VCH Verlag GmbH & Co. KGaA
• Kategorie: Wissenschaft und neue Technologien
• Serie: Current Topics from the Encyclopedia of Molecular Cell Biology and Molecular Medicine
• Sprache: Englisch

Seitenzahl: 2385

Veröffentlichungsjahr: 2018

Beschreibung

This reference work gives a compete overview of the different stages of drug development using a translational approach. The book is structured in different parts, following the different stages in drug development.

Leseprobe

Table of Contents

Cover

Title Page

Copyright

Preface

Volume 1

Part I: Biopharmaceuticals

Chapter 1: Analogs and Antagonists of Male Sex Hormones

1 Introduction

2 Historical

3 Endogenous Male Sex Hormones

4 Synthetic Androgens

5 Anabolic Agents

6 Androgen Antagonists

7 Summary

Acknowledgments

References

Chapter 2: Annexins

1 Diversity and Functions

2 Structure and Mechanism of Action

3 Regulation

4 Applications

References

Chapter 3: Genetic Engineering of Antibody Molecules

1 Antibody Structure and Engineering

2 Technological Milestones in Antibody Engineering

3 Expression Systems

4 Variable Region Engineering

5 Constant Region Engineering

6 Structurally Modified Antibodies

7 Conclusions

Acknowledgments

References

Chapter 4: Growing Mini-Organs from Stem Cells

1 Introduction

2 Spatiotemporal Control of Mini-Organ Structure and Differentiation

3 Organoid Technology

4 Missing Cues in Current Organoid Technology

5 Organ Bud Technology

6 The Future of Mini-Organ Technologies

Acknowledgments

References

Chapter 5: Hemoglobin

1 General Aspects

2 Structural Features and Basic Terminology

3 Human Hemoglobin

4 Derivatives with Heme Ligands

5 The Reaction with Heme Ligands

6 Mechanisms of Cooperative Binding and Allostery

7 Assembly of Globin Monomers

8 Reactions with Nitric Oxide

9 Hemoglobin Variants

10 Evolutionary Considerations

References

Chapter 6: Immune Checkpoint Inhibitors

1 Introduction

2 CTLA-4 Blockade

3 Targeting the PD-1 PD-L1 Pathway

4 Others Checkpoint Inhibitors

5 Safety Aspects

6 Future Direction: Biomarkers and Combination

7 Conclusion

References

Chapter 7: Molecular Mediators: Cytokines

1 Cytokines: The Historical Record

2 A Universal Language of Cells

3 Receptors

4 Functions

5 Life without Cytokines (What Knock-Out Mice Tell Us)

6 Cytokine Synthesis

7 The Cytokine Network

8 Individual Heterogeneity

9 Cytokines and Infections

10 Cytokines and Diseases

11 Conclusions

References

Chapter 8: Neural Transplantation: Evidence from the Rodent Cerebellum

1 Introduction

2 The Murine Cerebellum: A Suitable Model to Study Neural Transplantation

3 Integration of Cerebellar Progenitors in the Adult Cerebellum: The Case of Purkinje Cells

4 Stem Cell Therapies for Cerebellar Disorders: Issues and Perspectives

5 Conclusions

References

Chapter 9: RNA Interference in Cancer Therapy

1 Introduction: Cancer and RNAi

2 RNA Interference: Breakthrough of the Year 2002

3 MicroRNAome: The Biological Toolkit for the Regulation of Gene Expression

4 Current Prospects for RNA Interference-Based Therapy for Cancer

5 Rational Design of an RNAi-Based Therapeutic Approach in Cancer

6 Summary

References

Chapter 10: RNA Interference to Treat Virus Infections

1 Introduction

2 RNA Interference: an Evolutionarily Conserved Genome Defense Mechanism

3 RNA Interference as a Mechanism of Antiviral Immunity

4 Therapeutic Applications of RNAi

5 Challenges for Clinical Applications

6 Conclusions

Acknowledgments

References

Chapter 11: Stem Cell Therapy for Alzheimer's Disease

1 Introduction

2 Stem Cell Therapy for Alzheimer's Disease

3 Conclusions

Glossary

References

Chapter 12: Immunotherapy with Autologous Cells

1 Introduction

2 Selecting and Isolating Effector Cell Types

3 Modifying the Effector Cell Population

4 Manufacturing Cells for Adoptive Transfer

5 Clinical Course of Adoptive Transfer

6 NextGen Cell Therapy

Disclosure Statement

References

Chapter 13: Targeted Therapy: Genomic Approaches

1 Principles of Genomics-Driven Targeted Therapy

2 Therapeutic Agents Used in Targeted Therapy

3 Targeted Therapy and Precision Medicine

4 Concluding Remarks

Acknowledgments

References

Volume 2

Part II: Drug Discovery Methods and Approaches

Chapter 14: Pharmaceutical Process Chemistry

1 Setting the Scene

2 Historical Perspective

3 What Oral Drugs Look Like

4 Early Development Activities

5 Late Development Activities

6 Reaction Process Safety

7 The Analytical Interface

8 Green Chemistry

9 To Market

10 Future Challenges

References

Chapter 15: High-Performance Liquid Chromatography of Peptides and Proteins

1 Introduction

2 Instrumentation

3 Fundamental Terms and Concepts

4 Physico-Chemical Properties of Peptides and Proteins

5 Chromatographic Separation Modes for Peptides and Proteins

6 Method Development from Analytical to Preparative Scale

7 Multidimensional HPLC

8 Final Remarks

Abbreviations

Symbols

References

Chapter 16: Hit-to-Lead Medicinal Chemistry

1 Introduction to the Hit-to-Lead Phase

2 Confidence in the Hit Matter

3 Goal of Hit-to-Lead Medicinal Chemistry

4 Strategies of Hit-to-Lead Medicinal Chemistry

5 Fragment-Based Lead Discovery

6 Conclusions

References

Chapter 17: Mass Spectrometry-Based Methods of Proteome Analysis

1 Principles and Instrumentation

2 Quantitative Methods of Proteome Analysis Using MS

3 Specific Examples of Applications

4 Conclusions

References

Chapter 18: Natural Product-Based Drug Discovery

1 Introduction

2 Drug Discovery Process

3 Established Drugs from Natural Sources

4 Drug Discovery from Natural Sources

5 Drugs to Prevent Skin Aging

6 Conclusions

Acknowledgments

References

Chapter 19: Neurological Biomarkers

1 Introduction

2 Fluid Biomarkers for Alzheimer's Disease

3 Fluid Biomarkers for Parkinson's Disease

4 Fluid Biomarkers for Traumatic Brain Injury (TBI)

5 Concluding Remarks

Acknowledgments

References

Chapter 20: Pharmacokinetics of Peptides and Proteins

1 Introduction

2 Administration Pathways

3 Administration Route and Immunogenicity

4 Distribution

5 Elimination

6 Interspecies Scaling

7 Drug–Drug Interaction

8 Conclusions

References

Chapter 21: Physical Pharmacy and Biopharmaceutics

1 Definitions

2 History of Physical Pharmacy and Biopharmaceutics

3 Application of Thermodynamics in Pharmacy

4 Oral Absorption Mechanism

5 Biopharmaceutics Classification System (BCS)

6 Biopharmaceutical Application in Drug Molecule Design

7 Biopharmaceutics Application in Drug Product Design

8 Conclusions

References

Chapter 22: Prions

1 Prions

2 Prions Are Distinct from Viruses

3 Disease Paradigms

4 Nomenclature

5 Discovery of the Prion Protein

6 PrP Gene Structure and Organization

7 Cellular form of PrP: Primary Structure, Expression, and Putative Function(s)

8 Structures of PrP Isoforms

9 Prion Replication

10 Cell Biology of PrP

Sc

Formation

11 Prion Peripheral Pathogenesis

12 Prion Toxicity

13 Strains of Prions

14 Interplay between the Species and Strains of Prions

15 Human Prion Diseases

16 Prion Diseases of Animals

17 Fungal Prions

18 Prevention and Therapeutics for Prion Diseases

19 Implications for Common Neurodegenerative Diseases

References

Chapter 23: RNA Metabolism and Drug Design

1 Introduction: RNA as a Drug Target

2 Antisense Oligonucleotides

3 RNA Interference

4 Small Molecules as RNA-Binding Drug Leads

5 Conclusions and Outlook

References

Chapter 24: Structure-Aided Drug Discovery and NMR-Based Screening

1 Introduction

2 Protein Tyrosine Kinases

3 Protein Tyrosine Phosphatases

4 Ras GTPases

5 Conclusions

Acknowledgments

References

Chapter 25: Tuberculosis Drug Development

1 Introduction

2 The Present

3 Anti-TB Drug Discovery

4 Drugs in Development

5 Conclusions

References

Part III: Nanomedicine

Chapter 26: Microfluidics in Nanomedicine

1 Introduction

2 Microfluidic Assembly of Nanomedicines

3 Microfluidic Characterization of Nanomedicines

4 Microfluidic Evaluation of Nanomedicines

5 Challenges and Opportunities

6 Concluding Remarks

Acknowledgments

References

Chapter 27: Nanoparticle Conjugates for Small Interfering RNA Delivery

1 The RNA Interference Pathway

2 Limitations of Unmodified siRNA Delivery and Carrier Design Considerations

3 siRNA Nanocarriers in Clinical Development

4 The Future of Nanoparticle-Based siRNA Delivery

Acknowledgments

References

Chapter 28: Quantum Dots for Biomedical Delivery Applications

1 Introduction

2 Properties of QDs

3 Lithographically Defined QDs

4 Colloidal QDs

5 QDs Application in Optics

6 Transport (Electrical) Properties of QDs

7 Application of QDs in Diagnostics

8 Nucleic Acid Detection

9 Application of QDs in Drug Treatments

Acknowledgments

References

Index

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Guide

Cover

Table of Contents

Preface

Begin Reading

List of Illustrations

Chapter 1: Analogs and Antagonists of Male Sex Hormones

Figure 1 Cellular events in steroidogenesis in the Leydig cell.

Figure 2 Enzymatic conversion of cholesterol to testosterone. Enzymes are denoted as: (

a

) side chain cleavage; (

b

) 3β-hydroxysteroid dehydrogenase; (

c

) 17α-hydroxylase; (

d

) 17,20-lyase; (

e

) 17β-hydroxysteroid dehydrogenase.

Figure 3 Enzymatic conversion of testosterone to biologically active metabolites, 5α-dihydrotestosterone and estradiol.

Figure 4 Reductive metabolites of testosterone.

Figure 5 Aromatization of androgens.

Figure 6 Mechanism of action of 5α-dihydrotestosterone (DHT). T = testosterone; A = androstenedione; DHEA = dehydroepiandrosterone; AR = androgen receptor; HSPs = heat shock proteins; Co-R = coregulators/coactivators; HRE = hormone response element; 3β-HSD = 3β-hydroxysteroid dehydrogenase; and 17β-HSD = 17β-hydroxysteroid dehydrogenase.

Figure 7 Schematic diagram of the androgen receptor.

Figure 8 Summary of structure–activity relationships for androgens.

Figure 9 Summary of structure–activity relationships for anabolic agents.

Figure 10 Summary of structure–activity relationships for 5α-reductase inhibitors.

Chapter 2: Annexins

Figure 1 Schematic illustration of the primary structures of six annexins. Each of the four (or eight) homologous domains contains the 17-amino acid “endonexin fold” sequence represented by a sawtooth line (sequence: KGhGTDExxLIpILApR: h, hydrophobic residue; p, polar residue; x, variable residue) [10]. The unique N-terminal structures are on the left (or right in the case of annexin A6); Y and S represent phosphorylation sites in the tails of annexins A1 and A2. The annexin A2 tetramer is drawn showing the association of the N termini of the heavy chains with the light chain (p10 or S100A10) dimer. The Ys inside the loops in the tail of annexin A7 represent a pro-beta helix [11].

Figure 2 Schematic representation of various membrane-trafficking steps, showing the involvement of annexins. (a) In the biosynthetic pathway, annexin A2 in complex with S100A10 has been shown to participate in the Ca

2+

-evoked exocytosis of chromaffin granules and endothelial Weibel–Palade bodies. The complex probably functions at the level of the plasma membrane, possibly by linking the large secretory vesicles to the plasma membrane or by organizing plasma-membrane domains so that efficient fusion can take place. Annexin A13b is required for the budding of sphingolipid- and cholesterol-rich membrane domains at the

trans

-Golgi network, and therefore the delivery of such material to the apical plasma membrane in polarized epithelial cells; (b) In the endocytic pathway, annexin A6 has been proposed to be involved in clathrin-coated-pit budding events that depend on the activity of a cysteine protease that is required to modulate the spectrin membrane skeleton. Annexin A2, which can associate with caveolae, has been shown to form a lipid–protein complex with acylated caveolin and cholesteryl esters that seems to be involved in the internalization/transport of cholesteryl esters from caveolae to internal membranes. Annexin A2 is also found on early endosomes, where it is required, in complex with S100A10, to maintain the correct morphology of perinuclear recycling endosomes. Moreover, its depletion can interfere with the proper biogenesis of multivesicular endosomes from early endosomes. Annexin A1 also seems to function in multivesicular endosome biogenesis, more specifically, in the process of inward vesicle budding.

Figure 3 The structure of annexin A5 as determined by X-ray diffraction (Molecular Modeling Database ID: 55379; Protein Data Bank ID: 1AVR) [12]. (a) “Side” view of the molecule, with the calcium-binding sites, and the membrane-binding face at the top. Calcium ions are represented by the spheres. The-high affinity sites are represented by the first, second, and fifth spheres from left to right; the third and fourth spheres indicate low-affinity ion-binding sites that were identified by lanthanide binding. The extended N terminus is at the bottom; (b) View of the “cytoplasmic” side of the molecule and the N terminus. The calcium-binding sites are on the opposite face. Note the open architecture and potential ion channel in the center of the molecule.

Chapter 3: Genetic Engineering of Antibody Molecules

Figure 1 IgG structure. (a) The general structure of the immunoglobulin G (IgG) molecule (the most abundant antibody in blood) and the active fragments that can be derived from it. The antibody protein is made of two light chains and two heavy chains with discrete domains: two domains constitute the light chain (V

L

and C

L

), while four domains make up the heavy chain (V

H

, C

H

1, C

H

2, and C

H

3). The variable regions are designated as the Fv region and include the complementarity-determining regions (CDRs) that are the critical amino acid residues for the affinity and specificity of the antibody-binding sites. The effector functions of the antibody are properties of the Fc fragment. The carbohydrate units (black circles) present at N297 within the C

H

2 domains contribute to the functional properties of the antibody. The hinge region provides flexibility to the antibody molecule, facilitating antigen binding, and effector functions. The enzyme papain cleaves the antibody into two Fab fragments containing the antigen-binding sites, and an Fc fragment responsible for the effector functions; (b) Genes that encode the heavy and light chains. In the genes, each domain is encoded by a discrete exon (indicated by boxes) separated by intervening sequences (introns) indicated by the line. Both, heavy and light chains contain hydrophobic leader sequences (L) necessary for their secretion, a variable domain that contains three CDR sequences, which provides variability in recognition sites between the antibodies, and a joining segment (J). In the heavy chains there is also a diversity segment (D).

Figure 2 The comparative structure of the human antibody classes. IgD (184 kDa), IgE (189 kDa), IgG (146 kDa for IgG1, 2, and 4, and 165 kDa for IgG3), IgA (dimer 300–360 kDa), and IgM (pentamer 970 kDa). Antibodies can be monomeric (IgG, IgE, and IgD) or polymeric (IgA: dimeric and IgM: pentameric), where the polymeric antibodies contain a joining (J) chain.

Figure 3 Potential modes of action of antibodies. Antibodies can elicit their protective activity by blocking the interaction of soluble factors (ligands) to surface receptors by either targeting the free soluble factor or the receptor on the target cells, which may be a cancer cell. Targeting antigens on the surface of the cells may alter signaling and induce an antiproliferative and/or proapoptotic activity that can be favored by crosslinking. In addition, antibodies such as IgG1 can activate immune effector functions such as ADCC, ADCP, and CDC.

Figure 4 Schematic representation of a murine monoclonal antibody, a mouse/human chimeric antibody, a “CDR-grafted” or humanized antibody, and a fully human monoclonal antibody. Chimeric antibodies have variable regions and binding specificities derived from a murine monoclonal antibody and human constant regions with their corresponding effector functions. Humanized antibodies are composed mostly of human sequences, except for the areas in contact with the antigen (CDRs), which are derived from mouse sequences.

Figure 5 Hybridoma production for the generation of mouse monoclonal antibodies. Mice immunized with an antigen of interest elicit an adaptive humoral immune response against the antigen. Splenic B cells from the immunized mice are harvested and fused with murine myeloma cells. The resulting antibody-secreting cells are screened to identify fused cells (hybridomas) specific for the antigen of choice. Single clones secreting the antibody with the desired properties are isolated using selection media that kill the unfused myeloma cells, while the unfused B cells die because they have a short lifespan. The new hybridomas are later subcloned to obtain a homogeneous cell line.

Figure 6 Recombinant technology for the generation of chimeric monoclonal antibodies from murine hybridomas. mRNA obtained from a mouse hybridoma cell line is reverse-transcribed and variable regions amplified (RT-PCR) using a set of primers flanking the V

L

and V

H

regions. The PCR products are cloned into intermediate cloning vectors, digested with restriction enzymes flanking the variable regions, and ligated into expression vectors containing human light and heavy constant region sequences. Here, the yellow rectangles are selectable markers for bacteria (amp – ampicillin) and the beige rectangles are selectable markers for eukaryotic cells (neo – neomycin/his – histidinol). The green segments are the eukaryotic expression promoters, the red arrows are the coding sequences for constant region κ and γ1, the violet arrow is the variable light (V

L

), and the blue arrow is variable heavy (V

H

). These vectors are transfected into mammalian cells, which are then screened for antibody production.

Figure 7 Generation of fully human monoclonal antibodies using recombinant DNA technology and phage display libraries. The sequences encoding the V

L

and V

H

are amplified from the mRNA of peripheral blood mononuclear cell-derived donor B cells using RT-PCR and used to construct a scFv library. The genetic sequence encoding each scFv is cloned into a phage display vector for expression on the surface of the bacteriophage. Bacteriophage from the resulting library of scFv clones are selected for their ability to bind antigen. Multiple rounds of binding, elution, and amplification result in a library that is highly enriched for phage displaying scFvs that recognize the target of interest. The scFvs from these phage are isolated and cloned into antibody expression vectors and transfected into myeloma or other cells appropriate for expression.

Figure 8 Generation of fully human monoclonal antibodies using the

XenoMouse

™ technology. Mouse embryonic stem (ES) cells are produced in which either the endogenous heavy or light chain locus has been disrupted by homologous recombination or in which yeast artificial chromosomes (YACs) encoding for the human IgH and Igκ loci have been introduced. These modified ES cells can give rise to either immune-compromised mice that are incapable of producing endogenous antibodies, or transgenic mice that can make both human and mouse immunoglobulins. Breeding the two mouse strains and backcrossing their progeny can generate a

XenoMouse

™ that produces only fully human antibodies. This mouse can be immunized with an antigen and generate fully human monoclonal antibodies using the hybridoma technology.

Figure 9 Schematic representation of various genetically engineered antibody fragments. The relative size and domain relationships between engineered Fab, single-chain Fv (scFv), single-chain Fab, scFv-Fc, scFv-C

H

3 or minibody, scFv dimer or diabody, and hcAbs fragments are shown.

Figure 10 Schematic representation of the structure of two different polymeric IgGs. IgM-like IgG molecules form a covalent assembly of several IgG monomers due to the presence of a cysteine residue in the μ tailpiece (μTp) of human IgM that is added to the carboxy-terminus of the heavy chain of human IgG through genetic engineering. A polymeric antibody can also be generated when a non-antibody partner such as avidin is fused to the carboxy-terminus of the C

H

3 domain of an IgG, as in the case of the dimeric anti-TfR IgG3-Av. Since avidin exists naturally as a non-covalent tetramer, the IgG–avidin fusion protein has a dimeric structure. The molecule shown schematically is IgG3 with its long extended hinge region.

Figure 11 Schematic representation of recombinant fusion proteins. Non-antibody proteins such as cytokines, ligands, or toxins can be fused to different fragments of the antibody to generate an antibody fusion protein. (a) A non-antibody protein (blue circle) can be genetically fused to the carboxy- (A1) or amino-terminus (A2) of the full-length antibody or to different antibody fragments (A3–A11) to generate an antibody–fusion protein; (b) Two different non-antibody proteins (blue and purple circles) can be fused in a single (B1–B2 and B4–B5) or in tandem format (B3) at the ends of the same antibody or antibody fragment. The domain structure of the antibodies facilities their use to develop bifunctional antibody fusion proteins that can consist of non-antibody protein (fused to the amino-terminus of the heavy (B1) or light chain (B2)) and the second non-antibody protein (fused to the carboxy-terminus of the heavy chain). The heterominibody (DCH) (B5), consists of one protein fused to the C

H

1 domain, the second different protein fused to the C

L

domain linked both to two scFvs by the IgG3 hinge region; (c) C1–C3 represent three fusion proteins that lack antibody variable regions with the non-antibody protein fused to the amino-terminus of the C

H

1 domain (C1), immediately before the hinge (C2), or fused to the carboxy-terminus to the C

H

3 domain (C3).

Chapter 4: Growing Mini-Organs from Stem Cells

Figure 1 Paradigm shift in stem cell differentiation. Studies of induction of stem cell differentiation have begun to aim at generating 2D cell or engineered tissue. Recently, the target has dynamically shifted to generating complex 3D mini-organs by recapitulating organogenesis, such as organoids and organ buds.

Figure 2 Principles of self-organization phenomena. For simplicity, the principles of self-organization can be divided into three major phenomena.

Assembly

is an intrinsic cell-sorting process in a time course manner.

Patterning

is a region-specific cell fate specification in a tissue so as to evolve a heterogeneous cell population.

Morphogenesis

is a spatiotemporal control of tissue mechanics accompanied by dynamic morphological change.

Figure 3 Recapitulating a key organogenetic event in culture

.

Pioneering studies have implied that intercellular communication plays an important role in directing liver bud delamination from a primitive gut. In the mouse, liver organogenesis is initiated at embryonic day 8.5 via hepatic specification, which is driven by an interaction between the ventral portion of the foregut endoderm and the constituents of the adjacent immature endothelial cells and the surrounding septum transversum mesenchyme. Interestingly,

in vivo

liver budding process progresses prior to blood perfusion.

Figure 4 Organ bud self-organization via mesenchymal cell-driven condensation

.

This liver bud self-organization was recently achieved by recapitulating the liver budding process as follows: human iPSC-derived hepatic endoderm cells were mixed with human endothelial and mesenchymal progenitor cells on a soft substrate

in vitro

; the mixed cells self-condensed to form a 3D mass, approximately 4–5 mm in diameter. Additional culture of these condensed masses eventually self-organized into a tissue that had an inner-branched endothelial structure, showing features specific to early liver bud in terms of structures and gene-expression properties. A self-condensation approach could be adapted to self-organize kidney bud, pancreatic bud, and mesenchymal condensation.

Figure 5 Future application of stem cell-derived mini-organs. Future technological improvements in culturing and differentiating miniature organs will revolutionize the current paradigm of drug discovery and development in the pharmaceutical industry, facilitate the present understanding of human developmental biology and disease modeling, and hopefully offer novel therapies against end-stage organ failure.

Chapter 5: Hemoglobin

Figure 1 Overview of ferric Hb, which is similar to the oxygenated derivative (HbO

2

), in two orientations rotated by 90° over the Y-axis. Only the

α

-carbons of the polypeptide chain are shown. Residues whose side chains are involved in contacts between subunits are circled and given boldface numbers. There are two types of unlike subunit contacts:

α

1

β

1

(or

α

2

β

2

) and

α

1

β

2

(or

α

2

β

1

), the first interface being more extensive than the second (see also Table 2). The

α

1

β

1

contact involves the B, C, and H helices and the GH corner, whereas the

α

1

β

2

contact concerns mainly helices C and G and the FG corner.

Figure 2 Schematic representation of the heme pocket, with the

distal

side positioned above and the

proximal

side below the heme. Phenylalanine CD1 and the proximal histidine F8 are the only totally invariant residues present in all hemoglobins. In vertebrates, valine E11 and the distal histidine E7 are involved in the reversible O

2

binding to the heme Fe(II). Note the hydrogen bond between the N

ε

of the distal HisE7 and the bound O

2

. Neutron diffraction, NMR, and computational chemistry have shown that, in MbO

2

, HisE7 is protonated only on N

ε

, whereas in the CO derivative protonation also occurs on N

δ

, which faces the bulk water, thereby favoring a more perpendicular geometry by releasing part of the steric hindrance [5–7].

Figure 3 Relative amounts of globin subunits (top) and Hb tetramers (bottom) at different stages in the development of the human embryo, fetus, and infant. The pattern of globin gene expression is controlled by a regulatory element, called locus control region (LCR). In the absence of an interaction with LCR, individual globin genes are either inactive or very poorly expressed [8].

Figure 4 The exon–intron structure of a globin gene encoding a typical polypeptide chain of mammalian Hb or Mb. From the gene, a primary transcript or pre-mRNA is synthesized (step 1); the intervening sequences or introns are then excised (step 2) by splicing to yield the mature mRNA; this is translated (step 3) into the polypeptide chain, which spontaneously adopts the typical globin fold. Three globin “modules” corresponding to the three exonic transcripts are schematically illustrated in green, light cyan, and gray, respectively. The central exon (the biggest) binds the heme in a native configuration.

Figure 5 Optical absorption spectra of deoxy (dashed line), oxy (solid line), and CO (dot-dashed line) hemoglobin in the visible and near-ultraviolet (the so-called Soret band) regions at pH 7.4: ε

mM

, millimolar extinction coefficient in heme (i.e., referred to an equivalent molecular mass of 16 250 g mol

−1

).

Figure 6 O

2

equilibrium curves Mb and Hb: % saturation with O

2

, reported as a function of O

2

partial pressure [1]. The saturation curve for Mb is hyperbolic (left), while the typical shape of the O

2

equilibrium curve for Hb is sigmoid (a to e). The curves from a to e represent the O

2

-binding isotherms at various pH values (reflecting the Bohr effect): from left to right, pH 7.6, 7.4, 7.2, 7.0, and 6.8.

Figure 7 Hill plot of the O

2

binding curve of Hb, as log[

Y

/(1 −

Y

)] versus log

p

O

2

. The intercept of the upper asymptote with the

x

-axis, when the ordinate is 0, allows the calculation of

K

R

, the O

2

equilibrium constant of the high-affinity state; likewise, the intercept of the lower asymptote with the

x

-axis allows the calculation of

K

T

, the O

2

equilibrium constant of the low-affinity state (see allostery). The slope in the central part of the curve yields the maximum Hill coefficient, and its intercept with the

x

-axis at

Y

= 0.5 yields the overall O

2

affinity. The Hill equation accounts for the data between approx.

Y

= 0.1 and

Y

= 0.9, and helps to describe the behavior of vertebrate Hbs in terms of cooperativity (

n

) and affinity (

p

1/2

).

Figure 8 General representation of ligand (X) binding and ligand-linked conformational changes, illustrating the alternative ways of generating cooperativity according to the sequential KNF model [25] (indicated by the diagonal in boldface) and the concerted MWC model [23] (represented by the equilibria between the two extreme columns, all intermediates being absent or negligible or undetectable). Each subunit within the tetramer can have only two distinct tertiary conformations, one (circle) with high affinity for heme ligands or R state; and the other (square) with low affinity or T state. In the sequential model, heme–ligand binding induces an isomerization in each ligated subunit, which assumes the high-affinity conformation; the unligated subunits retain their low-affinity structure, even though the contacts with the ligated neighbor(s) are altered, thereby increasing their tendency to switch to the high-affinity state. An important property of the sequential model is that the extent of binding and structural changes at different ligand saturations must be identical. In the concerted model, the tetramer is postulated to exist in only two quaternary states (R and T) in which all four protomers are in either one of two conformations (squares or circles). The quaternary states are in equilibrium with each other at every degree of saturation: the fully ligated tetramer is predominantly in the R state, whereas the T state is favored in the fully unligated species. The conformational transition of the subunits (between square and circle) is concerted, involving all protomers within the tetramer, with the result that the molecule conserves structural symmetry. This situation corresponds to an extreme case of cooperativity among the protomers, characterized by a virtual absence of the hybrid states (i.e., coexistence of circles and squares in one tetramer), which, on the contrary, are present in the sequential model. The sequential model can account for both positive and negative cooperativity, whereas the concerted model can accommodate only for positive cooperativity.

Figure 9 Schematic diagram illustrating the ligand-linked changes in quaternary structure of Hb (top) and the distances (in nm) between heme groups (bottom). Both structures have a dyad axis (

Y

) relating the

α

1

β

1

dimer to the

α

2

β

2

dimer, and in both cases the molecular contacts between

α

1

and

β

1

(as well as those between

α

2

and

β

2

) change very little; accordingly, the positions of ligated and unligated

α

1

β

1

dimers have been superimposed. In going from deoxy to oxy Hb, the main differences in conformation are: (i) a rotation of 15° (

θ

) about a pivot (

P

) of the

α

2

β

2

dimer relative to the

α

1

β

1

dimer so that the two

β

chains are about 0.6 nm further apart in the former than in the latter; and (ii) a shift of the

α

2

β

2

dimer along the

P

axis by about 7.5° into the page. Major conformational changes in the T-to-R transition involve the

α

1

β

2

(and

α

2

β

1

) subunit interfaces. As a result of the quaternary switch, the distances between the heme groups change, bringing into closer contact the two

β

subunits, and further apart the two inter-dimer interfaces. This concerted movement is such that the tetramer is ready to catch the message whenever a ligand binds/unbinds from the subunits.

Figure 10 The reactions of myoglobin with O

2

and NO. The primary physiological function involves the reversible binding of O

2

to deoxy-myoglobin (Mb) to yield oxy-myoglobin (MbO

2

), which facilitates the transport of O

2

from the periphery of the cell to the mitochondria for use in respiration. MbO

2

reacts rapidly (and irreversibly) with nitric oxide (NO) to yield nitrate and ferric myoglobin (met Mb), thereby quenching free NO that might otherwise inhibit cytochrome

c

oxidase. Met Mb is reduced to Mb by met Mb reductase (

e

−

arrow). Moreover, Mb binds rapidly and reversibly with NO, yielding nitrosyl-myoglobin (MbNO). This pathway might be of greater significance in cellular compartments with low O

2

concentrations, for example, in the immediate environment of mitochondria. In the presence of O

2

, MbNO can be converted back to met Mb at a rate limited by the thermal dissociation of NO, again yielding nitrate [36].

Figure 11 The O

2

content of blood and some O

2

carriers as a function of O

2

partial pressure under physiological conditions (pH 7.4, 37 °C).

A

, native Hb stripped from BPG;

B

, whole blood;

C

, pyridoxylated, glutaraldehyde-polymerized Hb;

E

, plasma. Area

D

comprises the range of commonly employed perfluorocarbons (compounds forming fine and stable emulsions with water). The vertical lines indicate venous (40 Torr) and arterial (105 Torr) O

2

pressures. It should be noted that the release of O

2

by a solution of stripped, native Hb is very small, whereas for polymerized pyridoxylated Hb it is approximately half that of blood.

Figure 12 Possible evolution of vertebrate globin genes, as deduced from DNA and amino acid sequence differences. The arrangement of the globin genes and pseudogenes (denoted by the prefix

ψ

) in humans is shown at the top, together with the indication of the chromosome where the gene is located. Estimated times of divergence in millions of years are only approximate. The high similarity between two

α

-genes (

α

1

and

α

2

) and between genes G

γ

and A

γ

indicates that their duplication must have occurred quite recently in evolutionary time. The G

γ

and A

γ

genes produce chains with glycine or alanine, respectively, at position H14(136) (see also Table 1) [2, 3, 9, 18, 40, 47, 48].

Chapter 6: Immune Checkpoint Inhibitors

Figure 1 Immune checkpoints regulate the evolution of immune response. (a) Stimulation of the TCR by MHC/peptide on dendritic cell (DC) complexes delivers signal 1, while interactions between costimulatory ligands on the antigen-presenting cell (APC) and CD28 on the T cell provide signal 2; (b) Activation signal is initiated by binding of B7 molecules on the APC (DC) to cluster of differentiation 28 (CD28) receptors on the T cell. Cytotoxic T-lymphocyte antigen 4 (CTLA-4), expressed on the T cell, binds B7 molecules, resulting in T-cell inactivation.

Figure 2 Targets of antibody immune modulators. (a) The interaction of T-cell receptor (TCR) with a major histocompatibility complex (MHC) molecule expressed by antigen-presenting cells (DC). The interaction of the CD28 receptor on T cell with B7 costimulatory molecules (B7-1 and B7-2) on the DC is necessary to complete T-cell activation. This phase occurs primarily within the lymph nodes. To prevent inappropriate T-cell activation, negative regulators of T-cell immunity, including CTLA-4 and PD-1, are required. CTLA-4 competes with CD28 for the interaction with B7, and it is upregulated after T-cell activation; (b) In the peripheral tissues other negative regulators participate in T-cell inactivation. Moreover, two general mechanisms of expression of immune-checkpoint ligands on tumor cells are identified. (i) Innate immune resistance: Constitutive oncogenic signaling can upregulate PDL1 expression on all tumor cells, independently of inflammatory signals in the tumor microenvironment; (ii) Adaptive immune resistance: PDL1 is induced in response to inflammatory signals that are produced by an active antitumor immune response. For example, the secretion of interferon-γ by activated T cells increases the expression of PDL1 on tumor cells.

Figure 3 Multiple costimulatory and coinhibitory ligand–receptor interaction between T cell and dendritic cell (DC), tumor cell, and tissue macrophage in the tumor microenvironment. CTLA-4: cytotoxic T-lymphocyte-associated antigen 4; GAL9, galectin 9; HVEM, herpesvirus entry mediator; ICOS, inducible T cell costimulator; IL, interleukin; LAG3, lymphocyte activation gene 3; PD1, programmed cell death protein 1; PDL, PD1 ligand; TCR, T-cell receptor; TIM3, T-cell membrane protein 3.

Figure 4 Cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) pathways. CTLA-4 recruits the phosphatases SHP2 and PP2A via the YVKM motif in its cytoplasmic domain. SHP2 recruitment results in an attenuation of TCR signaling by dephosphorylating the CD3ζ chain. PP2A recruitment results in downstream dephosphorylation of AKT, further dampening the T-cell activation pathway.

Figure 5 Program death 1 (PD1) pathways. PD-1 contains in the cytoplasmic domain both an immune-receptor tyrosine-based inhibitory motif (ITIM) and an immune-receptor tyrosine-based switch motif (ITSM). The negative signal of PD-1 is based on the recruitment of SH2-domain containing tyrosine phosphatase (SHP2) through ITSM. SHP2 inhibits phosphatidylinositide 3-kinase (PI3K) phosphorylation, a ZAP 70 pathway that results in T-cell exhaustion. IL-2 signaling via the interleukin-2 receptor (R-IL2) induces signal transducer and activator of transcription-5 phosphorylation (pSTAT-5). Dimerization and nuclear translocation of phosphorylated STAT-5 leads to PD-1 upregulation.

Figure 6 TIM-3 pathways and immune cells implication. TIM-3 is expressed on CD8 T cell exhausted. TIM-3+ T regulator cells are potent suppressors of immune responses in tumor tissue, and may promote the development of dysfunctional phenotype in intratumoral CD8 T cells. Tumor-associated dendritic cells (TADCs) express TIM-3 and lead to a decrease in free HMGB1 available to bind the nucleic acids released by dying tumor cells. TIM-3 expression also promotes the recruitment of myeloid-derived suppressor cells (MDSCs). IFNγ, interferon-gamma; IL-2, interleukin-2; IL-10, interleukin-10; Gal9, Galectin 9.

Figure 7 Check-point inhibitor antibodies and combination currently under development.

Chapter 7: Molecular Mediators: Cytokines

Figure 1 Mode of action of cytokines.

Figure 2 Families of cytokine receptors.

Figure 3 Cytokine receptors share common chains.

Figure 4 Example of signaling cascade initiated by TNF and IL-1, the later sharing some common pathways with endotoxin. LPS: lipopolysaccharide.

Figure 5 Different properties of soluble receptors.

Figure 6 Cytokines and soluble mediators as coordinators of regulated processes taking place in a bacteria-loaded site.

Figure 7 T-cell subpopulations, the nature of environmental cytokines required for their differentiation, the nature of the produced cytokines and their respective role in immunity and inflammation.

Figure 8 Inflammation is under the control of pro-inflammatory cytokines, whereas its resolution involves anti-inflammatory cytokines and other signals that turn off the production of pro-inflammatory cytokines.

Figure 9 Inflammation is the consequence of a cascade of events initiated by IL-1 and/or TNF. The action of these cytokines on various target cells leads to the release of numerous inflammatory mediators. Anti-inflammatory cytokines, the activation of the neuroendocrine pathway and the effects of glucocorticoids as well as the enhanced production of acute phase proteins exert a negative control on the inflammatory process. ACTH: adrenocorticotropic hormone; CNS: central nervous system; PACAP: pituitary adenylate cyclase-activating polypeptide; PAF: platelet-activating factor; VIP: vasoactive intestinal peptide.

Figure 10 The cytokine network (for details, see the text).

Figure 11 Individual heterogeneity for cytokine production and responsiveness.

Chapter 8: Neural Transplantation: Evidence from the Rodent Cerebellum

Figure 1 Adult cerebellar cytoarchitecture. Wiring diagram for a cerebellar corticonuclear microcircuit. Abbreviations: BC, basket cell; CF, climbing fiber; DCN, deep cerebellar nuclei; GL, granule cell layer; GR, granule cell; GO, Golgi cell; IO, inferior olive; INT, interneuron; LC, Lugaro cell; MF, mossy fiber; ML, molecular layer; N-O, nucleo-olivary inhibitory projection; PC, Purkinje cell; PCL, Purkinje cell layer; PCN, precerebellar neuron; PF, parallel fiber; PJ, projection neuron; SC, stellate cell; UB, unipolar brush cell; WM, white matter.

Figure 2 Circuit rewiring after graft in the adult damaged cerebellum. (a) The cartoon shows a simplified scheme of the cerebellar cortical circuitry and corticonuclear projection. (b) In the case of selective Purkinje cell degeneration, the cortical afferents are deprived of their targets and the corticonuclear connection is interrupted. (c) Efficient cell replacement strategies should replace lost Purkinje cells through new neurons (gray) able to rewire damaged connections. (d) When cerebellar grafts are placed in the host cortex, Purkinje cells eventually settle in the recipient ML, restoring a normal relationship with their afferents, but failing to send their axons to the deep cerebellar nuclei. (e) In the case of intraparenchymally positioned transplants, many Purkinje cells remain within the graft, establishing nuclear innervation but failing to restore normal connectivity with host cortical targets. Abbreviations: ML, molecular layer; GL, granular layer, DCN, deep cerebellar nuclei; PCL, Purkinje cell layer; WM, white matter.

Chapter 9: RNA Interference in Cancer Therapy

Figure 1 The miRNA and siRNA pathways of RNAi. Primary miRNAs (pri-miRNAs) are transcribed in the nucleus by RNA Polymerase II as long, capped, and polyadenylated (A-(n)) precursors, and are trimmed by the microprocessor complex (including Drosha and DCGR8) into 70- to 100-nucleotide hairpin precursors, usually containing interspersed mismatches along the duplex, called pre-miRNAs. Pre-miRNAs associate with the Exportin/RanGTP complex and are translocated to the cytoplasm (left side of figure), where they are further processed into a 19- to 25-nucleotide duplex (miRNA:miRNA*) by the Dicer–TRBP complex. Finally, the duplex interacts with an Argonaute (AGO2) protein into the RISC (RNA-induced silencing complex) apparatus: one strand of the duplex (the passenger * strand) is removed, whereas the guide strand, the mature miRNA, remains stably associated within the RISC, and directs the complex to the target mRNA for the post-transcriptional gene silencing. The interactions between miRNA

seed

sequence and the 3′-UTR of the mRNA generally culminate in translation repression. However, cleavage and degradation of the mRNA have also been documented. Long, perfectly base-paired, dsRNA (right side of figure) are also processed by the Dicer–TRBP complex into small siRNAs. Once they enter the RISC complex, an Argonaute protein cleaves the passenger strand, and the guide strand is used to bind the complementary mRNA target. SiRNAs usually anneals to the mRNAs by a perfect complementarity, mainly leading to their degradation.

Figure 2 MicroRNAs as targeted therapeutics. When aiming to repress oncogenic proteins, the expression levels of tumor suppressor microRNAs can be restored by using different strategies including siRNAs, shRNAs (short hairpin RNAs), bi-shRNAs (bifunctional siRNA), targeting by perfect base-complementarity oncogenic mRNAs, or miRNA mimics, synthetic analogs of endogenous miRNAs.

Figure 3 MicroRNAs as therapeutic targets. Aberrantly overexpressed microRNAs (oncomiRs) can conversely be inhibited by using: antimiRs (ASO, antisense oligonucleotides; LNAs, locked nucleic acids), designed to be complementary to the endogenous miRNAs; miRNA sponges, which contain multiple binding sites for microRNAs and prevent their loading onto the RISC complex; miRNA masks, small antisense oligonucleotides, which bind the target mRNA at the 3′-UTR miRNA-target sites, avoiding the interaction between mRNA and endogenous miRNAs, and transcriptional repression.

Figure 4 Rationale design and challenges of RNAi therapeutics for human cancers. Schematic showing the critical issues to be taken into account when designing an RNAi-based strategy for cancer treatment: selection of the targets according to the tumor characteristics and patients' information from the clinic; the biological barriers affecting biostability and safety profile of RNAi therapeutics; and an efficient drug delivery culminating in the correct cellular uptake by tumor cells.

Chapter 10: RNA Interference to Treat Virus Infections

Figure 1 Timeline of the milestones for the major advances in the RNAi field.

Figure 2 (a) Domain architecture of a typical Dicer protein and the crystal/cryoelectron microscopy structures of the human Dicer protein. Adapted from Ref. [23]; (b) Domain architecture of a typical Argonaute protein and the crystal structure of

P. furiosus

Argonaute. Adapted from Ref. [24].

Figure 3 The canonical microRNA pathway. The pathway is initiated by the Pol II transcription of an RNA molecule that folds back to form a hairpin-like structure. This molecule is processed by nuclear proteins (Drosha and DGCR8), and then exported to the cytoplasm by Exp-5. In the cytoplasm, the small RNA is further processed by Dicer and associated dsRNA binding proteins (e.g., TRBP) and loaded onto the RISC complex. The mature miRISC will target complementary RNA and cause either endonucleolytic cleavage (perfect complementarity) or translational arrest (presence of bulges).

Figure 4 Antiviral innate immunity pathways in plants, invertebrates, and vertebrates. In plants and invertebrates (left panel), long double-stranded viral replication intermediates are recognized by Dicer proteins (e.g., Dcr-2). Dicer processes these viral long dsRNA onto siRNAs. In plants and worms, host-encoded RNA-dependent RNA polymerases (RdRPs) produce secondary siRNAs, to amplify and spread the response. RISC complexes loaded with virus-derived siRNAs then target the viral RNAs. In vertebrates (right panel), viral double-stranded RNA or specific features of single-stranded RNAs (e.g., uncapped triphosphate extremities) are recognized by RIG-I-like helicases in the cytoplasm, or by TLR-3, -7, or -8 in the endosomes. Activation of these receptors triggers signaling and leads to the transcription of interferon and proinflammatory genes.

Figure 5 Strategies for the delivery of shRNA or siRNA in mammalian cells. Adenoviral or lentiviral vectors are used to deliver DNA molecules encoding precursors of shRNAs. Upon transcription in the nucleus, these RNAs will be processed and exported to the cytoplasm, like endogenous miRNAs. In the case of siRNAs, different strategies to deliver them to the RISC complex in the cytosol are illustrated. See text for details. SNALP: stable nucleic-acid lipid particle.

Chapter 11: Stem Cell Therapy for Alzheimer's Disease

Figure 1 Aβ and Tau in Alzheimer's disease (AD). (a) Aβ and tau comprise the hallmark neuropathological alternations associated with AD. Transgenic mouse models such as the 3xTg-AD model, which contains three distinct human mutated genes that allow for the age-dependent development of both Aβ and tau pathology, have been valuable tools in deciphering the role that Aβ and tau play in the development and progression of AD; (b) Cumulative studies using human samples and transgenic models, such as the 3xTg-AD model, have found that mutations which lead to early AD onset result in changes in Aβ levels, particularly Aβ

1–42

. The elevated Aβ levels result in Aβ aggregation that can also lead to a series of downstream events that result in the initiation of tau hyperphosphorylation, neuronal injury, and the death of susceptible neurons. These findings comprise the working theory of AD progression known as the

amyloid cascade hypothesis.

Figure 2 Potential mechanisms for stem cell-based therapy in the Alzheimer's disease brain. Stem cell-based therapy could be used to promote endogenous neurogenesis in either the subventricular zone (red) or the subgranular zone of the hippocampus (yellow) by administering small molecules that can cross the blood–brain barrier. In addition, cell replacement strategies, utilizing exogenous stem cells sources could be targeted to regions of the brain susceptible to extensive neuronal loss such as the basal forebrain cholinergic system (blue). Alternative strategies could use exogenous stem cells to deliver growth factors or anti-inflammatory mediators to other highly damaged regions, such as the hippocampus.

Chapter 12: Immunotherapy with Autologous Cells

Figure 1 Overview of approach to adoptive immunotherapy. The patient's own lymphocytes are obtained by: (a) peripheral blood draw; (b) excision of tumor bearing lymphocytes; (c) direct bone marrow biopsy; or (d) apheresis collection of mononuclear cells. Depending on the desired effect, these cells may then undergo (e)

ex-vivo

modifications including gene transfer and (f) expansion prior to (g) reinfusion.

Figure 2 Mechanism of leukapheresis for mononuclear cell collection. (a) Anticoagulated whole blood enters the machine housing traveling in sterile tubing; (b) Centrifugal force separates the various blood components by their density. In general, separation occurs between plasma (including platelet-rich and platelet-poor plasma), mononuclear cells, and red cell components; (c) By selectively aspirating the desired layer, specific blood components, may be isolated. Mononuclear cell layer removal is depicted here.

Figure 3 Selection of antigen-specific clones and expression of engineered T-cell receptors.

Figure 4 Multiple generations of CARs. The first-generation CARs were composed of a single extracellular domain with a scFV [88]. Second-generation CARs incorporated intracellular domains of costimulatory molecules such as CD28 [92, 97, 98] or 4-1BB [94, 95, 99]

in cis

with the remainder of the receptor.

Chapter 13: Targeted Therapy: Genomic Approaches

Figure 1 Targeted therapy approaches. (a) The hypothetical distribution of disorders by the number of underlying interaction is represented by the Poisson curve (blue), with the chances of meaningfully using targeted therapy depicted as a red line. The distribution goes from asymptotically close to zero for complex disorders, and asymptotically closer to one for Mendelian disorders (see text for details); (b) Three different types of targeted therapy approaches are commonly applied; (c,d) As physicists about a century ago moved from considering light as rays to its interpretation as waves (sometimes, at their convenience, using either description), we are moving from the paradigm of thinking about molecular life in terms of linear biochemical and signaling pathways (c, which can be disrupted by a drug with a predetermined consequences), to the more complex picture of biochemical “fabric” (d), where the drugs produce waves or ripples, interacting with those from other drugs or environmental inputs; (c) Common theoretical approach to targeted therapy, wherein signaling events are considered as linear with proposed precision targeting (red circle) and narrowly focused downstream effects; (d) Ripple effects of targeted therapy and the complexity of perturbing the signaling milieu: precisely hitting targets (crosshairs) in a few cases may have the intended therapeutic effect. However, commonly, the ripples effects, perturbation of alternative targets (white spots), under the correct conditions (e.g., correct dosage and drug combination, optimal treatment schedule) induce signaling-network-wide changes for the therapeutic effect (red circles). Wave image (c) modified from the Wolfram Demonstrations Project http://demonstrations.wolfram.com/TheQuantumHarmonicOscillatorWithTimeDependentBoundaryConditi/; wave image (d) generated using Wolfram (http://demonstrations.wolfram.com/WaveInterference/); network (d) generated using Cytoscape [1].

Figure 2 Target specificity and type based on Therapeutic Targets Database (TTD) data. (a,c) Relationship between the number of drugs and targets reveals that most targets correspond to only a few drugs (a), and, reciprocally, the overwhelming majority of drugs have at most two known targets (c); (b) Targets can be divided into four categories: suppressive effect on cancer/pathogen; suppressive effect on host; enhancing effect on pathogen/cancer; enhancing effect on host. The blue circles represent 10 targets based on TTD data; open blue circles represent manually curated data from the literature, indicating cases where compounds are used either to just visualize the cancer cells to enable the subsequent surgical removal (“neutral” position on the panel; see Sect. 2.5 for details), or to restore/enhance their antigen-presenting function, enabling their subsequent destruction by the immune system (see Sect. 2.3). All information was retrieved from the TTD [2] and sorted as human versus cancer/pathogen based on the target UniProt ID/disease type, and by functionality based on “agonist/activator” versus “inhibitor/antagonist” drug classifiers.

Figure 3 Evolving target specificity. The number of targets for drugs approved by 2006 and analyzed in 2006 (black line) compared to the same set of drugs reanalyzed in 2014 (red line) highlights the changes in terms of target specificity as drugs are continue to be studied. The gray line represents the number of targets for drugs approved from 2006–2014. The inset shows the reassessment of number of drug targets for drugs originally described to have one target in 2006 (blue line), two targets in 2006 (red line), and three targets in 2006 (green line) when reanalyzed in 2014 (indicated by the lines emanating from each solid sphere). Drug target data were obtained from DrugBank [3].

Figure 4 General biological aspects of targeted therapy. (a) Mutation leads to malignant cell transformation, and at the same time can provide a unique target for therapeutic intervention; (b) Pathogens can present unique targets for therapeutic intervention.

Figure 5 Pathological point mutations. The missense mutation in EGFR exon 21 (L858R) produces constitutively active receptors; a similar effect is seen with the V600E missense mutation in exon 15 of BRAF. Both mutations result in proteins targeted therapeutically. One of the causes of cystic fibrosis is a nonsense mutation in exon 20 (W1282X) of the cystic fibrosis transmembrane conductance regulator (CFTR).

Figure 6 Chromosomal aberration. (a) Three chromosomal translocations involving MYC are associated with Burkitt's lymphoma (BL): t(8;14), t(2;8), and t(8;22). t(8;14) is associated with 85–90% of BL cases. t(2;8) and t(8;22) are found in 10–15% of cases [140]. (a,b) EML4-ALK is caused by an inversion of Chr. 2 (t(2;2)); the Philadelphia Chromosome comes into existence when a translocation between Chr. 9 and Chr. 22 occurs. BCR-ABL is the oncogenic protein product of the Philadelphia Chromosome. The Circos plot (a) was generated using Circos (http://circos.ca/) [141].

Figure 7 Variations in gene expression. (a) In the case of ERBB2, gene amplification (Amp) leads to increased mRNA expressions; however, in general, the correlation between gene copy number and mRNA expression is low; (b) Distribution of correlation coefficients between copy number and mRNA levels in lung adenocarcinoma is shown; (c,d) Protein levels for ERBB2 correlate with mRNA expression levels: no such correlation is detectable for MYC; (e) Increased methylation correlates with decreased mRNA expression in the case of ERBB2; in the case of MYC, methylation patterns, and mRNA expression levels do not correlate (f). Data were obtained from the The Cancer Genome Atlas (TCGA; http://cancergenome.nih.gov/) to generate panels (a, c–e) using cBioPortal [162, 163] and panel (b) using the Genome Data Analysis Center (https://confluence.broadinstitute.org/display/GDAC/Home). Gain, gained; Diploid, normal number of chromosomes; Hetloss, heterozygously deleted; Homdel, homozygously deleted.

Figure 8 Targeting the human kinome. (a) All FDA-approved small-molecule kinase inhibitors are shown, and the dominant kinase targeted by each inhibitor is indicated on the kinome tree; (b,c) Numbers of drug targets for kinase inhibitors vary widely between different inhibitors; in addition, these numbers are reported differently in different databases and studies. Targets for bosutinib and lapatinib are indicated, as retrieved from the DrugBank (black dots) [3], the Therapeutic Targets Database (TTD; blue circles [2]) and an

in-vitro

study [81] (red circles); (b) Kinases targeted by bosutinib are shown. The size of the red circles indicates the inhibitory activity of the drug against the target (kinase) [81]; (c) Kinase targets for lapatinib are shown (red circle sizes are arbitrary). The human kinome illustration is reproduced courtesy of Cell Signaling Technology, Inc. (www.cellsignal.com) [180].

Figure 9 Epigenetic modulation. (a) Epigenetic modulation of gene expression via methylation status changes are shown; “writers” methylate methylation sites, causing condensation of chromatin and silencing of genes; “erasers” remove methylation, opening up the chromatin and allowing gene expression; (b) Methylation of histone H3 lysine 4 (H3K4) in normal cells is associated with gene expression; (c) Methylation of histone H3 lysine 9 (H3K9) in cancer cells is associated with gene silencing.

Figure 10 Targeted therapy against PCSK9. (I) Targeting PCSK9 mRNA with oligonucleotides; (II) exocytosis of LDLR and PCSK9 (red); (III) peptide mimetic binding to PCSK9; (IV) antibody binding to PCSK9; (V) LDL bound to LDLR and PCSK9; (VI) endocytosis of LDL/LDLR/PCSK9 and LDL/LDLR; (VII) lysosomal degradation of LDL and LDL/LDLR/PCSK9; (VIII) recycling of LDLR in the absence of bound PCSK9. PCSK9, proprotein convertase subtilisin/kexin type 9; LDL, low-density lipoprotein; LDLR, low-density lipoprotein receptor; Tx, treatment.

Figure 11 Distribution of current successful targets. About 6% of targets are membrane transporters and ion channels (I); about 22% are extracellular receptors (II); enzymes, which participate in important cellular processes such as metabolism, protein modification, intracellular signaling, protein degradation, comprise the largest number of targets, approximately 44% (III); only about 4% of targets are contained within the nucleus (IV); and about 4% of targets are structural proteins (V); 19% of targets include factors and regulators (VI); and about 1% of targets are still undetermined (VII). This distribution is based on data from 2006 [226].

Figure 12 Monoclonal antibody (mAb)-based therapy. (I) Successful ligand binding to the extracellular receptor; (II) mAb binds to receptor with consequent internalization and degradation of the complex; (III) Immunoconjugate of mAb, linker and radioactive agent binds to receptor, and after internalization the complex is degraded, causing intracellular release of the radioactive agent (radioactive probes can also cause cell death from the membrane surface and do not necessarily need to be internalized); (IV) bispecific monoclonal antibody (bsAb) simultaneously binds to receptors on targeted and immune effector cells; (V) cytotoxic agent is released from the immunoconjugate (similar to (III)); (VI) mAb-covered liposome with cytotoxic cargo is guided to the cell; (VII) targeting and altering the tumor microenvironment using mAbs; (VIII) targeting of extracellular cytokines, toxins and ligands can also be accomplish using mAbs.

Figure 13 Gene therapy in clinical trials. (a) Indication treated with gene therapy; (b) phase of gene therapy clinical trials; (c) gene types targeted by gene therapy. Data source: http://www.wiley.com/legacy/wileychi/genmed/clinical/.

Figure 14 Multidrug targeted therapy approaches. (a) Vertical treatment approach – inhibition of two or more proteins in the same signaling cascade; (b) Horizontal treatment approach – inhibition of two or more proteins in parallel signaling cascades; (c) Redundant treatment approach – inhibition of the same protein with two or more different therapeutic agents; (d) Synthetic lethality approach: (I and II) single gene disabled (mutation, RNAi, or inhibitor), survival possible; (III) combined inhibition of A and B, synthetic lethality; and (IV) activation of alternative pathways induces resistance (alternatively, A and B can also be reactivated).

Chapter 14: Pharmaceutical Process Chemistry

Figure 1 Attrition and timescale of the R&D process. Reproduced with permission from Pfizer.

Figure 2 Examples of late nineteenth century pharmaceuticals.

Figure 3 Structure of prontosil.

Scheme 1 The Upjohn cortisone synthesis.

Figure 4 Examples of oral drugs.

Scheme 2 Route A synthesis of lotrafiban.

Scheme 3 Route B synthesis of lotrafiban.

Figure 5 Pharmaceuticals manufactured using biocatalytic reactions.

Scheme 4 Route C synthesis of lotrafiban.

Scheme 5 Pd(binap)-catalyzed amination of 3-bromobenzotrifluoride.

Figure 6 High-energy functional groups.

Figure 7 Heat production versus heat removal.

Figure 8 FT-IR reaction monitoring of mono-HCl salt formation. The hydrochloric acid charge is optimized to minimize the formation of the bis-HCl salt. Reproduced with permission from Ref. [50]; © 2006, Elsevier.

Figure 9 The Pfizer solvent selection guide. Reproduced with permission from Ref. [65]; © 2008, The Royal Society of Chemistry.

Figure 10 Structures of deacetylbaccatin (DAB) and paclitaxel.

Scheme 6 Classical resolution route to pregabalin. (i) KOH, MeOH, H

2

O, reflux; (ii) H

2

RaNi, EtOH, H

2

O; then HOAc: then isopropyl alcohol (IPA) wash; (iii) (

S

)-mandelic acid, IPA, H

2

O, recrystallize from IPA, H

2

O, salt break, recrystallize from IPA, H

2

O.

Scheme 7 Biocatalytic route to pregabalin. (i) Lipolase-catalyzed enzymatic resolution performed in water; (ii) thermal decarboxylation performed in water; (iii) hydrolysis (KOH) and hydrogenation (H

2

/RaNi), both reactions performed in water; (iv) base-catalyzed epimerization.

Figure 11 Options for pharmaceutical development.

Figure 12 Peroxisome proliferator-activated receptor-α agonist LY518674.

Figure 13 Inflation-adjusted trend in R&D efficiency. Reproduced with permission from Ref. [88]; © 2012, Nature Publishing Group.

Figure 14 Pharmaceutical R&D expenditure, timelines, and output (1999–2009). Reproduced by permission of CMR International, a Thomson Reuters business.

Chapter 15: High-Performance Liquid Chromatography of Peptides and Proteins

Figure 1 Schematic depiction of a chromatogram. Abbreviations:

t

0

= column void time (time from injection to detection of unretained compound),

t

R

1

,

t

R

2

,

t

R

3

= retention times (time from injection to detection of retained compounds),

h

= peak height,

w

= peak width (measured at baseline), and

w

1/2

= peak width at half height (measured to characterize column efficiency).

Figure 2 Van Deemter–Knox plots (top curve) and the plots of individual contributions of the

A

-term,

B

/

u

term, and the

Cu

-term to the plate height.

Figure 3 Optimization of isocratic elution. Two chromatograms obtained for (a) 19% and (b) 14% (v/v) of organic solvent modifier in the mobile phase (corresponding to

ϕ

= 0.19 and 0.14, respectively) can be used to plot (c) the corresponding logarithmic retention factors ln

k

versus the volume fraction of the organic solvent modifier in order to identify the mobile phase composition resulting in optimal peak spacing. Trend lines can determine mobile phase compositions which result in peak overlap or excellent peak resolution.

Figure 4 Optimization goals of speed, resolution, capacity, and recovery for a chromatographic purification, and their inter-relationship.

Figure 5 Degree of orthogonality of major chromatographic modes employed in the separation of peptides and proteins.

Figure 6 Two-dimensional separation space for a set of peptides and proteins (circles) utilizing separation systems that are: (a) uncorrelated (orthogonal); (b) completely correlated; and (c) inversely correlated, where the retention factors ln

k

obtained in the second dimension are plotted versus the retention factors obtained in the first dimension.

Figure 7 Compatibility between commonly used mobile phases of chromatographic modes based on miscibility, solubility, and eluotropic strength.

Chapter 16: Hit-to-Lead Medicinal Chemistry

Figure 1 Drug discovery chevron diagram.

Figure 2 An example of the selective optimization of side activities (SOSA) approach.

Figure 3 Selectivity: the separation between drug concentration required for pharmacological effect and that which produces toxicity.

Figure 4 A typical screening cascade depicting several levels of assays used to filter compounds on the path to lead declaration.

Figure 5 Molecular weight gain involved in the development of hit (

5

) to the drug sorafenib (

6

).

Figure 6 An example of the evolution of fragment hits to generate a potent ROA inhibitor (

10

).

Chapter 17: Mass Spectrometry-Based Methods of Proteome Analysis

Figure 1 Principle scheme of (a) single MS and (b) MS/MS analyses. (a) Intact proteins or peptides are transferred from the condensed phase into the gas phase and are ionized through capture (positive mode) or loss (negative mode) of protons. In high-throughput protein identification experiments, a positive mode of ionization is used. A negative mode of ionization can be used for the analysis of carbohydrates and nucleic acids. Ions of different

m

/

z

are discriminated by magnetic or electric fields; (b) Ions of which the structure needs to be determined are chosen for fragmentation via CID reactions in the MS/MS experiment. The fragmentation patterns obtained can be searched against protein databases for identification.