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Target Discovery and Validation : Methods and Strategies for Drug Discovery.

By: Contributor(s): Material type: TextTextSeries: Methods and Principles in Medicinal Chemistry SeriesPublisher: Newark : John Wiley & Sons, Incorporated, 2020Copyright date: ©2020Edition: 1st edDescription: 1 online resource (398 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783527818259
Subject(s): Genre/Form: Additional physical formats: Print version:: Target Discovery and ValidationLOC classification:
  • QH307.2 .T374 2020
Online resources:
Contents:
Cover -- Title Page -- Copyright -- Contents -- Preface -- A Personal Foreword -- Chapter 1 Chemical Strategies for Evaluating New Drug Targets -- 1.1 Introduction -- 1.2 Use Cases and Case Studies for Chemogenomic Compounds and Chemical Probes -- 1.2.1 Chemogenomic Libraries -- 1.2.2 Inactive Control -- 1.2.3 Use of Biological Target Panels and Profiling -- 1.3 Development of Chemical Probes -- 1.3.1 From BIX01294 to EPZ035544: Development and Improvement of G9a/GLP Inhibitors -- 1.3.2 Development of BRD9 Inhibitors -- 1.4 Compound‐Based Target Evaluation with Patient‐Derived Cells -- 1.4.1 Compound‐Based Target Evaluation -- 1.4.2 Patient‐Derived Cell Assays -- 1.4.3 Target Evaluation Approach -- 1.4.4 Case Story: Inflammatory Bowel Disease (IBD) Tissue Platform -- 1.5 Summary and Outlook -- References -- Chapter 2 Affinity‐Based Chemoproteomics for Target Identification -- 2.1 Introduction -- 2.2 Small Molecule Phenotypic Mechanism of Action Elucidation -- 2.3 Quantitative High‐Resolution Mass Spectrometry as a Protein Detection Read‐Out -- 2.4 In‐Lysate Affinity‐Based Chemical Proteomics -- 2.4.1 Design of the Affinity Probe -- 2.4.2 General Experimental Pulldown Workflow -- 2.4.3 Limitations -- 2.5 In‐Cell Light‐Activated Affinity‐Based Chemoproteomics -- 2.5.1 Design of the Reactive Photoaffinity Probe (PAL Probe) -- 2.5.2 General Experimental Workflow -- 2.5.3 Limitations -- 2.6 Target Validation and Mode of Action -- 2.7 Concluding Remarks -- References -- Chapter 3 Activity‐Based Protein Profiling -- 3.1 Introduction -- 3.2 Activity‐Based Probe (ABP) and Affinity‐Based Probe (AfBP) Design -- 3.2.1 Warheads (Reactive Groups) -- 3.2.1.1 Electrophilic Warheads -- 3.2.1.2 Photocrosslinking Warheads -- 3.2.2 Reporter Tags -- 3.2.3 Linkers -- 3.2.4 Bioorthogonal Ligation Chemistry -- 3.2.4.1 Staudinger Ligation.
3.2.4.2 Copper(I)‐Catalysed Azide-Alkyne Cycloaddition (CuAAC) -- 3.2.4.3 Strain‐Promoted Azide-Alkyne Cycloaddition (SPAAC) -- 3.2.4.4 Diels-Alder Reaction -- 3.3 Chemical Proteomic Workflow -- 3.3.1 Quantitative Proteomics by Mass Spectrometry -- 3.3.1.1 Label‐Free Quantification (LFQ) -- 3.3.1.2 Chemical Labelling Quantification -- 3.3.1.3 Metabolic Labelling Quantification -- 3.4 ABPP Applications and Case Studies -- 3.4.1 Case Study 1: Activity‐Based Protein Profiling as a Robust Method for Enzyme Identification and Screening in Extremophilic Archaea -- 3.4.2 Case Study 2: Failed Clinical Trial of a Fatty Acid Amide Hydrolase (FAAH) Inhibitor -- 3.4.3 Case Study 3: Target Identification of Small Molecule Inhibitors -- 3.4.3.1 New Target Profiling for Sulforaphane -- 3.4.3.2 Profiling USP Inhibitors in Human Cell Lines as Potential Therapeutic Molecules -- 3.4.4 Case Study 4: Fragment‐Based Ligand Discovery Aided by Photoaffinity Labelling -- 3.4.5 Case Study 5: Quenched Fluorescent Activity‐Based Probe (qABP) Design and Application in Protein Localization -- 3.5 Summary -- References -- Chapter 4 Kinobeads: A Chemical Proteomic Approach for Kinase Inhibitor Selectivity Profiling and Target Discovery -- 4.1 Kinase Inhibitor Target Deconvolution Using Chemical Proteomics -- 4.1.1 Polypharmacology of Small Molecule Kinase Inhibitors -- 4.1.2 Chemoproteomic Profiling of Kinase Inhibitors -- 4.1.3 Tips and Tricks Regarding Chemoproteomic Assay Development -- 4.2 Detailed Kinobeads Protocol -- 4.2.1 Cell or Tissue Lysate -- 4.2.2 Affinity Matrices -- 4.2.3 Kinobeads Competition Assay -- 4.2.4 Mass Spectrometry -- 4.2.5 Peptide and Protein Identification and Quantification -- 4.2.6 Data Analysis -- 4.3 Application Examples for Kinobeads -- 4.3.1 Expanding the Target Space of Kinobeads.
4.3.2 Target Space Deconvolution of Small Molecule Kinase Inhibitors -- 4.3.3 Opportunities Arising from Inhibitor Polypharmacology: Drug Repositioning -- 4.3.4 Chemoproteomic‐Guided Medicinal Chemistry -- 4.4 Kinobeads, Inhibitors, and Drug Discovery: Where Are We Heading? -- 4.4.1 What Is a Good Drug? -- 4.4.2 How Can We Discover New Drugs in the Future? -- 4.4.3 The Yin and Yang of Chemoproteomic‐Guided Drug Discovery -- Acknowledgments -- References -- Chapter 5 Label‐Free Techniques for Target Discovery and Validation -- 5.1 Introduction -- 5.2 CETSA: How It All Began -- 5.3 The CETSA Formats -- 5.3.1 CETSA Classics -- 5.3.2 CETSA HT -- 5.3.3 CETSA MS -- 5.4 Target Discovery -- 5.4.1 Generation of Active Hit Molecules -- 5.4.2 Tool Generation (Small Screens to Identify Tool Compounds) -- 5.4.3 Target Classes That Are In and Out of Scope and Difficult Targets -- 5.4.4 Focused or Iterative Library Screening -- 5.4.5 Fragment Library Screening -- 5.4.6 Hit Confirmation -- 5.4.7 Phenotypic Hit Deconvolution to Discover Targets -- 5.5 Target Validation -- 5.5.1 Binding Modes -- 5.5.2 Selectivity, Specificity, and Safety -- 5.5.3 Translation Bench to Bedside (via Animals) -- 5.6 Conclusion -- References -- Chapter 6 Reverse Translation to Support Efficient Drug Target Selection and Stratified Medicine -- 6.1 Introduction: the Challenge -- 6.2 Genetics to Date in Drug Discovery -- 6.3 Genetic Strategies for Target Discovery -- 6.3.1 GWAS -- 6.3.2 Rare Disease Genetics -- 6.3.2.1 Rare Mutation → Rare Disease Drug Discovery -- 6.3.2.2 Rare Mutation → Common Disease Drug Discovery -- 6.3.3 Somatic Mutations -- 6.3.4 Analytical Approaches -- 6.4 Functional Validation -- 6.4.1 Prioritization of Putative Mutations -- 6.4.2 Determining Functional Consequence of Mutation -- 6.4.2.1 Publicly Available Data -- 6.4.2.2 Systems Biology.
6.4.2.3 Model Systems: 'The Tissue Is the Issue' -- 6.4.3 Druggability: From Validation of a Gene to a Druggable Target -- 6.5 Forward‐Looking Perspectives -- 6.5.1 Molecular Taxonomy of Disease -- 6.5.2 Precision Medicine -- 6.5.3 Data Integration -- 6.6 Conclusion -- References -- Chapter 7 Elucidating Target Biology and Drug Mechanism of Action Across Human Cell‐Based Model Systems -- 7.1 Introduction -- 7.2 Advances in Human Cell‐Based Model Development -- 7.2.1 Next‐Generation Sequencing (NGS) -- 7.2.2 CRISPR Genome Editing -- 7.2.3 Induced Pluripotent Stem Cell Biology -- 7.2.4 3D Cell and Organoid Models -- 7.2.5 Microfluidic and Organ‐on‐a‐Chip Devices -- 7.2.6 In Vivo Imaging -- 7.2.7 High‐Content Imaging -- 7.3 Multiparametric High‐Content Phenotypic Profiling of Target Biology and Drug Mechanism of Action -- 7.3.1 High‐Content Cell Painting in Functional Genomics -- 7.3.2 Integration of Multiparametric High‐Content Imaging with Chemoinformatics -- 7.3.3 Guiding Chemical Design and Target Selectivity from Multiparametric High‐Content Analysis -- 7.4 Target‐Annotated Compound Libraries for Phenotypic Screening and MOA Determination -- 7.5 Quantitative Pathway Profiling Across New Model Systems -- 7.5.1 Pathway Profiling at the Gene Transcription Level -- 7.5.2 Dynamic Post‐Translational Pathway Profiling Across Dose-Response and Time‐Series Studies -- 7.6 Conclusions -- References -- Chapter 8 Cell Biology Methods in Target Validation -- 8.1 Introduction -- 8.2 Biomarkers -- 8.2.1 Direct Target Engagement Biomarkers -- 8.2.2 Indirect Target Engagement Biomarkers and Pathway Biomarkers -- 8.2.3 Response Biomarkers -- 8.2.4 Correlation of Biomarkers -- 8.3 Direct Evidence to Show That Modulation of a Target Leads to a Cellular Response.
8.4 Direct Evidence That Target Modulation Is Responsible for Cellular Responses by Mutations Conferring Sensitivity to Existing Drugs -- 8.4.1 The 'Bump‐and‐Hole' Approach to Generate Sensitivity to Small Molecule Inhibitors -- 8.4.2 Chemogenomic Approaches for Inducible Degradation of Protein Targets -- 8.5 Resistance Conferring Mutations -- References -- Chapter 9 Genetic Manipulation/Modulation for Target Discovery and Validation -- 9.1 Introduction -- 9.2 Overview of the Development of Leading Genetic Manipulation Technologies -- 9.2.1 RNAi, ZFNs, and TALENs -- 9.2.2 Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) -- 9.3 Considerations for Designing and Interpreting CRISPR Experiments -- 9.3.1 Methodological Considerations for Genetic Manipulation by the CRISPR/Cas Technology -- 9.3.2 Choosing a Cellular Model: Biological and Genomic Aspects -- 9.3.3 gRNA Design -- 9.3.3.1 Identification of Target Locations -- 9.3.3.2 Selection of Spacer Sequences -- 9.3.3.3 Predictive Tools -- 9.3.4 Successful Application of the CRISPR/Cas Technology -- 9.3.4.1 Delivering CRISPR Reagents to Target Cells -- 9.3.4.2 Check for Anticipated Knockout/Knock‐In -- 9.4 Further Developments of the CRISPR/Cas Technology Facilitates Additional Modes of Genetic Perturbation -- 9.4.1 CRISPRi -- 9.4.2 CRISPRa -- 9.4.3 Base Editing -- 9.5 The CRISPR/Cas Technology in Target Discovery and Validation -- 9.5.1 CRISPR/Cas Technology for Early Target Validation -- 9.5.2 CRISPR Screens and Use for Target Discovery -- 9.5.3 CRISPR Screens: General Principle and Considerations -- 9.5.4 Selected Examples of Target Discovery Using CRISPR Screens to Illustrate the Breadth of Applications -- 9.6 Application of CRISPR Genome Editing in Immunology Studies -- 9.7 Concluding Remarks -- References -- Chapter 10 Computational Approaches for Target Inference.
10.1 Introduction.
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Cover -- Title Page -- Copyright -- Contents -- Preface -- A Personal Foreword -- Chapter 1 Chemical Strategies for Evaluating New Drug Targets -- 1.1 Introduction -- 1.2 Use Cases and Case Studies for Chemogenomic Compounds and Chemical Probes -- 1.2.1 Chemogenomic Libraries -- 1.2.2 Inactive Control -- 1.2.3 Use of Biological Target Panels and Profiling -- 1.3 Development of Chemical Probes -- 1.3.1 From BIX01294 to EPZ035544: Development and Improvement of G9a/GLP Inhibitors -- 1.3.2 Development of BRD9 Inhibitors -- 1.4 Compound‐Based Target Evaluation with Patient‐Derived Cells -- 1.4.1 Compound‐Based Target Evaluation -- 1.4.2 Patient‐Derived Cell Assays -- 1.4.3 Target Evaluation Approach -- 1.4.4 Case Story: Inflammatory Bowel Disease (IBD) Tissue Platform -- 1.5 Summary and Outlook -- References -- Chapter 2 Affinity‐Based Chemoproteomics for Target Identification -- 2.1 Introduction -- 2.2 Small Molecule Phenotypic Mechanism of Action Elucidation -- 2.3 Quantitative High‐Resolution Mass Spectrometry as a Protein Detection Read‐Out -- 2.4 In‐Lysate Affinity‐Based Chemical Proteomics -- 2.4.1 Design of the Affinity Probe -- 2.4.2 General Experimental Pulldown Workflow -- 2.4.3 Limitations -- 2.5 In‐Cell Light‐Activated Affinity‐Based Chemoproteomics -- 2.5.1 Design of the Reactive Photoaffinity Probe (PAL Probe) -- 2.5.2 General Experimental Workflow -- 2.5.3 Limitations -- 2.6 Target Validation and Mode of Action -- 2.7 Concluding Remarks -- References -- Chapter 3 Activity‐Based Protein Profiling -- 3.1 Introduction -- 3.2 Activity‐Based Probe (ABP) and Affinity‐Based Probe (AfBP) Design -- 3.2.1 Warheads (Reactive Groups) -- 3.2.1.1 Electrophilic Warheads -- 3.2.1.2 Photocrosslinking Warheads -- 3.2.2 Reporter Tags -- 3.2.3 Linkers -- 3.2.4 Bioorthogonal Ligation Chemistry -- 3.2.4.1 Staudinger Ligation.

3.2.4.2 Copper(I)‐Catalysed Azide-Alkyne Cycloaddition (CuAAC) -- 3.2.4.3 Strain‐Promoted Azide-Alkyne Cycloaddition (SPAAC) -- 3.2.4.4 Diels-Alder Reaction -- 3.3 Chemical Proteomic Workflow -- 3.3.1 Quantitative Proteomics by Mass Spectrometry -- 3.3.1.1 Label‐Free Quantification (LFQ) -- 3.3.1.2 Chemical Labelling Quantification -- 3.3.1.3 Metabolic Labelling Quantification -- 3.4 ABPP Applications and Case Studies -- 3.4.1 Case Study 1: Activity‐Based Protein Profiling as a Robust Method for Enzyme Identification and Screening in Extremophilic Archaea -- 3.4.2 Case Study 2: Failed Clinical Trial of a Fatty Acid Amide Hydrolase (FAAH) Inhibitor -- 3.4.3 Case Study 3: Target Identification of Small Molecule Inhibitors -- 3.4.3.1 New Target Profiling for Sulforaphane -- 3.4.3.2 Profiling USP Inhibitors in Human Cell Lines as Potential Therapeutic Molecules -- 3.4.4 Case Study 4: Fragment‐Based Ligand Discovery Aided by Photoaffinity Labelling -- 3.4.5 Case Study 5: Quenched Fluorescent Activity‐Based Probe (qABP) Design and Application in Protein Localization -- 3.5 Summary -- References -- Chapter 4 Kinobeads: A Chemical Proteomic Approach for Kinase Inhibitor Selectivity Profiling and Target Discovery -- 4.1 Kinase Inhibitor Target Deconvolution Using Chemical Proteomics -- 4.1.1 Polypharmacology of Small Molecule Kinase Inhibitors -- 4.1.2 Chemoproteomic Profiling of Kinase Inhibitors -- 4.1.3 Tips and Tricks Regarding Chemoproteomic Assay Development -- 4.2 Detailed Kinobeads Protocol -- 4.2.1 Cell or Tissue Lysate -- 4.2.2 Affinity Matrices -- 4.2.3 Kinobeads Competition Assay -- 4.2.4 Mass Spectrometry -- 4.2.5 Peptide and Protein Identification and Quantification -- 4.2.6 Data Analysis -- 4.3 Application Examples for Kinobeads -- 4.3.1 Expanding the Target Space of Kinobeads.

4.3.2 Target Space Deconvolution of Small Molecule Kinase Inhibitors -- 4.3.3 Opportunities Arising from Inhibitor Polypharmacology: Drug Repositioning -- 4.3.4 Chemoproteomic‐Guided Medicinal Chemistry -- 4.4 Kinobeads, Inhibitors, and Drug Discovery: Where Are We Heading? -- 4.4.1 What Is a Good Drug? -- 4.4.2 How Can We Discover New Drugs in the Future? -- 4.4.3 The Yin and Yang of Chemoproteomic‐Guided Drug Discovery -- Acknowledgments -- References -- Chapter 5 Label‐Free Techniques for Target Discovery and Validation -- 5.1 Introduction -- 5.2 CETSA: How It All Began -- 5.3 The CETSA Formats -- 5.3.1 CETSA Classics -- 5.3.2 CETSA HT -- 5.3.3 CETSA MS -- 5.4 Target Discovery -- 5.4.1 Generation of Active Hit Molecules -- 5.4.2 Tool Generation (Small Screens to Identify Tool Compounds) -- 5.4.3 Target Classes That Are In and Out of Scope and Difficult Targets -- 5.4.4 Focused or Iterative Library Screening -- 5.4.5 Fragment Library Screening -- 5.4.6 Hit Confirmation -- 5.4.7 Phenotypic Hit Deconvolution to Discover Targets -- 5.5 Target Validation -- 5.5.1 Binding Modes -- 5.5.2 Selectivity, Specificity, and Safety -- 5.5.3 Translation Bench to Bedside (via Animals) -- 5.6 Conclusion -- References -- Chapter 6 Reverse Translation to Support Efficient Drug Target Selection and Stratified Medicine -- 6.1 Introduction: the Challenge -- 6.2 Genetics to Date in Drug Discovery -- 6.3 Genetic Strategies for Target Discovery -- 6.3.1 GWAS -- 6.3.2 Rare Disease Genetics -- 6.3.2.1 Rare Mutation → Rare Disease Drug Discovery -- 6.3.2.2 Rare Mutation → Common Disease Drug Discovery -- 6.3.3 Somatic Mutations -- 6.3.4 Analytical Approaches -- 6.4 Functional Validation -- 6.4.1 Prioritization of Putative Mutations -- 6.4.2 Determining Functional Consequence of Mutation -- 6.4.2.1 Publicly Available Data -- 6.4.2.2 Systems Biology.

6.4.2.3 Model Systems: 'The Tissue Is the Issue' -- 6.4.3 Druggability: From Validation of a Gene to a Druggable Target -- 6.5 Forward‐Looking Perspectives -- 6.5.1 Molecular Taxonomy of Disease -- 6.5.2 Precision Medicine -- 6.5.3 Data Integration -- 6.6 Conclusion -- References -- Chapter 7 Elucidating Target Biology and Drug Mechanism of Action Across Human Cell‐Based Model Systems -- 7.1 Introduction -- 7.2 Advances in Human Cell‐Based Model Development -- 7.2.1 Next‐Generation Sequencing (NGS) -- 7.2.2 CRISPR Genome Editing -- 7.2.3 Induced Pluripotent Stem Cell Biology -- 7.2.4 3D Cell and Organoid Models -- 7.2.5 Microfluidic and Organ‐on‐a‐Chip Devices -- 7.2.6 In Vivo Imaging -- 7.2.7 High‐Content Imaging -- 7.3 Multiparametric High‐Content Phenotypic Profiling of Target Biology and Drug Mechanism of Action -- 7.3.1 High‐Content Cell Painting in Functional Genomics -- 7.3.2 Integration of Multiparametric High‐Content Imaging with Chemoinformatics -- 7.3.3 Guiding Chemical Design and Target Selectivity from Multiparametric High‐Content Analysis -- 7.4 Target‐Annotated Compound Libraries for Phenotypic Screening and MOA Determination -- 7.5 Quantitative Pathway Profiling Across New Model Systems -- 7.5.1 Pathway Profiling at the Gene Transcription Level -- 7.5.2 Dynamic Post‐Translational Pathway Profiling Across Dose-Response and Time‐Series Studies -- 7.6 Conclusions -- References -- Chapter 8 Cell Biology Methods in Target Validation -- 8.1 Introduction -- 8.2 Biomarkers -- 8.2.1 Direct Target Engagement Biomarkers -- 8.2.2 Indirect Target Engagement Biomarkers and Pathway Biomarkers -- 8.2.3 Response Biomarkers -- 8.2.4 Correlation of Biomarkers -- 8.3 Direct Evidence to Show That Modulation of a Target Leads to a Cellular Response.

8.4 Direct Evidence That Target Modulation Is Responsible for Cellular Responses by Mutations Conferring Sensitivity to Existing Drugs -- 8.4.1 The 'Bump‐and‐Hole' Approach to Generate Sensitivity to Small Molecule Inhibitors -- 8.4.2 Chemogenomic Approaches for Inducible Degradation of Protein Targets -- 8.5 Resistance Conferring Mutations -- References -- Chapter 9 Genetic Manipulation/Modulation for Target Discovery and Validation -- 9.1 Introduction -- 9.2 Overview of the Development of Leading Genetic Manipulation Technologies -- 9.2.1 RNAi, ZFNs, and TALENs -- 9.2.2 Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) -- 9.3 Considerations for Designing and Interpreting CRISPR Experiments -- 9.3.1 Methodological Considerations for Genetic Manipulation by the CRISPR/Cas Technology -- 9.3.2 Choosing a Cellular Model: Biological and Genomic Aspects -- 9.3.3 gRNA Design -- 9.3.3.1 Identification of Target Locations -- 9.3.3.2 Selection of Spacer Sequences -- 9.3.3.3 Predictive Tools -- 9.3.4 Successful Application of the CRISPR/Cas Technology -- 9.3.4.1 Delivering CRISPR Reagents to Target Cells -- 9.3.4.2 Check for Anticipated Knockout/Knock‐In -- 9.4 Further Developments of the CRISPR/Cas Technology Facilitates Additional Modes of Genetic Perturbation -- 9.4.1 CRISPRi -- 9.4.2 CRISPRa -- 9.4.3 Base Editing -- 9.5 The CRISPR/Cas Technology in Target Discovery and Validation -- 9.5.1 CRISPR/Cas Technology for Early Target Validation -- 9.5.2 CRISPR Screens and Use for Target Discovery -- 9.5.3 CRISPR Screens: General Principle and Considerations -- 9.5.4 Selected Examples of Target Discovery Using CRISPR Screens to Illustrate the Breadth of Applications -- 9.6 Application of CRISPR Genome Editing in Immunology Studies -- 9.7 Concluding Remarks -- References -- Chapter 10 Computational Approaches for Target Inference.

10.1 Introduction.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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