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E-raamat: Structural Biology in Drug Discovery: Methods, Techniques, and Practices

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Structural Biology in Drug Discovery: Methods, Techniques, and PracticesSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 09-Jan-2020
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781118900505
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With the most comprehensive and up-to-date overview of structure-based drug discovery covering both experimental and computational approaches, Structural Biology in Drug Discovery: Methods, Techniques, and Practices describes principles, methods, applications, and emerging paradigms of structural biology as a tool for more efficient drug development. Coverage includes successful examples, academic and industry insights, novel concepts, and advances in a rapidly evolving field.

The combined chapters, by authors writing from the frontlines of structural biology and drug discovery, give readers a valuable reference and resource that:





Presents the benefits, limitations, and potentiality of major techniques in the field such as X-ray crystallography, NMR, neutron crystallography, cryo-EM, mass spectrometry and other biophysical techniques, and computational structural biology Includes detailed chapters on druggability, allostery, complementary use of thermodynamic and kinetic information, and powerful approaches such as structural chemogenomics and fragment-based drug design Emphasizes the need for the in-depth biophysical characterization of protein targets as well as of therapeutic proteins, and for a thorough quality assessment of experimental structures Illustrates advances in the field of established therapeutic targets like kinases, serine proteinases, GPCRs, and epigenetic proteins, and of more challenging ones like protein-protein interactions and intrinsically disordered proteins

Arvustused

"The book ... is a surprisingly comprehensive, monumental collection of chapters by a number of researchers in the field of drug discovery. ... [ Editor Jean-Paul] Renaud was able to see the broad crucial aspects of the field and therefore able to invite excellent scientists to coauthor this book and cover so many aspects and in so much depth." -- Crystallography Reviews, March 2022

List of Contributors xxii
Preface xxvii
Part I Overview, Concepts, and Approaches 1(142)
1 The Evolving Role of Structural Biology in Drug Discovery
3(20)
Jean-Paul Renaud
1.1 Introduction
3(2)
1.2 The Expanding Toolbox of Structural Biology for Drug Discovery
5(5)
1.3 The Various Uses of Structural Biology in Drug Discovery
10(2)
1.4 Evolving Drugs and Targets
12(1)
1.5 Current Trends and Perspectives
13(1)
References
14(9)
2 A Structural View on Druggability: Experimental and Computational Approaches
23(30)
Ursula Egner
Roman C. Hillig
2.1 Introduction
23(1)
2.2 Views on Target Druggability
24(1)
2.3 In Silico Methods for Druggability Assessment of Targets with Well-defined Pockets
25(9)
2.3.1 Binding Site Identification
26(2)
2.3.2 Selection of Descriptors and Datasets for Method Development
28(1)
2.3.3 Development of Druggability Models
29(4)
2.3.4 Druggability Prediction via Alternative Methods
33(1)
2.4 Experimental Methods for Druggability Assessment
34(3)
2.5 A Challenge for Druggability Predictions: Protein-Protein Interactions
37(8)
2.5.1 Identification of Binding Sites for Protein-Protein Interaction Targets
39(1)
2.5.1.1 Computational Solvent Mapping
39(1)
2.5.1.2 Molecular Dynamics and Monte Carlo Simulations
40(1)
2.5.1.3 Hot Spot Identification
42(1)
2.5.2 Druggability Assessment of Protein-Protein Interaction Targets
43(2)
2.6 Perspective
45(1)
References
46(7)
3 Structural Chemogenomics: Profiling Protein-Ligand Interactions in Polypharmacological Space
53(26)
Babs Briels
Chris de Graaf
Andreas Bender
3.1 Introduction
53(1)
3.2 Simultaneously Targeting Multiple Proteins Can Be More Efficient in Disrupting Disease Mechanism
54(3)
3.2.1 Disease Mechanisms Call for the Need of A Systematic Targeting Approach
54(1)
3.2.2 Multiple Ways to Adopt A Multi-target Approach with Low-Affinity Binders
55(1)
3.2.3 Polypharmacology Allows for Repurposing of Marketed Drugs and Drug Rescue
56(1)
3.2.4 Optimization of Multiple Structure-Activity Relationships Simultaneously Is Difficult
57(1)
3.3 Computer-Aided Approaches for Profiling Bioactivities of Ligands
57(11)
3.3.1 Ligand-Based Methods for Target Prediction
58(1)
3.3.1.1 In Silico Target Prediction Using Chemical Similarity Methods and Data Mining
58(1)
3.3.1.2 Ligand-Based Pharmacophore-Based Models for Target Prediction
58(1)
3.3.1.3 Identification of Privileged Ligand Scaffolds and Structure-Selectivity Cliffs
59(1)
3.3.2 Protein-Ligand-Based Methods to Predict Bioactivities of Ligands Against Targets
60(1)
3.3.2.1 Chemogenomics for All-Against-All Bioactivity Prediction
60(1)
3.3.2.2 Proteochemometric Modeling Combines Protein-Ligand Space in a Predictive Statistical Method
61(1)
3.3.3 Structure-Based Tools for Prospective Protein-Ligand Interaction Prediction
62(1)
3.3.3.1 Cavity Detection Methods Locate Probable Ligand Binding Sites
62(1)
3.3.3.2 Cavity Description Methods Simplify Protein Structure Description for Fast Binding Site Comparison
63(1)
3.3.3.3 Similarity Search Methods
64(1)
3.3.3.4 Scoring Protein Cavity Similarity by Counting Overlapping Occurrences
65(1)
3.3.3.5 Protein-Based Pharmacophore Modeling
65(1)
3.3.3.6 Target Fishing Using Proteome-Scale Docking
66(1)
3.3.3.7 Post-processing Docking Data to Complement Scoring Functions
66(1)
3.3.3.8 Knowledge-Based Structural Databases to Navigate Protein-Ligand Interaction Space
67(1)
3.4 Applications
68(3)
3.4.1 Designing Ligands with Desired D2 and D4 Dopamine Receptor Activities
69(1)
3.4.2 Similarity Ensemble Approach (SEA) to Predict Off-Target Binding of FDA-Approved Drugs
69(1)
3.4.3 Target Prediction in Chemical Genetics Using SEA
69(1)
3.4.4 Ligand-Based Prediction of Target Space for Malaria Drug Development Using PredictFX
70(1)
3.4.5 Chemically Similar Compounds of Multi-target SAR-Tested Ligands Inhibit Cell Proliferation and Tumor Growth
70(1)
3.4.6 Prospective Prediction of Cross-Reaction Protein Kinase Inhibitors Using Binding Site Comparison Method SiteAlign
70(1)
3.4.7 Explaining the Mode of Action of Traditional Medicine Using A Chemogenomic Target Prediction Tool
71(1)
3.4.8 Combining Ligand-Based and Structure-Based Pharmacophore Screenings to Determine Novel Bioactive GPCR Ligands and Multi-target Binding
71(1)
3.4.9 Profiling Bioactive Compounds Using a Combined Ligand-Based and Protein-Based Workflow
71(1)
3.5 Conclusion
71(1)
References
72(7)
4 Fragment-Based Ligand Discovery
79(20)
Ben J. Davis
Roderick E. Hubbard
4.1 Introduction
79(1)
4.2 The Evolution of FBLD
79(2)
4.3 The FBLD Process
81(1)
4.4 Fragment Libraries
82(1)
4.4.1 Step A: Chemoinformatics Selection
82(1)
4.4.2 Step B: Focused Libraries?
83(1)
4.4.3 Step C: Characterizing Diversity
83(1)
4.4.4 Step D: Visual Inspection
83(1)
4.5 Maintaining a Fragment Library
83(1)
4.6 Fragment Screening
84(5)
4.6.1 Nuclear Magnetic Resonance (NMR)
84(3)
4.6.2 Surface Plasmon Resonance (SPR)
87(1)
4.6.3 Thermal Shift Assay (TSA)
88(1)
4.6.4 Biochemical Assay
88(1)
4.6.5 Crystallography
88(1)
4.6.6 Mass Spectrometry
88(1)
4.6.7 Isothermal Titration Calorimetry (ITC)
88(1)
4.6.8 Other Ideas and Approaches
89(1)
4.7 Integrating Fragments with Other Compounds
89(1)
4.8 Validating Fragment Hits: Comparing Methods
90(1)
4.9 Fragment Hit Rates
91(1)
4.10 Determining Structures of Fragment: Protein Complexes
91(1)
4.11 Fragment Evolution
92(4)
4.12 Concluding Remarks
96(1)
Acknowledgments
96(1)
References
96(3)
5 Combining Structural, Thermodynamic, and Kinetic Information to Drive Hit-to-Lead Progression
99(26)
Geoffrey A. Holdgate
Christopher Phillips
5.1 Introduction
99(1)
5.1.1 Hit Identification
99(1)
5.2 The Role of Thermodynamics in Hit to Lead
99(8)
5.2.1 Isothermal Titration Calorimetry (ITC) Technology and Measurements
99(1)
5.2.1.1 Introduction
99(1)
5.2.1.2 Commercial ITC Instrument History
99(1)
5.2.1.3 ITC Instrumentation
100(1)
5.2.1.4 The ITC Experiment
100(1)
5.2.1.5 Measurement of Thermodynamic Parameters
101(1)
5.2.1.6 Benefits of Applying Thermodynamic Measurements in Hit to Lead
103(1)
5.2.1.7 Exploitation of Measured Thermodynamics
104(3)
5.3 The Role of Kinetics in Hit to Lead
107(14)
5.3.1 Surface Plasmon Resonance (SPR) Technology and Measurements
107(1)
5.3.1.1 Introduction
107(1)
5.3.1.2 Commercial SPR Instrument History
108(1)
5.3.1.3 General SPR Instrumentation
108(1)
5.3.1.4 The SPR Experiment
109(1)
5.3.1.5 Other Methods to Determine Binding Kinetics
113(1)
5.3.1.6 Biolayer Interferometry (BLI)
113(1)
5.3.1.7 Radioligand Binding
113(1)
5.3.1.8 Residence Times
114(1)
5.3.1.9 Mechanism of Action
116(1)
5.3.1.10 Protein Structure and Dynamics
116(1)
5.3.1.11 Correlating Kinetic and Structural Data in Hit-to-Lead Programs
117(1)
5.3.1.12 Correlating Structural and Thermodynamic Data in Hit-to-Lead Programs
118(3)
5.4 Summary
121(1)
References
122(3)
6 Allostery as Structure-Encoded Collective Dynamics: Significance in Drug Design
125(18)
Indira H. Shrivastava
Chang Liu
Anindita Dutta
Ahmet Bakan
Ivet Bahar
6.1 Introduction
125(3)
6.1.1 Experimental Data Highlight the Complexity of Allosteric Events, Beyond MWC or KNF Models: Bacterial Chaperonin GroEL as a Paradigm
125(2)
6.1.2 New Views: Allostery as Population Shift Between Preexisting Conformers or Reconfiguration Along Preexisting Soft Path
127(1)
6.1.3 Dynamics and Drug Discovery
128(1)
6.2 Computational Methods
128(4)
6.2.1 Gaussian Network Model (GNM): Simplest ENM
129(2)
6.2.2 Anisotropic Network Model (ANM) Theory and Assumptions
131(1)
6.3 Applications
132(4)
6.3.1 Conformational Sampling by ANM and Comparison with Experimental Data and Molecular Simulations
132(1)
6.3.1.1 p38 Protein Kinase
132(1)
6.3.1.2 Leucine Transporter (LeuT)
132(1)
6.3.2 Allosteric Drug Binding Sites Inferred from ENM Analysis: Application to HIV-1 Reverse Transcriptase
133(1)
6.3.3 Pharmacophore Modeling from Druggability Simulations
134(2)
6.4 Future Directions and Conclusion
136(2)
6.4.1 Allosteric Cooperativity and Cellular Effects
136(2)
6.4.2 Future Directions and Concluding Remarks
138(1)
References
138(5)
Part II Tools 143(220)
7 Biophysical Assessment of Target Protein Quality in Structure-Based Drug Discovery
145(20)
Arne Christian Rufer
Michael Hennig
7.1 Biophysical Methods in Drug Discovery
145(1)
7.2 Case Study I: Micro-inhomogeneity
146(4)
7.2.1 Recovering Active Enzyme for Ligand Co-crystallization: The Lysosomal Cysteine Protease Cathepsin S
146(4)
7.3 The Role of Biophysical Methods in the Optimization of Protein Crystallization
150(4)
7.3.1 Biophysical Methods Performed in Solution (Liquid Sample)
151(3)
7.3.2 Biophysical. Methods That Require Immobilization on Surfaces or Transfer of the Protein to the Gas Phase
154(1)
7.4 Case Study II: Minimizing Macro-inhomogeneity
154(5)
7.4.1 Optimizing Detergent Conditions for Membrane Proteins: The Mitochondrial β-Oxidation Pacemaker Carnitine Palmitoyltransferase 2
154(4)
7.4.2 Comparison of AUC to SEC for the Characterization of CPT-2
158(1)
7.5 Outlook and Concluding Remarks: Requirements for Upcoming Biophysical Methods
159(1)
Acknowledgment
160(1)
References
160(5)
8 An Industrial Perspective on Protein-Ligand Complex Crystallization
165(22)
Carien Dekker
Arnaud Goepfert
8.1 Introduction to Co-crystal Structures and Drug Development
165(1)
8.2 Basics of X-Ray Analysis of Co-crystals
165(2)
8.2.1 Protein Crystallography in a Nutshell
165(1)
8.2.2 Application of X-Ray Analysis to the Study of Ligand Binding
166(1)
8.3 Ligands
167(2)
8.3.1 Detection of Ligand Binding
167(1)
8.3.2 Validation of Ligand Binding
167(1)
8.3.3 Ligand Binding Sites: Pockets, Grooves, and Allosteric Sites
168(1)
8.3.4 Crystal Packing Sites and Other Artifacts
168(1)
8.3.5 Complementary Techniques: NMR, SPR, ITC, DSF, SAXS, and EM
168(1)
8.4 Preparing Protein for Successful Crystallization
169(3)
8.4.1 Construct Design and the Importance of Boundary Predictions
170(1)
8.4.2 Protein Production
170(1)
8.4.3 Protein Purification and Quality Assessment
171(1)
8.5 Crystallization
172(3)
8.5.1 The Crystallization Process
172(1)
8.5.2 Crystallization Screening
172(1)
8.5.3 Automation of Crystallization Setup and Imaging
173(1)
8.5.4 Optimization of Crystallization
174(1)
8.5.5 What If the Protein Does Not Crystallize?
174(1)
8.6 Selecting Ligands for Crystallization
175(3)
8.6.1 Introduction to Ligands and Compound Selection
175(1)
8.6.2 Finding the Best Starting Point for Hit to Lead
176(1)
8.6.3 Hot Spots, Potency, and IC50's
176(1)
8.6.4 The Importance of Solubility
177(1)
8.6.5 The Effects of Ligands on Protein Stabilization
177(1)
8.6.6 Pitfalls of Detecting Ligand Binding in a Protein Crystal
177(1)
8.7 Methods for Obtaining Co-Crystals: Soaking and Co-crystallization
178(6)
8.7.1 Concept of Ligand Soaking
178(1)
8.7.2 Advantages and Potential of Soaking Ligands
178(1)
8.7.3 Ligand Concentrations
179(1)
8.7.4 Exemplary Soaking Can Guide Drug Discovery
180(2)
8.7.5 Concept of Co-crystallization
182(1)
8.7.6 Advantages and Potential of Co-Crystallization
182(1)
8.7.7 Case Study: Complex Structures of HdmX with p53 Peptide Analogs
182(2)
8.8 Future Perspective
184(1)
Acknowledgment
184(1)
References
184(3)
9 Membrane Protein Crystallization
187(24)
Ching-Ju Tsai
Gebhard F.X. Schertler
9.1 Introduction
187(2)
9.1.1 A Brief History
187(1)
9.1.2 Membrane Protein Biochemistry
187(2)
9.1.3 Overview from Protein Preparation to Crystallization
189(1)
9.2 Membrane Protein Production
189(3)
9.2.1 Membrane Proteins from Natural Sources
191(1)
9.2.2 Bacterial and Yeast Expression Systems
191(1)
9.2.3 Insect Cell Expression Systems
191(1)
9.2.4 Mammalian Cell Expression Systems
192(1)
9.2.5 Cell-Free Expression Systems
192(1)
9.3 Amphipathic Manipulation of Membrane Proteins
192(3)
9.3.1 Detergent in Membrane Protein Biochemistry
192(2)
9.3.2 Classical Detergents
194(1)
9.3.3 Maltose-neopentyl Glycol Amphiphiles
194(1)
9.3.4 Amphipols
194(1)
9.3.5 Lipopeptide Detergents and n-Strand Peptides
195(1)
9.3.6 Nanodiscs
195(1)
9.4 Preparing Protein Samples for Crystallization
195(3)
9.4.1 Overview of Protein Sample Preparation
195(1)
9.4.2 Criteria for Selecting Suitable Protein Targets
196(1)
9.4.3 Quality Control of Purified MPs
197(1)
9.4.4 Protein Engineering
198(1)
9.5 Membrane Protein Crystallization
198(5)
9.5.1 In Surfo Crystallization
199(1)
9.5.2 In Meso Crystallization
200(1)
9.5.3 Bicelle Crystallization
200(1)
9.5.4 2D Crystallization
201(1)
9.5.5 Effect of Detergent and Lipid in Crystallization
201(1)
9.5.6 Complex with Fusion and Binding Partners
202(1)
9.5.7 Optimizing Crystallization Conditions
202(1)
9.5.8 Evaluating Crystallization Conditions
202(1)
9.6 Methods for Determining Membrane Protein Structures
203(1)
9.6.1 X-Ray Crystallography
203(1)
9.6.2 X-Ray Free-Electron Laser
203(1)
9.6.3 Cryo-electron Microscopy
204(1)
9.6.4 Nuclear Magnetic Resonance Spectroscopy
204(1)
9.7 Conclusion and Outlooks
204(1)
References
205(6)
10 High-Throughput Macromolecular Crystallography in Drug Discovery: Evolving in the Midst of Revolutions
211(42)
Gerard Bricogne
10.1 Introduction
211(1)
10.2 Setting the Scene for Evolution and Revolutions
212(2)
10.2.1 MX, SBDD, and SG and Beyond
212(1)
10.2.2 MX for SBDD in a Nutshell: A Vast Combinatorial Search
212(1)
10.2.3 The High-Throughput (HT) Imperative in MX-for-SBDD Workflows
213(1)
10.3 Baseline: The "Human, All Too Human" Workflow of Early MX for SBDD
214(1)
10.4 First Wave of Automation Toward High-Throughput Operation: Robotics Without Refactoring
215(2)
10.5 Second Wave of Automation: The Twin Tracks of In Situ Crystallography and Microcrystallography
217(15)
10.5.1 In Situ Crystallography
218(1)
10.5.1.1 Initial Concept
218(1)
10.5.1.2 Immediate Screening for Diffraction Quality
218(1)
10.5.1.3 Data Collection from Multiple Small Crystals
218(1)
10.5.1.4 Robotics Unbound: Take 1
219(1)
10.5.1.5 Related Instrumental Developments
220(1)
10.5.2 Microcrystallography
221(1)
10.5.2.1 Initial Concept
221(1)
10.5.2.2 Hard Limits on MX Diffraction Measurements from Fundamental Principles
221(1)
10.5.2.3 Aiming for the Highest Possible S/N Ratio in MX Experiments
222(1)
10.5.2.4 Related Instrumental Developments
228(1)
10.5.3 Convergence Toward Multi-crystal Data Collection
228(1)
10.5.3.1 Microcrystallography in Action: A Chronicle of Early GPCR Structure Determinations
229(1)
10.5.3.2 In Situ Crystallography in Action: Two Recent Studies on Membrane Proteins
231(1)
10.5.3.3 Evolution of Processing Methods for Multi-crystal Datasets
231(1)
10.6 An Emerging Third Wave of Automation: Serial Microcrystallography
232(3)
10.6.1 XFELs and SFX: A Very Brief Introduction
232(1)
10.6.1.1 Sample Delivery Issues
232(1)
10.6.1.2 Data Analysis Issues
233(1)
10.6.2 Serial Crystallography as the Convergence of SMX and SFX
233(1)
10.6.3 Pros and Cons of SMX vs. SFX
233(1)
10.6.4 The Heart of the Matter for Serial Crystallography: The Humpty Dumpty Problem
234(1)
10.6.5 A Neglected Niche: Club Class Data Collection on Macrocrystals
235(1)
10.7 From Diffraction Data to Structural Results: Evolving Best Practices
235(4)
10.7.1 Setting Up the Framework for Ligand Screening and Binding Mode Characterization by HTMX
235(1)
10.7.1.1 Crystal System
235(1)
10.7.1.2 High-Quality Reference Model
235(1)
10.7.1.3 Bookkeeping of Variants of Crystal Forms and Reference Models
236(1)
10.7.1.4 Ligand Chemoinformatics and Molecular Geometry
236(1)
10.7.2 Operating the High-Throughput Ligand Screening Pipeline
236(1)
10.7.2.1 Processing Diffraction Images and Identification of Crystal Form
236(1)
10.7.2.2 Use of Reference Atomic Models and mtz Files
236(1)
10.7.2.3 Eliciting Difference Density for Ligand Detection
236(1)
10.7.2.4 Ligand Electron Density Analysis and Automated Fitting
237(1)
10.7.2.5 Final Refinement of Ligand-Target Complex
237(1)
10.7.2.6 Validation of the Ligand-Target Co-structure
238(1)
10.7.3 Post-analysis of Ensembles of Ligand Co-structures
238(1)
10.7.4 Auto-processing at Synchrotrons: Toward Specialized Cloud Computing?
238(1)
10.8 Conclusions and Outlook: Whither HTMX for Drug Discovery?
239(1)
Acknowledgments
240(1)
References
240(13)
11 Assessment of Crystallographic Structure Quality and Protein-Ligand Complex Structure Validation
253(24)
Karolina A. Majorek
Matthew D. Zimmerman
Marek Grabowski
Ivan G. Shabalin
Heping Zheng
Wladek Minor
11.1 Introduction
253(3)
11.2 Quality Parameters
256(1)
11.3 Dataset Quality
256(7)
11.3.1 Dataset Quality: Resolution
256(1)
11.3.2 Dataset Quality: Other Quality Indicators of Diffraction Data
257(1)
11.3.3 Agreement of the Model to the Experimental Data
258(1)
11.3.3.1 Agreement of the Model to the Experimental Data: R and Rfree Factors
258(1)
11.3.3.2 Agreement of the Model with the Experimental Data: B-Factors and Occupancy
258(1)
11.3.3.3 Agreement of the Model to the Experimental Data: Electron Density Fit
259(2)
11.3.4 Stereochemical Accuracy of the Model
261(1)
11.3.4.1 Stereochemical Accuracy of the Model: Bond Length and Angle r.m.s.d.
261(1)
11.3.4.2 Stereochemical Accuracy of the Model: Ramachandran Plot and Peptide Planarity
261(1)
11.3.4.3 Stereochemical Accuracy of the Model: van der Waals Clashes and Hydrogen Bonding Networks
262(1)
11.3.4.4 Stereochemical Accuracy of the Model: Metal Ions
263(1)
11.3.5 Coordinate Uncertainty
263(1)
11.4 Low-Resolution Structures
263(1)
11.5 Possible Influence of Crystal Packing
264(1)
11.6 Software Tools
265(3)
11.7 Analysis of Quality Metrics
268(3)
11.8 Conclusions
271(1)
Acknowledgments
271(1)
References
271(6)
12 Complementary Information from Neutron Crystallography Studies
277(18)
Motoyasu Adachi
Ryota Kuroki
12.1 Introduction
277(1)
12.2 Differences in Characteristics of X-Rays and Neutrons
277(1)
12.3 A Brief History of Protein Neutron Crystallography
278(1)
12.4 Facility, Neutron Source, and Detector
278(1)
12.5 Current Status of Neutron Protein Crystallography
278(1)
12.6 Method for Neutron Crystallography of Proteins
279(4)
12.6.1 Sample Preparation
279(1)
12.6.1.1 Sample Requirement for Neuron Crystallography
279(1)
12.6.1.2 Protein Overproduction and Purification for Neutron Protein Crystallography
280(1)
12.6.1.3 Perdeuteration of Protein
280(1)
12.6.1.4 Consideration of Chemical Instability During the Crystallization Experiment
280(1)
12.6.1.5 Crystal Lattice Engineering to Control Crystal Packing
281(1)
12.6.2 Crystal Growth for Neutron Protein Crystallography
281(1)
12.6.2.1 Crystallization Screening to Obtain a Large Crystal Volume
281(1)
12.6.2.2 Macroseeding to Grow Large Crystals
281(1)
12.6.2.3 Periodic Addition of Protein to Promote Large Crystal Growth
281(1)
12.6.3 Neutron Diffraction Experiment
281(1)
12.6.3.1 Mounting a Deuterated Protein Crystal
281(1)
12.6.3.2 Neutron Diffraction Data Collection
281(1)
12.6.3.3 Data Processing of the Neutron Diffraction Dataset
282(1)
12.6.3.4 Model Building Along with the Neutron Scattering Length Map
283(1)
12.7 General Information Obtained from Neutron Crystallography
283(2)
12.7.1 Hydrogen Atoms Contributing to the Fold of a Protein
283(1)
12.7.1.1 Hydrogen Bonding Interaction
283(1)
12.7.1.2 Structure of Aliphatic Groups
284(1)
12.7.2 Hydration Structure
284(1)
12.7.3 Ionization Status of Side Chains
285(1)
12.7.3.1 Ionization Status of Active Site Residues
285(1)
12.7.3.2 Hydrogen Atoms of Residues at Protein-Protein Interfaces
285(1)
12.8 Use of Neutron Crystallography for the Structure Analysis of Protein Drug Targets
285(2)
12.8.1 Acid Proteases
285(1)
12.8.1.1 Acid Proteases as a Drug Target
285(1)
12.8.1.2 Neutron Structure Analysis of HIV-1 Protease
285(1)
12.8.2 Serine Proteases
286(1)
12.8.2.1 Serine Proteases as a Drug Target Protein
286(1)
12.8.2.2 Neutron Structure Analysis of Porcine Pancreatic Elastase with Its Inhibitor
287(1)
12.9 Use of Neutron Protein Crystallography for Drug Design
287(2)
12.9.1 Determination of the Ionization State of Active Site Residues
287(1)
12.9.2 Characteristics of the Hydration of Water
288(1)
12.9.3 Discrimination of Atoms, Water Molecules, and Other Bound Inorganic Ions
288(1)
12.9.4 Improvement of Protein-Protein Association
288(1)
12.10 Future Perspectives of the Use of Neutron Crystallography for Drug Design
289(1)
References
289(6)
13 Determination of Protein Structure and Dynamics by NMR: State of the Art and Application to the Characterization of Biotherapeutics
295(30)
Marc-Andre Delsuc
Marc Vitorino
Bruno Kieffer
13.1 Introduction
295(1)
13.2 Solution Structure Determination of Macromolecules by NMR
296(5)
13.2.1 Introduction
296(1)
13.2.2 The NMR Observables
297(2)
13.2.3 From NMR Observables to 3D Models
299(1)
13.2.4 Current Developments
300(1)
13.3 Assignment and Labeling Strategies
301(3)
13.3.1 Spectral Assignment
301(1)
13.3.1.1 Homonuclear Spectroscopy
301(1)
13.3.1.2 Labeling with 15N, 13C, and 2H
301(1)
13.3.2 Partial or Full Assignment
301(1)
13.3.2.1 Backbone Assignment
301(1)
13.3.2.2 Side-Chain Assignment
302(1)
13.3.2.3 Site-Directed Mutagenesis
303(1)
13.3.3 Isotopic Labeling Methods
303(1)
13.3.3.1 Bacterial
303(1)
13.3.3.2 Cell-Free
303(1)
13.3.3.3 Yeast
303(1)
13.3.3.4 Insect or Mammalian Cells
303(1)
13.3.3.5 Chemical Synthesis
303(1)
13.3.4 Mixed Strategies
303(1)
13.3.4.1 Native Unlabeled Proteins
303(1)
13.3.4.2 Classical 15N, 15N-13C, and 15N-13C-2H Approaches
303(1)
13.3.4.3 Methyl Groups
304(1)
13.3.4.4 SAIL
304(1)
13.3.4.5 Selective Amino Acid Labeling/Unlabeling
304(1)
13.3.4.6 Subunit Labeling/Segmental Labeling
304(1)
13.3.4.7 Chemical Labeling
304(1)
13.4 NMR and Dynamic Aspects
304(3)
13.5 Biomolecular Dynamics by NMR
307(3)
13.5.1 Introduction
307(1)
13.5.2 Probing Disorder: Relaxation Measurements and Interpretation
308(1)
13.5.3 Beyond the Rotational Diffusion Limit
309(1)
13.6 Intrinsically Disordered Proteins
310(3)
13.6.1 Introduction
310(1)
13.6.2 General Presentation of IDPs
310(1)
13.6.3 NMR Techniques for IDP
311(1)
13.6.4 Interpreting IDP Spectra
312(1)
13.6.5 IDPs as Drug Targets
313(1)
13.7 Alternative Approaches for Non-soluble Proteins
313(2)
13.7.1 Solid-State NMR
313(1)
13.7.2 Membrane Proteins
314(1)
13.8 Optimized Strategies for the Study of Biomolecules in Solution
315(3)
13.8.1 Instrumental Setup
315(1)
13.8.2 Sample Preparation
315(1)
13.8.2.1 Unlabeled Proteins in Buffer
316(1)
13.8.2.2 Labeled Proteins
316(1)
13.8.3 NMR Experiments
316(1)
13.8.3.1 Quality Control
316(1)
13.8.3.2 1D Spectroscopy on Unlabeled Samples
317(1)
13.8.3.3 2D Spectroscopy on Unlabeled Samples
317(1)
13.8.3.4 2D and 3D Spectroscopy on Labeled Samples
318(1)
13.9 Conclusion
318(1)
References
319(6)
14 NMR Studies of Protein-Small Molecule Interactions for Drug Discovery
325(22)
Daniel F. Wyss
Edward R. Zartler
14.1 Introduction
325(2)
14.2 Early-Stage Discovery
327(6)
14.2.1 Target Validation
327(1)
14.2.2 Hit Identification and Validation
328(4)
14.2.3 Hit-to-Lead Optimization
332(1)
14.3 Lead Optimization
333(2)
14.4 Emerging Applications/Fields
335(5)
14.4.1 Membrane Proteins
335(2)
14.4.2 In-Cell NMR Spectroscopy
337(1)
14.4.3 Intrinsically Disordered Proteins
337(3)
14.5 Outlook
340(1)
References
340(7)
15 Computational Structural Biology for Drug Discovery: Power and Limitations
347(16)
Andrey V. Ilatovskiy
Ruben Abagyan
15.1 Introduction
347(1)
15.2 Converting PDB Entries into Full-Atom Models
347(4)
15.2.1 Extent of the Construct
347(1)
15.2.2 Electron Density Fit
348(1)
15.2.3 PDB Files
349(1)
15.2.4 Pocket Environment and Functional State
349(1)
15.2.5 Proteome Coverage
349(2)
15.3 Homology Modeling
351(3)
15.3.1 Homology Modeling Process
351(1)
15.3.2 Target Difficulty
352(1)
15.3.3 Model Quality
352(1)
15.3.4 Assessments
353(1)
15.3.5 Limitations
353(1)
15.3.5.1 Sequence-Structure Relationship and Template Selection
353(1)
15.3.5.2 Target-Template Alignment
353(1)
15.3.5.3 Backbone Deviations
353(1)
15.3.5.4 Loops
354(1)
15.3.5.5 Ligand Binding
354(1)
15.3.5.6 Model Selection and Ranking
354(1)
15.4 Prediction of Protein-Ligand Interactions
354(3)
15.4.1 Prediction of Transition State Analogs
357(1)
15.4.2 Compound Profiling
357(1)
15.4.3 Prediction of Compound Metabolism
357(1)
15.5 Future Perspective
357(1)
Acknowledgments
358(1)
References
358(5)
Part III Structure-Based Discovery in Some Important or Promising Targets and Therapeutic Families 363(158)
16 The Role of Structural Biology in Kinase Inhibitor Drug Discovery Success
365(30)
Mauro Angiolini
16.1 Protein Kinases and Their Structural Elements: A Dynamic Landscape for Drug Discovery
365(5)
16.2 The Challenge of Selectivity and Drug Resistance: Design and Discovery of Afatinib, the First Irreversible Protein Kinase Inhibitor Approved for Cancer Treatment
370(5)
16.3 When Structural Biology Drives Chemistry to Therapeutic Breakthrough: The Vemurafenib Case History
375(2)
16.4 Second-Generation Anaplastic Lymphoma Kinase Inhibitors: The Discovery of the First-in-Class Drug Ceritinib
377(3)
16.5 The Discovery of Type II Inhibitor Ponatinib: A Milestone in the Struggle Against the ABL Gatekeeper Resistant Mutation T315I
380(3)
16.6 Protein Kinase Inhibitor Drug Discovery and Structural Biology: Future Perspective
383(1)
References
384(11)
17 Serine Proteinases from the Blood Coagulation Cascade
395(28)
Herman Schreuder
Hans Matter
17.1 Introduction
395(3)
17.1.1 Some Background of Heart Disease
395(1)
17.1.2 The Blood Coagulation Cascade
395(1)
17.1.3 General Background About Serine Proteases
396(1)
17.1.4 Indirect Coagulation Inhibitors
397(1)
17.2 Thrombin
398(6)
17.2.1 General Structure and Active Site
398(1)
17.2.2 Exosite-I
398(2)
17.2.3 Exosite-II
400(1)
17.2.4 Discovery of Direct Thrombin Inhibitors
400(1)
17.2.5 Hirudin
400(1)
17.2.6 Hirudin-Derived Thrombin Inhibitors
400(1)
17.2.7 Thrombin Active Site Inhibitors
401(1)
17.2.8 Melagatran
402(1)
17.2.9 Dabigatran
402(1)
17.2.10 The Quest for Orally Available, Non-prodrug Direct Thrombin Inhibitors
402(2)
17.3 Factor Xa (FXa)
404(7)
17.3.1 Factor Xa Crystal Structure and Active Site
404(1)
17.3.2 Heparin-Binding Exosite
405(1)
17.3.3 Discovery of Direct FXa Inhibitors
405(1)
17.3.4 First-Generation FXa Inhibitors Coritaining Benzamidines
405(1)
17.3.4.1 DX-9065a
405(1)
17.3.4.2 Otamixaban
407(1)
17.3.5 Second-Generation FXa Inhibitors with Neutral S1 Substituents
407(1)
17.3.5.1 Reversed Binding Mode of Chlorobenzothiophene Substituents
407(1)
17.3.5.2 Apixaban
408(1)
17.3.5.3 Rivaroxaban
409(1)
17.3.5.4 The Secret Behind Chloro-aryl Binding in the S1 Pocket
409(1)
17.3.5.5 Dual Thrombin/FXa Inhibitors
410(1)
17.4 Factor VIIa (FVIIa)
411(3)
17.4.1 The FVIIa Active Site
412(1)
17.4.2 Exosites
412(1)
17.4.3 Discovery of Direct FVIIa Inhibitors
412(2)
17.5 Further Developments
414(1)
17.6 Factor IXa
414(1)
17.7 Factor XIa
415(1)
17.8 Impact of Structure-Based Drug Design
415(1)
References
416(7)
18 Epigenetic Proteins as Emerging Drug Targets
423(26)
P. Ann Boriack-Sjodin
18.1 Introduction
423(1)
18.2 Acetylation/Deacetylation
424(6)
18.2.1 Histone Deacetylases
425(1)
18.2.1.1 Metal Ion-Dependent HDACs
425(1)
18.2.1.2 Sirtuins
427(2)
18.2.2 Bromodomains
429(1)
18.2.3 Histone Acetyltransferases
430(1)
18.3 Methylation/Demethylation
430(10)
18.3.1 Protein Methyltransferases
431(1)
18.3.1.1 Inhibition via SAM Competitive Binding: DOT1L
432(1)
18.3.1.2 Inhibition via Substrate Competitive Binding: EHMT2
432(1)
18.3.1.3 Inhibition Through an Allosteric Mechanism: PRMT3
435(1)
18.3.1.4 Success Without Structure: EZH2
436(1)
18.3.2 Demethylases
436(1)
18.3.2.1 LSD Demethylases
437(1)
18.3.2.2 JmjC Demethylases
437(1)
18.3.2.3 Arginine Deiminases
438(1)
18.3.3 Methyl-lysine Reader Domains
438(1)
18.3.3.1 PHD Domains
438(1)
18.3.3.2 The "Royal Family"
438(1)
18.3.3.3 WD40 Repeat Domains
440(1)
18.4 Other Epigenetic Modifications
440(1)
18.5 The Future of Epigenetic Drug Discovery
440(1)
Acknowledgments
441(1)
References
441(8)
19 Impact of Recently Determined Crystallographic Structures of GPCRs on Drug Discovery
449(30)
Francesca Deflorian
Jonathan S. Mason
Andrea Bortolato
Benjamin G. Tehan
19.1 G Protein-Coupled Receptors as Pharmaceutical Targets
449(1)
19.2 Topology and Classes of GPCRs
449(1)
19.3 GPCR X-Ray Crystal Structures
450(1)
19.4 Class A GPCR Small Ligand Binding Sites and Druggability
451(4)
19.5 Class B GPCR X-Ray Crystal Structures
455(3)
19.6 Class C GPCRs and Allosteric Modulators
458(1)
19.7 GPCR Activation
459(2)
19.8 Structure-Based Approaches to GPCR Drug Discovery
461(12)
19.8.1 Virtual Screening
461(7)
19.8.2 Fragment-Based Drug Design
468(2)
19.8.3 Biophysical Mapping
470(1)
19.8.4 A Case History of Full SBDD for GPCRs: "High-End" Design
470(3)
19.9 Conclusion
473(1)
References
473(6)
20 Targeting Protein-Protein Interactions Perspective
479(24)
Chun-wa Chung
Michael M. Hann
20.1 Introduction
479(1)
20.2 Detection and Analysis of PPIs
479(3)
20.3 PPI Screening
482(1)
20.3.1 Screening Technologies
482(1)
20.3.2 Fragment-Based Screening Methods
482(1)
20.4 Examples
483(11)
20.4.1 Inhibitors of MDM2-p53: A Breakthrough in PPI Targeting
483(1)
20.4.1.1 Structure-Based Design of Spirooxindoles as MDM2 Inhibitors
484(1)
20.4.1.2 Dimer Stabilization: A Mechanism of Dual Inhibition of MDM2/X
485(1)
20.4.1.3 Other Opportunities for Inhibition
485(1)
20.4.2 Mimicry of Smac Peptide, IAP Antagonists
486(1)
20.4.3 Fragment-Based Approaches for BCL Antagonists
487(1)
20.4.4 Epigenetic Reader Proteins
487(1)
20.4.4.1 Bromodomains
487(1)
20.4.4.2 Methyl-lysine Reader Domains
490(2)
20.4.5 Competitive Antagonists: IL-2 Receptor
492(2)
20.5 Stapled Peptides
494(1)
20.6 Alternatives to Small-Molecule Orthosteric Inhibition
494(2)
20.6.1 Protein Degradation
494(1)
20.6.2 PPI Stabilizers
495(1)
20.7 Conclusion and Perspectives
496(1)
References
496(7)
21 Mass Spectrometry-Based Strategies for Therapeutic Antibodies Extensive Characterization and Optimization (OptimAbs)
503(18)
Amandine Boeuf
Francois Debaene
Daniel Ayoub
HelEne Diemer
Anthony Ehkirch
Elsa Wagner-Rousset
Alain Van Dorsselaer
Sarah Cianferani
Alain Beck
21.1 Introduction
503(2)
21.2 Intact mAb Analysis SOS
21.2.1 Denaturing MS
505(1)
21.2.2 Native MS
506(1)
21.2.3 Intact mAb Analyses of Hz6F4 Isotypes
506(1)
21.3 Middle-Up mAb Analysis
506(2)
21.4 Bottom-Up Peptide Mapping for Primary Structure Assessment
508(2)
21.5 Top-Down Approaches for mAb Sequencing
510(3)
21.5.1 Top-Down mAb Analysis
510(1)
21.5.2 Middle-Down mAb Analysis
510(3)
21.6 Hydrogen/Deuterium Exchange Mass Spectrometry
513(1)
21.7 Native MS and Ion Mobility-Mass Spectrometry (IM-MS) for the Characterization of mAb/Ag Binding Stoichiometry and of Protein Conformation
514(1)
21.8 From Optimized Antibodies (OptimAbs) to Optimized Antibody-Drug Conjugates (OptimADCs)
514(1)
21.9 Concluding Remarks
515(1)
Acknowledgments
515(1)
References
516(5)
Part IV Challenges and New Frontiers 521(128)
22 Integrating Evolution of Drug Resistance into Drug Discovery: Lessons from the Viral Proteases of HIV-1 and HCV
523(22)
Aysegul Ozen
Celia A. Schiffer
22.1 Evolution of Antiviral Drug Resistance
523(5)
22.1.1 Human Immunodeficiency Virus
523(1)
22.1.2 Structure and Function of HIV-1 Protease
523(1)
22.1.3 HIV-1 Protease Inhibitors as Antivirals
524(1)
22.1.4 Viral Resistance to HIV-1 Protease Inhibitors
524(4)
22.2 Substrate Envelope in Drug Design
528(2)
22.2.1 Substrate Envelope in HIV Protease
528(1)
22.2.2 Another Quickly Evolving Virus: Hepatitis C
528(1)
22.2.3 NS3/4A Protease as an Antiviral Target
528(2)
22.2.4 Generality of the Substrate Envelope Hypothesis
530(1)
22.3 Protein Dynamics Is Key to Molecular Recognition
530(2)
22.3.1 Change in Dynamics as a Drug Resistance Mechanism
531(1)
22.3.2 Protein Dynamics Is Often Neglected in Drug Design
531(1)
22.4 Robust Drug Design: Hitting Multiple Targets at a Time
532(4)
22.4.1 Drug Target's Function and Protein Dynamics
532(1)
22.4.2 Integrating Dynamics into Drug Discovery While Avoiding Resistance: Dynamic Substrate Envelope
533(3)
22.4.3 Predicting Substrate Coevolution Using the Dynamic Substrate Envelope
536(1)
22.5 Future Perspective: Integrating Evolution and Conformational Dynamics into Drug Design
536(1)
Acknowledgments
537(1)
References
537(8)
23 A Comprehensive Review on Mycobacterium tuberculosis Targets and Drug Development from a Structural Perspective
545(22)
Jean-Denis Pedelacq
Minh Chau Nguyen
Thomas C. Terwilliger
Lionel Mourey
23.1 Introduction
545(1)
23.2 Tuberculosis
545(3)
23.2.1 The Disease
545(1)
23.2.2 Epidemiologic Data and Treatment
545(1)
23.2.3 Current Problems and Risks: The Challenge of a Tuberculosis-Free World
546(2)
23.3 Mycobacterium tuberculosis
548(1)
23.3.1 Mycobacterium Species
548(1)
23.3.2 The Mycobacterium tuberculosis Genome and Proteome
548(1)
23.3.3 The Structural Proteome of Mycobacterium tuberculosis
548(1)
23.4 Tuberculosis Drug Discovery and Development
549(9)
23.4.1 Target Identification
549(1)
23.4.2 Current Drug Development Pipeline
550(1)
23.4.3 Structural Studies of Pertinent Enzyme-Drug Complexes
550(1)
23.4.3.1 Isoniazid and Ethionamide
550(1)
23.4.3.2 Pyrazinamide Activation Pathway and Target
554(1)
23.4.3.3 RNA Polymerase and Regulatory Proteins
554(1)
23.4.3.4 Fluoroquinolones Target DNA Gyrase
555(1)
23.4.3.5 Examples of TB Drugs in Development and Their Targets
557(1)
23.5 Conclusion and Perspectives
558(1)
References
559(8)
24 Using Crystal Structures of Drug-Metabolizing Enzymes in Mechanism-Based Modeling for Drug Design
567(20)
Hao Sun
Dennis Scott
24.1 Structure-Based Modeling of Cytochrome P450s
569(6)
24.1.1 CYP3A4
572(2)
24.1.2 CYP2C8, CYP2C9, and CYP2C19
574(1)
24.1.3 CYP2D6
574(1)
24.1.4 CYP1A2
575(1)
24.2 Other Phase I Drug-Metabolizing Enzymes
575(1)
24.3 Phase II Drug-Metabolizing Enzymes
576(1)
24.4 Interplay Between Metabolism and Inhibition
577(2)
24.5 Future Directions
579(2)
Acknowledgment
581(1)
References
581(6)
25 Intrinsically Disordered Proteins: Targets for the Future?
587(26)
Vladimir N. Uversky
25.1 Introduction
587(7)
25.1.1 Introducing Intrinsically Disordered Proteins
587(1)
25.1.2 Techniques for Structural Characterization of IDPs and IDPRs
588(4)
25.1.3 Abundance of IDPs and IDPRs and Their Biological Functions
592(1)
25.1.4 IDPs/IDPRs in Human Diseases
593(1)
25.2 IDPs as Novel Drug Targets
594(1)
25.2.1 Why IDPs? A Brief Overview
594(1)
25.2.2 Druggability of Ordered Proteins
594(1)
25.2.2.1 Major Categories of Protein-Directed Drugs
594(1)
25.3 Molecular Mechanisms of Drugs Targeting Ordered Proteins
595(1)
25.3.1 Targeting Active Site
595(1)
25.3.2 Targeting Protein-Protein Interaction Interfaces
595(1)
25.3.3 Drugs for IDPs and IDPRs
595(1)
25.4 Disorder-Based Rational Drug Design
596(1)
25.5 Direct Targeting of IDPs/IDPRs
597(2)
25.6 Targeting Functionally Misfolded IDPs: A Hypothesis
599(1)
25.7 Targeting Intrinsically Disordered Structural Ensembles: α-Synuclein as an Illustration
599(2)
25.8 Targeting Aggregating IDPs
601(1)
25.9 Conclusions
602(1)
Acknowledgments
603(1)
References
603(10)
26 Cryo-electron Microscopy as a Tool for Drug Discovery in the Context of Integrative Structural Biology
613(20)
Socha De Carlo
Herve-William Remigy
26.1 Introduction
613(1)
26.2 The Resolution Revolution
613(1)
26.3 What Is Cryo-EM?
614(1)
26.4 The Cryo-EM Single-Particle Analysis Workflow
614(10)
26.4.1 Biochemistry
614(1)
26.4.2 Screening the Conditions to Obtain an Optimal Sample
615(1)
26.4.2.1 Differential Scanning Fluorimetry and High-Resolution EM
616(1)
26.4.2.2 ProteoPlex
616(1)
26.4.3 Sample Vitrification
616(1)
26.4.4 High-Resolution Cryo-EM
617(1)
26.4.5 Data Collection
617(2)
26.4.6 Increasing the Image Contrast
619(1)
26.4.6.1 Choosing a Suitable Detector
620(1)
26.4.6.2 Phase Plates to Address Smaller Macromolecular Complexes
622(1)
26.4.6.3 Beam-Induced Motion Correction and Dose Optimization
622(1)
26.4.7 Three-Dimensional Reconstruction and Map Interpretation
622(2)
26.5 Selected Case Studies
624(3)
26.5.1 The Glutamate Receptor: A Membrane Protein
624(1)
26.5.2 Visualizing Ligands in High-Resolution Cryo-EM Maps of TRPV1
624(1)
26.5.3 Visualizing Large Complexes Without Symmetry: The Ribosome
625(1)
26.5.4 Visualizing Antigen-Antibody Complexes by Cryo-EM
626(1)
26.5.5 Cryo-EM and SBDD: Antimalarial Mefloquine Derivatives
626(1)
26.6 Summary and Conclusion
627(1)
References
627(6)
27 Application of Hard-X-Ray Free-Electron Lasers for Static and Dynamic Processes in Structural Biology
633(16)
Shiborn Basu
Petra Fromme
Raimund Fromme
27.1 Introduction: Overview of X-Ray Free-Electron Lasers
633(1)
27.2 Comparison with Conventional X-Ray Crystallography
634(2)
27.3 XFEL Structures: Successes Since 2009
636(6)
27.3.1 Photosystem I Structure at 8.5 A: Proof of Concept
636(1)
27.3.2 Lysozyme Structure at 1.9A: Proof of High Resolution
637(1)
27.3.3 Single-Virus-Particle Imaging: Mimivirus at 30 nm
637(1)
27.3.4 Cathepsin B Structure at 2.1 A: First Unknown Structural Insight and Use of In Vivo Grown Crystals
638(1)
27.3.5 Serotonin Receptor Structure at 2.8 A: Room-Temperature Conformation Different from the Cryogenic Structure Solved at Synchrotron
639(1)
27.3.6 Phycocyanin: A Model Protein to Compare Different Crystal Delivery Methods to Obtain High-Resolution Structures
640(1)
27.3.7 Photosystem I and Ferredoxin: First Proof of Principle for Time-Resolved Studies
640(1)
27.3.8 Photosystem II: Unraveling the Water Oxidation Process - An Attempt to Make a Molecular Movie
641(1)
27.4 Challenges in XFELs
642(2)
27.5 Future Outlook
644(1)
27.5.1 Comparison of Existing XFELs
644(1)
27.6 Conclusion
644(1)
Acknowledgments
645(1)
References
645(4)
Index 649
JEAN-PAUL RENAUD, PhD, is cofounder and President & Chief Scientific Officer at Urania Therapeutics (formerly RiboStruct), which focuses on rational drug design targeting the human ribosome. Previously, he was cofounder and Chief Scientific Officer at NovAliX and CNRS Research Director in the Structural Biology and Genomics Department at the Institute of Genetics and Molecular and Cellular Biology. Dr Renaud has over 30 years of research experience, along with 48 articles, 4 book chapters and 3 patents to his credit. He also initiated and is the Chairman and Scientific Organizer of the NovAliX Conferences "Biophysics in Drug Discovery".
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