Protein Homeostasis in Drug Discovery E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Protein Homeostasis in Drug Discovery Comprehensive resource on all aspects of protein homeostasis, covering both historical perspectives and emerging technologies that are revolutionizing the field Protein Homeostasis in Drug Discovery highlights drug discovery and development efforts targeting protein homeostasis and considers the emerging appreciation that a protein's activity may not be the only factor to consider when developing therapeutic agents. The chapters cover various aspects of protein homeostasis such as cellular localization, abundance, interactions, and more. Moreover, the text contains up-to-date information regarding targeted protein degradation, an emerging drug discovery modality. Readers interested in targeting different regulatory events that control protein homeostasis or modulating protein abundance will find this book an excellent resource. Furthermore, those interested in the link between biological function and regulating protein levels in living organisms, especially in the context of drug discovery, will learn from numerous examples discussed in this book. In Protein Homeostasis in Drug Discovery, readers can expect to find information on: * Protein folding, quality control, pharmacology, and drug targeting processes * Recent advances in our understanding of protein homeostasis, covering emerging technologies and opportunities for therapeutic intervention * Targeted protein degradation (TPD) and strategies such as PROTACs and molecular glues, including a chapter on TPD as an antiviral drug discovery strategy * Drug discovery and development efforts aimed at correcting, stabilizing, and rescuing proteins, with examples included * Advantages and key shortcomings of both phenotypic and target-based traditional drug discovery methods Collectively, Protein Homeostasis in Drug Discovery offers the reader an opportunity to learn more about the importance of considering and targeting protein homeostasis. The text is a must-read resource for academics, professionals in the pharmaceutical industry, and advanced students in various science-related fields.
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Table of Contents
Cover
Title Page
Copyright Page
List of Contributors
Preface
Section I: Protein Folding and Quality Control in Drug Discovery
1 Epichaperomes as a Gateway to Understanding, Diagnosing, and Treating Disease Through Rebalancing Protein–Protein Interaction Networks
1.1 Introduction
1.2 Epichaperomes Explored Through Chemical Biology
1.3 Engineering Interactomes for Therapeutic Vulnerability Through Epichaperomes
1.4 Epichaperome Disruptors as Novel Therapeutics
1.5 Labeled Epichaperome Probes as Diagnostics
1.6 Summary and Outlook
Acknowledgements
Author Contribution
Conflict of Interest
References
2 Stability of Steroid Hormone Receptors
2.1 Introduction
2.2 Steroid Hormone Receptor Chaperoning and Quality Control
2.3 Small Molecule‐Induced Degradation of Steroid Hormone Receptors
2.4 Summary and Outlook
References
3 Pharmacological Chaperones
3.1 Introduction
3.2 Short History of Small Chaperones: From Chemical to Pharmacological Chaperones
3.3 Pharmacological Chaperones as Potential Treatments for GPCR‐Linked Diseases
3.4 What Have We Learned?
3.5 Conclusion
References
Section II: Protein Degradation and Clearance as Drug Targeting Opportunities
4 Exploiting the Proteasome for Disease Treatment
4.1 Introduction
4.2 The Ubiquitin–Proteasome Pathway
4.3 The Many Forms of the Proteasome and its Components
4.4 Architecture and Motions of the 26S Proteasome
4.5 Proteasome‐Associated Factors
4.6 Future Perspectives
Acknowledgment
References
5 Targeting the Ubiquitination Cascade for Drug Discovery
5.1 Introduction
5.2 Inhibitors Targeting E1 Activating Enzymes
5.3 Inhibitors Targeting E2 Conjugating Enzymes
5.4 Inhibitors Targeting E3 Ligases
5.5 Novel Surfaces of E2 and E3 Enzymes for Targeted Inhibition
5.6 Conclusion and Future Outlook
References
6 Understanding, Targeting, and Hijacking Autophagy
6.1 Introduction
6.2 Targeting Autophagy
6.3 Hijacking Autophagy
6.4 Conclusions and Outlook
References
7 Deubiquitinating Enzymes
7.1 Introduction
7.2 DUB Specificity and Regulation
7.3 DUBs in Disease
7.4 Conclusions and Future Directions
References
Section III: Redirecting Protein Degradation Process for Drug Development
8 History of IMiDs and Protein Degradation as a Pharmacological Modality
8.1 Introduction
8.2 Early Studies on Thalidomide
8.3 Early Studies on IMiDs
8.4 Discovery of Cereblon (CRBN) as the Primary Target of Thalidomide
8.5 Identification of CRBN Therapeutic Neosubstrates
8.6 Thalidomide Teratogenicity Associated with CRBN
8.7 Structural Understanding of CRL4
CRBN
and IMiDs
8.8 Species Specificity of IMiDs
8.9 The C2‐H2 ZF Motif is a Structural Degron of Neosubstrates
8.10 Molecular Mechanisms Regulating CRL4
CRBN
Activity
8.11 CELMoDs: A New Generation of Thalidomide Derivatives
8.12 Protein Degradation as a Novel Pharmacological Modality
8.13 Concluding Remarks
References
9 PROTAC Degraders
9.1 Introduction
9.2 Mechanism of PROTACs
9.3 Overview of Existing E3 Ligases Used in PROTAC Development
9.4 Toward the Expansion of the E3 Ligase Toolbox
9.5 Recent Advances in the PROTAC Field
9.6 Future Challenges and Outlook
References
10 Biochemical Principles of Targeted Protein Degradation
10.1 The Mechanism of Targeted Protein Degradation
10.2 Utilization of the Ubiquitin–Proteasome System
10.3 Design and Evaluation of Degradation Activating Compounds
10.4 Validation
10.5 Kinetic Considerations in TPD
10.6 Selectivity
10.7 TPD and the Biology of Protein Homeostasis
10.8 Conclusions and Future Directions
References
11 Pharmacology of PROTAC Degrader Molecules
11.1 Introduction
11.2 Optimizing Pharmacology
11.3 In vitro Optimization of PROTAC ADME Properties
11.4 The Importance of Understanding In Vivo PROTAC Metabolism
11.5 Make Sure Your PROTAC Structure is Optimized
11.6 Case Studies of In Vivo PROTACs
11.7 Build a Pharmacokinetic/Pharmacodynamic (PK/PD) Model
11.8 Conclusions
Acknowledgments
References
Section IV: Emerging Technologies and Future Opportunities
12 Proximity‐Inducing Bifunctional Molecules Beyond PROTACs
12.1 Introduction
12.2 Molecules to Induce Degradation
12.3 Molecules that Induce Post‐translational Modifications Beyond Ubiquitination
12.4 Design Principles of Proximity‐Inducing Bifunctional Small Molecules
12.5 Conclusions and Future Directions
References
13 Strategies for Tag‐Based Protein Control
13.1 Introduction
13.2 Monovalent Stabilizing Approaches
13.3 Monovalent Destabilizing Approaches
13.4 Bifunctional Approaches
13.5 Biologicals
13.6 Summary and Outlook
Acknowledgments
Declaration of Interests
References
14 Targeted Protein Degradation in Antiviral Drug Discovery
14.1 Introduction
14.2 Key Factors Impacting Targeted Viral Protein Degradation
14.3 Viral Protein Homeostasis
14.4 Paths for Viral Degraders Design
14.5 Antiviral Degrader Characterization and Validation
14.6 Advantages of Antiviral Degraders Over Conventional Inhibitors
Acknowledgments
References
15 Beyond Inhibition
15.1 Introducing Ligand‐Based Pharmacological Exploration
15.2 Case Studies
15.3 Conclusions
Acknowledgments
Conflicts of Interest
References
Index
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Endogenous hormones of each SHR.
Table 2.2 Reported half‐life values for both bound and unbound SHRs.
Chapter 3
Table 3.1 List of pharmacological chaperones tested for GPCR.
Chapter 4
Table 4.1 Inhibitors of the ubiquitin–proteasome pathway.
Chapter 5
Table 5.1 List of chemical compounds described in this chapter.
Chapter 6
Table 6.1 Several compounds targeting autophagy.
Chapter 9
Table 9.1 Comparison of different therapeutic agents.
Table 9.2 Emerging TPD technologies beyond PROTACs.
List of Illustrations
Chapter 1
Figure 1.1 Chemical structure of epichaperome chemical probes ranging from e...
Figure 1.2 (a) Stressors associated with disease remodel interactomes throug...
Figure 1.3 Schematic of epichaperomics, an affinity purification‐based chemo...
Figure 1.4 Schematic showing the biochemical and functional mechanism for th...
Figure 1.5 (a) Mechanism for the selective binding of epichaperome probes to...
Chapter 2
Figure 2.1 (a) General schematic of the domain architecture of steroid hormo...
Figure 2.2 Proteostasis of SHRs is mediated by chaperones and the ubiquitin–...
Figure 2.3 Structure of selective estrogen receptor degraders. The portion o...
Figure 2.4 Schematic showing the differences in mechanism between the differ...
Figure 2.5 (a) Structure of the ERa‐LBD with the key helices labeled and the...
Figure 2.6 (a) Detailed map of androgen receptor indicating key binding regi...
Chapter 3
Figure 3.1 Thermodynamic stability of native and misfolded states of protein...
Figure 3.2 Overview of the quality control systems in the biosynthetic and s...
Figure 3.3 Chemical molecules as strategies to increase protein expression....
Figure 3.4 Ligand binding site comparison of GnRHR, V2R, and MC4R. Extracell...
Chapter 4
Figure 4.1 Architecture of the 20S core particle (CP). (a) Cartoon diagrammi...
Figure 4.2 Specificity of inhibitors for immunoproteasome (iP) and constitut...
Figure 4.3 Cryo‐EM structure of human 26S proteasome with modeling of Rpn13 ...
Figure 4.4 Structures of proteasome substrate receptors with shuttle factors...
Chapter 5
Figure 5.1 The ubiquitination process and targets of small‐molecule inhibito...
Figure 5.2 Chemical structures of small‐molecule inhibitors targeting E1 enz...
Figure 5.3 Chemical structures of small‐molecule inhibitors targeting E2 enz...
Figure 5.4 Chemical structures of small‐molecule inhibitors targeting E3 enz...
Figure 5.5 Chemical structures of small‐molecule inhibitors targeting E3 enz...
Figure 5.6 Targeted modulation of E2 conjugating enzymes and E3 ligases by u...
Chapter 6
Figure 6.1 Three kinds of autophagy: macroautophagy, microautophagy, and cha...
Figure 6.2 Targeting autophagy. Precisely regulating of autophagy is an extr...
Figure 6.3 AUTACs utilize a targeting ligand and an S‐guanylation tag to ind...
Chapter 7
Figure 7.1 DUB phylogenetic tree and timeline of discoveries. (a) There are ...
Figure 7.2 DUB specificity and regulation. (a) Ubiquitin can be attached ont...
Figure 7.3 DUBs in disease. DUB activating and loss‐of‐function mutations ar...
Figure 7.4 DUB inhibitor characterization assays. There is a suite of useful...
Chapter 8
Figure 8.1 The structures of thalidomide, IMiDs, and other CRBN‐binding comp...
Figure 8.2 IMiD‐induced protein degradation of CRL4
CRBN
. When an IMiD binds ...
Figure 8.3 The 3D structures of CRBN, DDB1, GSPT1, and CC‐885 (PDB: 5HXB). (...
Chapter 9
Figure 9.1 Schematic overview of the mechanism of action of a PROTAC.
Figure 9.2 Representative PROTAC structures for the most studied E3 ligases....
Figure 9.3 The “Hook effect.”
Chapter 10
Figure 10.1 Catalytic cycle of a degrader. The mechanism of action for TPD is...
Figure 10.2 Different flavors of degrader molecules. While all degraders faci...
Figure 10.3 In vitro assays used for degrader characterization. (a) Fluoresce...
Figure 10.4 Protein degradation is time dependent, and longer incubation time...
Figure 10.5 Simulated thermodynamically and kinetically driven degradation un...
Figure 10.6 Targeted protein degradation provides additional routes for selec...
Chapter 11
Figure 11.1 (a) Chemical structures of commonly utilized E3 ligase binders. ...
Figure 11.2 Comparison of PROTAC solubility in pH7.4 buffer versus FaSSIF an...
Figure 11.3 Plot of mouse bioavailability plotted against (a) experimental p...
Figure 11.4 Unbound plasma concentration vs time profiles for the PROTAC AZ6...
Figure 11.5 Selected examples of PROTACs that have been dosed in vivo or sho...
Figure 11.6 Selected examples of PROTACs that have been optimized for in viv...
Figure 11.7 A basic binding model for PROTACs.
Figure 11.8 A pharmacological model describing binding kinetics, endogenous ...
Figure 11.9 Sensitivity of degradation of a generic target by a PROTAC to ch...
Figure 11.10 Dose–response with time for a representative PROTAC (left); deg...
Figure 11.11 In vitro maximum degradation of Target T by PROTAC X in differe...
Figure 11.12 Degradation of Target T by PROTAC X in vivo at 20 mg kg
−1
Chapter 12
Figure 12.1 A graphical summary of the recently developed bifunctional molec...
Figure 12.2 Post‐translational modifications (PTMs) performed by enzymes. Fr...
Figure 12.3 Design principles for bifunctional molecules. (a) Ligand identif...
Chapter 13
Figure 13.1 Summary of the tag‐based TPD approaches discussed in this chapte...
Chapter 14
Figure 14.1 Reported antiviral degraders. (a) Peptide‐based PROTAC designed ...
Figure 14.2 Summary of interactions that affect viral protein abundance, loc...
Figure 14.3 Steps of antiviral degrader validation. Stage 1 of validation is...
Chapter 15
Figure 15.1 Ligand‐based pharmacological exploration. (a) Differences betwee...
Figure 15.2 Crystal structure of the CDK12/cyclin K/DDB1/CR8 complex (PDB 6T...
Figure 15.3 (a) Structures of the BCL6 inhibitor BI‐3812 and degrader BI‐380...
Guide
Cover Page
Title Page
Copyright Page
List of Contributors
Preface
Table of Contents
Begin Reading
Index
Wiley End User License Agreement
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Protein Homeostasis in Drug Discovery
A Chemical Biology Perspective
Edited by
Milka Kostic
Department of Cancer Biology, Dana‐Farber Cancer Institute, Boston, MA, USA
and
Lyn H. Jones
Center for Protein Degradation, Dana‐Farber Cancer Institute, Boston, MA, USADepartment of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
This edition first published 2023© 2023 John Wiley & Sons, Inc.
All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions
The right of Milka Kostic and Lyn H. Jones to be identified as the editors of this work has been asserted in accordance with law.
Registered Office(s)John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA
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List of Contributors
Roman V. AgafonovC4 Therapeutics Inc., WatertownMA, USA
Sajjad AhrariInstitute for Research in Immunology and Cancer of the Université de MontréalQuébec, Canada
Tomoko Asatsuma‐OkumuraDepartment of Chemical BiologyTokyo Medical UniversityTokyo, Japan
Michel BouvierInstitute for Research in Immunology and Cancer of the Université de MontréalQuébec, Canada
Gwen R. BuelProtein Processing SectionCenter for Structural BiologyCenter for Cancer ResearchNational Cancer InstituteNational Institutes of HealthFrederick, MD, USA
Sara BuhrlageDepartment of Cancer BiologyDana‐Farber Cancer InstituteBoston, MA, USA
Gabriela ChiosisProgram in Chemical Biology ProgramMemorial Sloan Kettering Cancer CenterNew York, NY, USADepartment of MedicineMemorial Sloan Kettering Cancer Center and Weill Cornell Medical CollegeNew York, NY, USA
Amit ChoudharyChemical Biology and Therapeutics ScienceBroad Institute of MIT and HarvardCambridge, MA, USADepartment of MedicineHarvard Medical SchoolBoston, MA, USADivisions of Renal Medicine and EngineeringBrigham and Women's HospitalBoston, MA, USAIslet Cell & Regenerative BiologyJoslin Diabetes CenterBoston, MA, USA
Alessio CiulliCentre for Targeted Protein DegradationSchool of Life SciencesUniversity of DundeeDundee, UK
Richard W. DeiblerC4 Therapeutics Inc.Watertown, MA, USA
Chander S. DigwalProgram in Chemical Biology ProgramMemorial Sloan Kettering Cancer CenterNew York, NY, USA
Laura DohertyDepartment of Cancer BiologyDana‐Farber Cancer InstituteBoston, MA, USA
William A. ElamC4 Therapeutics Inc.Watertown, MA, USA
Alejandra FelixDepartment of Cancer BiologyDana‐Farber Cancer InstituteBoston, MA, USA
Fleur M. FergusonDepartment of Chemistry and BiochemistryUniversity of California San DiegoSan Diego, CA, USASkaggs School of Pharmacy and Pharmaceutical SciencesUniversity of California San DiegoSan Diego, CA, USA
Stewart L. FisherC4 Therapeutics Inc.Watertown, MA, USA
Zachary J. Gale‐DayDepartment of Pharmaceutical ChemistryUniversity of CaliforniaSan Francisco, CA, USA
Jason E. GestwickiDepartment of Pharmaceutical ChemistryUniversity of CaliforniaSan Francisco, CA, USA
Stephen D. GinsbergCenter for Dementia ResearchNathan Kline InstituteOrangeburg, NY, USADepartment of Psychiatry, Neuroscience & Physiology, and the NYU Neuroscience InstituteNew York University Grossman School of MedicineNew York, NY, USA
Nathanael S. GrayDepartment of Chemical and Systems BiologyChem‐H and Stanford Cancer InstituteStanford MedicineStanford UniversityStanford, CA, USA
Pablo M. GutierrezDMPK, Oncology R&DAstraZeneca, Cambridge, UK
Sofia GuzzettiDMPK, Oncology R&DAstraZeneca, Cambridge, UK
Hiroshi HandaDepartment of Chemical BiologyTokyo Medical UniversityTokyo, Japan
Oliver HsiaCentre for Targeted Protein DegradationSchool of Life SciencesUniversity of DundeeDundee, UK
Takumi ItoDepartment of Chemical BiologyTokyo Medical UniversityTokyo, Japan
Lyn H. JonesCenter for Protein DegradationDana‐Farber Cancer InstituteBoston, MA, USADepartment of Biological Chemistry and Molecular PharmacologyHarvard Medical SchoolBoston, MA, USA
Milka KosticDepartment of Cancer BiologyDana‐Farber Cancer InstituteBoston, MA, USA
Sophia LaiChemical Biology and Therapeutics ScienceBroad Institute of MIT and HarvardCambridge, MA, USADepartment of Chemistry and Chemical Biology, Harvard UniversityCambridge, MA, USA
Suli‐Anne LaurinInstitute for Research in Immunology and Cancer of the Université de MontréalQuébec, Canada
Gabriel LaPlanteDepartment of Molecular and Cellular BiologyCollege of Biological ScienceUniversity of GuelphGuelph, Ontario, Canada
Xiuxiu LuProtein Processing SectionCenter for Structural BiologyCenter for Cancer ResearchNational Cancer InstituteNational Institutes of HealthFrederick, MD, USA
Qi LiuDepartment of Molecular and Cellular Biology, College of Biological ScienceUniversity of GuelphGuelph, Ontario, Canada
Xiaoxi LiuDepartment of Cancer BiologyDana‐Farber Cancer InstituteBoston, MA, USA
Ashley E. ModellChemical Biology and Therapeutics ScienceBroad Institute of MIT and HarvardCambridge, MA, USADepartment of MedicineHarvard Medical SchoolBoston, MA, USADivisions of Renal Medicine and EngineeringBrigham and Women's HospitalBoston, MA, US
Behnam NabetHuman Biology DivisionFred Hutchinson Cancer CenterSeattle, WA, USA
Joe S. PatelC4 Therapeutics Inc.Watertown, MA, USA
Andy PikeDMPK, Oncology R&DAstraZeneca, Cambridge, UK
Anand R. SanthaseelaProgram in Chemical Biology ProgramMemorial Sloan Kettering Cancer CenterNew York, NY, USA
James S. ScottChemistry, Oncology R&DAstraZeneca, Cambridge, UK
Sahil SharmaProgram in Chemical Biology ProgramMemorial Sloan Kettering Cancer CenterNew York, NY, USA
Kylie J. WaltersProtein Processing SectionCenter for Structural BiologyCenter for Cancer ResearchNational Cancer InstituteNational Institutes of HealthFrederick, MD, USA
Mélissanne de WispelaereEvotec ID (Lyon) SASLyon, France
Hongguang XiaDepartment of Biochemistry & Research Center of Clinical Pharmacy of The First Affiliated HospitalZhejiang University School of Medicine Hangzhou, ChinaZhejiang Laboratory for Systems & Precision MedicineZhejiang University Medical CenterHangzhou, China
Xiaoyan XuDepartment of Biochemistry & Research Center of Clinical Pharmacy of The First Affiliated HospitalZhejiang University School of MedicineHangzhou, ChinaZhejiang Laboratory for Systems & Precision MedicineZhejiang University Medical CenterHangzhou, China
Yuki YamaguchiSchool of Life Science and TechnologyTokyo Institute of TechnologyYokohama, Japan
Junichi YamamotoSchool of Life Science and TechnologyTokyo Institute of TechnologyYokohama, Japan
Priscilla L. YangDepartment of Microbiology and ImmunologyStanford University School of MedicineStanford, CA, USA
Lingzhi YeDepartment of Biochemistry & Research Center of Clinical Pharmacy of The First Affiliated HospitalZhejiang University School of MedicineHangzhou, ChinaZhejiang Laboratory for Systems & Precision MedicineZhejiang University Medical CenterHangzhou, China
Wei ZhangDepartment of Molecular and Cellular BiologyCollege of Biological ScienceUniversity of GuelphGuelph, Ontario, CanadaCIFAR Azrieli Global Scholars ProgramCanadian Institute for Advanced ResearchToronto, Ontario, Canada
Manke ZhangDepartment of Biochemistry & Research Center of Clinical Pharmacy of The First Affiliated HospitalZhejiang University School of Medicine Hangzhou, ChinaZhejiang Laboratory for Systems & Precision MedicineZhejiang University Medical CenterHangzhou, China
Mengxin ZhouDepartment of Biochemistry & Research Center of Clinical Pharmacy of The First Affiliated HospitalZhejiang University School of MedicineHangzhou, ChinaZhejiang Laboratory for Systems & Precision MedicineZhejiang University Medical CenterHangzhou, China
Preface
Traditional drug discovery and development efforts have primarily focused on developing small molecule agents that inhibit the activity of a given target, with high potency and selectivity. In this scenario, the effect of the small molecule, the presumed drug, should have one, and only one, outcome: the target's activity is stopped in its tracks, and its biological function, which causes the disease, curtailed. Although useful as a framework for structuring projects and deliverables, this premise is far too simplistic because the majority of human diseases do not hinge on a single protein and/or are not dependent on upregulation of enzymatic activity and thus responsive to target inhibition. Additionally, most biological processes are plastic and adaptable, and perturbing one protein often results in compensatory effects and drug resistance.
With the advent of technologies that can map cellular states at genomic, transcriptomic, proteomic, and metabolomic levels, we are now entering an era of emerging appreciation that a target's activity may not be the only factor that needs to be taken into account when developing therapeutic agents. Impacting protein stability, cellular localization, abundance, interactions, and other aspects of protein homeostasis are coming to the forefront of translational chemical biology and medicinal chemistry efforts. This book is a compilation of chapters divided into four sections that collectively cover current state‐of‐the‐art in chemical biology approaches to studying, targeting, and redirecting protein homeostasis, and how these efforts are changing traditional inhibitor‐driven drug discovery into a more ligand‐guided process.
Part I is focused on protein folding and quality control in drug discovery. Many diseases are driven by protein misfolding or changes in proteostasis that result in a disease phenotype. This section provides an overview of several topics that illustrate progress made in this area. Chapter 1 focuses on the new concept of epichaperomes, long‐lived assemblies of molecular chaperones, co‐chaperones, and other binding partners that have emerged as important disease‐associated pathological scaffolds, especially in the context of neurodegenerative disease and cancer. The chapter defines the epichaperomes, discusses how epichaperomes affect the proteome, and describes efforts to exploit these pathological assemblies for drug and diagnostics development purposes. Chapter 2 builds on the theme of molecular chaperones and examines how chaperones and the ubiquitin–proteasome system (UPS) regulate folding, stability, and turnover of nuclear hormone receptors (NHRs). NHRs are a large class of transcription factors that are commonly considered as druggable given their responsiveness to small molecule (hormone) binding. The chapter describes the main chaperones involved in regulating NHR folding and stability, the factors that control UPS‐dependent degradation of NHRs, and small molecules that induce their degradation, especially selective estrogen receptor degraders (SERDs) and selective androgen receptor degraders (SARDs). In addition to molecular chaperones that ensure proper protein folding and trafficking, pharmacological chaperones, small molecules that function in a similar manner to molecular chaperones, have recently emerged as a pharmacological modality of interest. Chapter 3 provides a brief overview of cellular protein folding processes and describes efforts to develop pharmacological chaperones that are able to correct protein misfolding. Using G‐protein coupled receptors (GPCRs) as an example, the chapter illustrates the mechanism of action (MOA) of pharmacological chaperones and discusses major lessons learned from driving their development from preclinical concept into in vivo validation.
Part II discusses protein degradation and clearance as drug targeting opportunities. The section begins with Chapter 4 that reviews a large area of developing drugs directed at targeting the proteasome, a large macromolecular machine that mediates proteolysis of proteins post‐translationally modified with the small protein ubiquitin. The proteasome plays a critical role in regulating cellular processes, and targeting the proteasome has become an important strategy in drug discovery and development. This chapter discusses how subunit composition, dynamics, architecture, and proteasome‐associated factors affect proteasomal function, as well as targeting opportunities. The proteasome is an ultimate component of the UPS, a system of three main enzymes (E1, E2, and E3), which form an enzymatic cascade that mediates substrate protein ubiquitination. Therefore, these enzymes regulate flux through the UPS and represent important drug targets. Chapter 5 describes current efforts to develop small molecule inhibitors of these enzymes, highlighting targeting opportunities and discussing some of the pressing current challenges. The chapter also provides an exhaustive list of inhibitors described in the literature. Another family of enzymes involved in the UPS are deubiquitinating enzymes or DUBs. DUBs are a large family of proteases that catalyze proteolytic removal of ubiquitin marks. Thus, their activity opposes the UPS. Chapter 6 discusses the value of DUBs as drug targets, as well as the need to develop high‐quality chemical probes and tools to study the biology and substrate preference of these enzymes that, despite considerable efforts, remain incompletely understood. In addition to the UPS, eukaryotic cells use autophagy to control levels of long‐lived biomolecules and injured organelles. Chapter 7 describes recent efforts in understanding different types of autophagy and drugs that target these processes, as well as the newest developments aimed at redirecting autophagy toward degrading novel protein substrates as a means of controlling substrate protein levels.
In addition to the recently developed ability to redirect and control autophagy, agents that redirect activity of the UPS toward novel (neo)‐substrates has been of growing interest in drug discovery and development. Part III features four chapters that describe the history of the field of targeted protein degradation (TPD). Chapter 8 introduced thalidomide and immunomodulatory imide drugs (IMiDs) and the pharmacology of so‐called molecular glue compounds, molecules that use a single pharmacophore to mediate ternary complex formation between the E3 ubiquitin ligase, the molecular glue compound, and the target. The following chapters (Chapters 9, 10, and 11) describe progress in the field of bifunctional degrader molecules called PROTACs (Proteolysis Targeting Chimeras). PROTACs represent one of the newest pharmacological modalities of exceptional interest given their ability to induce targeted degradation of a protein of interest. The chapters describe advantages of targeted degradation over inhibition, as well as strategies for PROTAC design (Chapter 9), biochemical principles (Chapter 10), and pharmacology (Chapter 11).
Part IV is dedicated to the discussion of emerging concepts and future directions. Therefore, Chapter 12 builds on the lessons learned from PROTAC development and describes attempts to use bifunctional molecules to redirect the activity of other cellular enzymes, such as phosphatases and kinases. Developing molecules that achieve accurate control over enzymes and redirecting them toward novel substrates at will would enable both basic and translational research. Protein technologies that incorporate degradation tags enable accurate and acute target knockdown, and Chapter 13 describes advances made in the field. Chapter 14 describes recent efforts to use TPD to create improved antivirals, an important new direction for the field given that most of the initial development was aimed at cancer.
In the final chapter, we take a look at traditional drug discovery, both phenotypic and target‐based, and discuss their advantages and key shortcomings. We argue that selecting targets based on the disease biology and human genetics, and prioritizing ligand discovery over inhibitor discovery will likely yield molecules with unanticipated MOAs and novel pharmacology.
Collectively, this book offers the reader an opportunity to learn more about the importance of considering and targeting protein homeostasis, as well as the critical need for developing novel pharmacological modalities beyond inhibitors.
Milka KosticDepartment of Cancer Biology, Dana‐Farber Cancer Institute, Boston, MA, USA
Lyn H. JonesCenter for Protein Degradation, Dana‐Farber Cancer Institute, Boston, MA, USADepartment of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USAJuly, 2022
Section IProtein Folding and Quality Control in Drug Discovery
1Epichaperomes as a Gateway to Understanding, Diagnosing, and Treating Disease Through Rebalancing Protein–Protein Interaction Networks
Chander S. Digwal1, Sahil Sharma1, Anand R. Santhaseela1, Stephen D. Ginsberg2,3, and Gabriela Chiosis1,4
1Program in Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
2Center for Dementia Research, Nathan Kline Institute, Orangeburg, NY, USA
3Departments of Psychiatry, Neuroscience & Physiology and the NYU Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
4Department of Medicine, Memorial Sloan Kettering Cancer Center and Weill Cornell Medical College, New York, NY, USA
1.1 Introduction
Proteostasis, or protein homeostasis, the process that regulates proteins within the cell, involves an extensive network of components that control protein biogenesis, folding, trafficking, and degradation [1]. In this context, proteostasis depends on the proper function of several cellular machineries, including molecular chaperones, autophagy regulators, ubiquitin–proteasomal system, and the unfolded protein response network. These work together to govern the fate of a protein from synthesis to degradation, and act to maintain proteins in the correct concentration, conformation, and subcellular location [2]. The impact that these machineries exert on proteostasis, as well as the decline of their function that results in proteostasis defects, has been studied and reviewed in great detail [1–5], illustrating their importance for proper cellular function, and in turn, disease biology.
Paradoxically, this widely used definition of proteostasis overlooks the fact that proteins rarely act alone. It is the interaction of each protein with other proteins and biomolecules that impacts and defines the function of each individual protein and its homeostasis, as well as the proteome as a whole [6–8]. Even though proteins have historically been examined in isolation, it is now clear that proteomes are defined by complex protein–protein interactions (PPIs) shaped by protein posttranscriptional modifications (PTMs), protein abundance, and other factors, most of which manifest in a cell‐, tissue‐, and disease‐specific manner [9–11]. In this context, proteostasis changes that lead to disease represent perturbations of the underlying tissue‐ and cell‐specific PPI networks arising from both internal and external stressors (e.g. genetic mutations, proteotoxic stress, aging, chemical or other environmental exposures, and/or lifestyle choices, among others) [11–13]. It is the severity of perturbation to the complex network of PPIs, i.e. interactomes, that reproducibly captures proteostasis alterations and thus define phenotypes [8, 14–16]. Therefore, understanding proteostasis requires a mindset that goes beyond biogenesis, folding, trafficking, and degradation of proteins, and incorporates the study of the interactome.
Herein, we provide a brief overview of how the discipline of chemical biology has introduced an additional enriching layer in our appreciation of proteostasis and, in the process, has reshaped our understanding of interactomes in disease. We start by providing a short historical overview on the discovery of epichaperomes, long‐lived assemblies, and disease‐associated pathologic scaffolds composed of tightly bound chaperones, co‐chaperones, and other factors. We highlight our current knowledge of the effect epichaperomes have on reshaping PPIs at a proteome‐wide level in cancer and neurodegenerative disorders. Finally, we discuss novel opportunities for drug discovery by detecting and rebalancing proteome‐wide PPI defects through epichaperomes.
1.2 Epichaperomes Explored Through Chemical Biology
1.2.1 What are Epichaperomes?
The term “epichaperome” was coined by Rodina et al. in 2016 to describe multimeric, long‐lived chaperone assemblies identified in cancer cells and primary tumor specimens [17]. These structures were discovered when the authors applied a variety of chemical biology tools, including heat‐shock protein 90 (HSP90) inhibitor PU‐H71 (Zelavespib) [18–20], and solid support immobilized [19–21] and fluorescently labeled [19, 20, 22] variants, Figure 1.1. These molecules were used in combination with chemoproteomics and analytic biochemical methods that retain native protein conformations and complexes to investigate factors that determine the sensitivity of tumors to HSP90‐targeted therapy [17]. The authors found that the apoptotic response of cancer cells caused by PU‐H71 was dependent on the presence and abundance of epichaperomes, but independent of levels of HSP90, other chaperones, and HSP90 client proteins (Figure 1.2a,b) [17, 23, 30]. These preclinical findings were later tested in the clinic in the context of metastatic breast cancer, demonstrating that patients with highest epichaperome levels in their tumors at baseline receive the greatest therapeutic benefit of PU‐H71 therapy, as evidenced by longer time to progression [31].
Figure 1.1 Chemical structure of epichaperome chemical probes ranging from epichaperome disrupters to epichaperome detection and quantification probes to tools for affinity purification. Note a control chemical probe that contains the purine core but has little to no affinity for epichaperomes is also shown.
Independent of tissue of origin, tumor subtype, or genetic background, approximately 50–60% of tumors were found to express variable epichaperome levels, with ~10–15% being high expressors [12, 17]. Unlike individual chaperones (e.g. HSP90, heat shock cognate 70 (HSC70)) found at high levels throughout the body [32–35], epichaperomes are found specifically in cells exposed to chronic stressors, such as those that contribute to cancer and Alzheimer’s disease (AD) [17, 24, 25, 32] (Figure 1.2a). Additionally, epichaperomes function as pathologic scaffolds, and cause thousands of proteins to improperly interact and organize inside cells [12] (Figure 1.2a). Thus, the higher the epichaperome levels, the higher the number of proteins being negatively impacted, i.e. the higher of number of aberrant PPIs [17, 24, 25, 36] (Figure 1.2a,b).
Figure 1.2 (a) Stressors associated with disease remodel interactomes through the switch of chaperones into epichaperomes, long‐lived assemblies, and disease‐associated pathologic scaffolds composed of tightly bound chaperones, co‐chaperones, and other factors. Not to be confused with chaperones, ubiquitous proteins which fold and act through one‐on‐one dynamic complexes, epichaperomes act as pathologic scaffolds that form specifically in disease. They cause thousands of proteins to improperly interact and organize inside cells. Major chaperones such as HSP90 and HSC70 play a central role in the formation of epichaperome structures, yet these chaperones become functionally and biochemically distinct entities when part of epichaperomes. (b) The higher the epichaperome levels, the higher the number of proteins being negatively impacted, i.e. the higher of number of aberrant protein–protein interactions (PPIs), the more vulnerable the cell is to epichaperome therapy. (c) Epichaperome formation, constituency, and function are context dependent and shaped by stressors intrinsic to each pathologic phenotype.
The constituency of epichaperome scaffolding platforms is context dependent [13, 21, 23–29] (Figure 1.2c). For example, Rodina et al. discovered that HSP90 and HSC70 play a central role in the formation of epichaperome structures in tumors [17], where these structures dysregulate PPI networks to provide a survival advantage to cancer cells and tumor‐supporting cells in the microenvironment [12, 17, 32]. Glucose‐regulated protein 94 (GRP94), an endoplasmic reticulum (ER) HSP90 paralog, participates in epichaperomes in HER2‐ and EGFR‐overexpressing breast cancers where it is found to be translocated to the plasma membrane and involved in rewiring signaling pathways [29, 37, 38]. Interestingly, HSC70 is also an epichaperome constituent along with HSP90 in AD brains where epichaperomes negatively impact the connectivity of proteins integral for synaptic plasticity and metabolic rewiring [25]. HSP60 becomes an epichaperome component in neurons exposed to mitochondrial toxins, such as rotenone, to produce defects in dopamine pathways relevant to understanding the pathogenesis of Parkinson’s disease (PD), whereas HSC70 is co‐opted in conditions of genetic stress (e.g. PARKIN mutation) to activate inflammatory pathways [24].
Although specific triggers for epichaperome formation are not understood, PTMs may play an important role to stabilize specific chaperone conformation that facilitates epichaperome incorporation [12, 39]. This conformation may become stabilized by PTMs within constituent chaperones, such as reported for GRP94 [29], interacting proteins, or both. Organelle‐specific protein networks may also form in disease conditions, similar to those noted for the HSP90‐containing epichaperomes. Furthermore, each disease‐specific set of alterations may provide a unique triggering event that drives epichaperome formation. For example, Yan et al. found that N‐glycosylation at N62 in GRP94 is a structural mediator for the switch of the chaperone into the epichaperome, as it stabilizes a unique GRP94 conformation that facilitates stable interactions with proteins, other chaperone members, and co‐chaperones [29]. Through this type of stabilization, the functions of these proteins are enhanced, and dependent cellular protein networks are aberrantly remodeled. Yan et al. reported that in breast tumors driven by receptor tyrosine kinase (RTK; e.g. HER2 and EGFR) overexpression, Glyc62GRP94‐epichaperomes form at the plasma membrane, where they reduce RTK internalization and maintain RTK in a state competent for constitutively enhanced downstream signaling [29].
Overall, epichaperomes are scaffolding platforms that rewire PPI networks, including signaling pathways and metabolic processes that promote disease formation and maintenance. Epichaperome assembly is dependent on specific phenotypic contexts, and may be triggered by key chaperone PTMs that function to induce epichaperome‐promoting conformations.
1.2.2 Mapping the Effects of Epichaperomes on the Proteome
Individual proteome components impacted by epichaperomes are also context specific, and dependent upon underlying stressors, and the constituency of individual epichaperomes [17, 24, 25] (Figure 1.2c). The epichaperome platforms and their interacting proteins have been studied using an unbiased chemoproteomics method called epichaperomics (reviewed in [11] and see Figure 1.3). Epichaperomics is an affinity‐purification method that uses the multitude of epichaperomes in a particular cell as bait to capture the disease‐promoting complement of proteins and query their disease‐specific interactions (Figure 1.3). An analogy is affinity‐purification methods whereby several tagged proteins are added to the cell and interacting proteins are captured [40]. Another analogy is yeast two‐hybrid (Y2H) experimentation [41]. However, unlike classic affinity purification and Y2H approaches, in epichaperomics, there is no need to introduce artificial baits because the epichaperomes themselves serve as the baits [11]. Also, in epichaperomics, there is not one bait but rather a multitude of baits (i.e. the distinct epichaperome structured characteristic of a specific cellular context), each having individual interactors [11]. Similar to other affinity‐purification methods, bait‐bound interactors are captured and interrogated by mass spectrometry for unequivocal identification [11]. In the case of epichaperomics, the epichaperome “biological” baits are captured by chemical probes (Figure 1.1) that trap epichaperomes bound to their interacting proteins and retain bona fide interactions through subsequent isolation steps and enabling their unbiased identification by mass spectrometry [11]. To date, only probes that capture HSP90‐incoporating epichaperomes have been reported, and therefore information on epichaperome interactors comes from the use of these probes [11].
As reviewed by Ginsberg et al. [11], epichaperomic profiling in cancer, PD, and AD robustly demonstrated that this approach provides insights into human disease biology unavailable through other omics platforms and derived datasets, as it generates an unbiased view of proteome‐wide PPI changes (including number and nature of PPIs) inherent to each phenotype, and the functional output of these connections [11]. By eliminating the need for exogenous introduction of a tagged protein as bait, the method can be applied to dissect native cellular states in samples ranging from cells to tissues, including primary specimens, immune‐system associated cell populations, postmortem brain tissues, biopsies, as well as relevant animal models and cultured cells [17, 24, 25, 36]. Moreover, the ability of chemical baits that select, enrich, and trap epichaperome–proteome interactions enable robust identification of a dynamic range of proteins, increasing the likelihood that both low copy proteins and weak PPIs are detected, which was shown to be the case in both cancer and neurodegenerative disorders [11, 25, 36].
Figure 1.3 Schematic of epichaperomics, an affinity purification‐based chemoproteomics approach to investigate in a context‐specific manner the proteome and the proteome functions negatively impacted by epichaperome formation.
Inda et al. applied the epichaperomics platform to postmortem human brains of AD patients, iPSC‐derived neurons of familial AD, transgenic (Tg) mouse brains modeling tauopathies, and N2a cells transfected with human tau [25]. Stressors or the combination of stressors driving each of these phenotypes are distinct. For example, in sporadic AD, each patient presents with disease caused by a personalized combination of genetic, epigenetic, proteotoxic, and environmental factors [42]. In the tested familial AD neurons, the stressor is of genetic origin, emerging from amyloid‐beta precursor protein (APP) duplication [43]. In the PS19 Tg mice, the stressor is of proteotoxic nature, and induced by overexpression of the human T34 isoform of tau (1N4R) with the P301S mutation [44], whereas in N2a cells, proteotoxicity is derived from overexpression of the human T40 isoform of tau (4R2N) [25]. Inda et al. found the interactome impacted by epichaperomes was stressor‐specific, with each stressor impacting thousands of proteins to establish aberrant connections while concomitantly losing normal connectivity [25]. Remarkably, despite the largely distinct proteome impacted by these stressors, a common theme was that they were largely implicated in PPI networks related to synaptic plasticity [25]. Thus, although the identity of individual synaptic plasticity‐related proteins impacted by epichaperome formation differed between these stressor conditions, epichaperome‐mediated changes in the interaction of these proteins all shared the same functional output: imbalance in protein pathways integral to synaptic plasticity [11, 25]. Taken together, defects in synaptic plasticity are a pervasive epichaperome‐mediated vulnerability of brain cells in response to various genetic, toxic, and environmental stressors. These defects may be correctable through epichaperome‐targeted therapies [13], opening new opportunities for developing novel targeting modalities by rebalancing disease‐associated changes in proteostasis.
Another important layer of information derived from epichaperomics is the full extent of the proteome whose interactions are disrupted by epichaperome formation. Inda et al. determined that approximately 942 proteins lost interactions with at least one partner, and 1191 proteins formed new interactions in the transition from no cognitive impairment (NCI) to AD. Therefore, epichaperome rewiring is accompanied by large systemic perturbations to the interactomes, PPIs, and protein networks [25]. Ultimately, epichaperome formation can lead to both a loss of function and a gain of function in protein networks, altering interactions of thousands of proteins with or without changing their expression levels.
1.3 Engineering Interactomes for Therapeutic Vulnerability Through Epichaperomes
Since epichaperomes function as scaffolds that rewire PPI networks, it might be possible to develop therapeutic strategies that redirect this intrinsic mechanism toward novel applications to control PPI networks. This question was recently addressed in the context of cancer [36], where dynamic and redundant nature of PPI networks represents a challenge for monotherapy [45]. Cellular networks have inbuilt plasticity that enables rewiring of PPIs as a strategy to improve reliability and enable cellular survival under continuous fluctuations in the extracellular and intracellular environments [46]. Unfortunately, this plasticity also provides a vexing outlet for therapy evasion, especially in cancer [47]. For example, most pancreatic cancer cells have common activating point mutations in KRAS, leading to uncontrolled activation of downstream intracellular signaling pathways, including the RAF/MEK/ERK pathway that contributes to tumor cell proliferation and survival [48, 49]. Nevertheless, inhibitors targeting the RAF/MEK/ERK pathway perform poorly in these tumors due to reciprocal increase in alternate signaling activity, such as in the AKT/mTOR pathway [50].
Recently, Joshi et al. hypothesized that tumors cannot have an infinite number of alternate pathways for rerouting the signaling, and that a limit must exist where no further PPIs can be physically and functionally possible within a cell [36]. This implies that even cancer cells must have a finite number of possible functional PPI permutations in a specific cellular context [36]. Attaining a state where a maximal number of PPIs is reached, dubbed a hyperconnectivity state, should in theory be a state of maximal vulnerability to monotherapy as it would lack redundant paths that allow evasion. Through empirical interrogation, the authors found that the hyperconnectivity state is amenable to chemical biology engineering, and in fact can be pharmacologically created through modulating epichaperomes via PU‐H71 [36]. When pancreatic tumors were engineered into the hyperconnectivity state, they became highly vulnerable to inhibitors of intrinsic protein pathways, such as of the RAF/MEK/ERK pathway [36]. This illustrates that pharmacologic epichaperome modulation could be used to create therapeutic vulnerability by rewiring PPI networks and that interactome connectivity can be exploited to develop effective therapies.
1.4 Epichaperome Disruptors as Novel Therapeutics
Mechanistic findings support an important role for epichaperome in cancer, PD, and AD, and the potential value of epichaperome modulators as therapeutics [12, 24, 25, 36, 51]. For example, Inda et al. found that introduction of human tau into N2a cells was sufficient to induce epichaperome formation, resulting in functional imbalances within synaptic protein networks detected in postmortem AD brains [25]. Epichaperome disruption rebalanced the activity of these networks to their pre‐tau overexpression state, suggesting a causal link between synaptic plasticity pathway dysfunction and epichaperome formation [25, 51]. Similar restorative effects were also observed in mice. For example, in the PS19 mouse model of tauopathy [44], mutant tau overexpression is one of the major stressors that imbalances synaptic protein networks [44]. Treatment of PS19 mice with an epichaperome agent resulted in a significant rebalance in the activity of synaptic protein networks to levels observed in wild‐type (WT) littermates [25]. Moreover, epichaperome treatment restored functionality, including postsynaptic responsiveness, repaired largely compromised synaptic plasticity, and reversed cognitive decline [25]. Studies conducted in both the preventive and the interventional treatment settings in PS19 mice demonstrated cognitive improvements with measured parameters equaling those in WT mice. Similar improvements in memory performance were found in the 3×Tg AD model expressing human APPswe, PS1M146V, and tauP301L, mutations of APP, presenilin 1, and tau, respectively [25]. These examples illustrate that it is possible to repair defects within PPI networks by targeting epichaperomes.
Accordingly, we propose that the development of drug candidates that disrupt epichaperomes, while sparing the folding functions of individual chaperones, may have an important role in the treatment of a broad spectrum of diseases (Figure 1.4). We highlight several examples of small molecules that exert their biological effects by targeting epichaperomes. Although initially developed and used as an ATP‐competitive inhibitor of HSP90, recent studies have shown that PU‐H71 becomes kinetically trapped within epichaperome‐bound HSP90, whereas it rapidly dissociates from free HSP90 [17, 36, 52]. Importantly, the dissociation rate constant (koff) of PU‐H71 from epichaperomes is proportional to epichaperome occupancy, with a koff from “active” epichaperomes (i.e. epichaperomes bound to the full complement of proteins in a specific cellular context) lower than for incompletely assembled (i.e. “primed”) epichaperomes [17, 36]. This property supports the use of PU‐H71 and related agents as chemical probes to study epichaperomes and to interrogate disease biology [17, 21, 23–25, 28, 30, 32, 36, 53], as well as drug target leads toward a new class of therapeutic agents that function by preferentially engaging and modulating epichaperome function.
Figure 1.4 Schematic showing the biochemical and functional mechanism for the restorative effect of epichaperome disrupters on cellular function.
1.4.1 Kinetic Factors as Parameters in Epichaperome Drug Development
As seen for the PU‐H71 example above, kinetics of target engagement appears to be a critical parameter that determines epichaperome‐modulating capabilities of small molecules. In general, early‐stage drug development efforts have traditionally focused on optimizing target binding affinity (i.e. equilibrium constant for drug binding process), guided by the principle that higher affinity translates into a stronger pharmacological effect [54]. However, under physiological conditions within the human body, the concentration of a free drug varies over time, as determined by the drug's rate of absorption, distribution, and elimination [55], thus continuously shifting the binding equilibrium. Thus, binding kinetics (rates of association (kon) and dissociation (koff)) may have a more profound effect on a drug's impact by influencing pharmacodynamics (i.e. efficacy at the site of action), selectivity (i.e. impact on similar targets), and therapeutic index (i.e. safety profile during administration) [56–58]. Therefore, optimizing kinetic factors can be employed in drug discovery to influence not only potency and selectivity, but also to impact the safety profile of a potential drug candidate [59]. A drug with a slower koff will occupy the target for a longer period. Hence, it will have a longer target residence time (tR), which influences efficacy, while being more rapidly cleared from off‐target sites, which influences safety. An example of how kinetics impacts drug efficacy are candesartan and losartan, two closely related blood pressure medicines. Despite equivalent angiotensin II antagonistic activity in plasma, candesartan has greater efficacy in lowering arterial pressure with significantly longer duration of action than losartan due to its slower‐off rate [60]. Another example of kinetic selectivity in drug safety is the development of drugs that target muscarinic receptors to treat asthma [61]. Despite comparable binding affinity for muscarinic receptors M2, which is responsible for drug toxicity, and M3, responsible for drug efficacy, the antagonist tiotropium has an exceptionally long residence time on the M3 receptor (tR = 30 hours on M3 vs. 3 hours on M2), which accounts for its therapeutic index [61].
These kinetic factors should also be considered when developing epichaperome drug candidates [12, 32, 52]. Although not formally demonstrated, chaperones in epichaperomes are likely present in specific conformations not available to the folding chaperones [29]. Therefore, designing molecules that selectively target epichaperomes should be feasible. Several existing examples support this hypothesis, as epichaperome ligands examined to date stabilize the epichaperome upon binding, and this “trapped” drug–epichaperome intermediate is then followed by disassembly of the epichaperome [25].
Epichaperome drug candidates that transitioned to clinic bind HSP90‐containing epichaperomes via insertion into the N‐terminal domain ATP‐binding pocket of HSP90 [12, 32, 52]. However, it is important to consider that not all HSP90 inhibitors act equally well, or equally selectively on epichaperomes in relation to free HSP90 [12]. The first feature determines drug efficacy, whereas the latter influences the therapeutic index [12, 36]. For example, Joshi et al. compared the efficacy of PU‐H71 and the structurally similar compound Debio‐0932 (also called CUDC‐305), and demonstrated that only PU‐H71 inhibits epichaperome (and thus cancer growth) effectively, whereas partial epichaperome suppression by Debio‐0932 resulted in cancer cell regrowth [36].
PU‐H71 is the most clinically advanced epichaperome‐targeting drug [31]. However, PU‐H71 does not permeate the blood–brain barrier (BBB), limiting its use [32]. Bolaender et al. have recently reported a battery of tests designed to probe epichaperome engagement, specificity, and selectivity at the cellular and organismal level, in mice and humans [32]. Using this approach, they discovered a PU‐H71 derivative, PU‐HZ151, which retains the potency and selectivity of PU‐H71 for epichaperomes with the added benefit of BBB permeability [32]. This agent is currently in clinical evaluation in AD under the name PU‐AD and in gliomas under the name Icapamespib [62–64].
As noted above, each driver of epichaperome formation prefers specific chaperones, as well as specific chaperone configurations. PU‐WS13 (see Figure 1.1), a small molecule discovered by the Chiosis lab, was shown to preferentially bind Glyc62GRP94‐epichaperomes over GRP94 [29, 38]. PU‐WS13 binds to an allosteric pocket of GRP94 that only partly overlaps with the ATP‐binding pocket and is not accessible in the closely related paralog HSP90 [38]. The compound shows >100‐fold selectivity over HSP90 and no interaction with other ATP‐binders, such as kinases, when tested at 10 μM against a 98‐kinase panel [65]. Moreover, PU‐WS13 shows reduced binding to an N62Q GRP94 mutant when compared to GRP94 glycosylated at N62 [29]. PU‐WS13 is toxic to Glyc62GRP94‐expressing cancer cells, but not to cancer cells with abundant GRP94 but no Glyc62GRP94‐epichaperome expression [29]. When tested in tumor‐bearing mice, PU‐WS13 potently suppressed the growth of Glyc62GRP94‐dependent breast tumors without affecting HSP90 or GRP94 functions [29]. The specificity of PU‐WS13 for the pathologic GRP94 variant over the intracellular physiologic GRP94 pool was recently confirmed by independent laboratories [66].
Using PU‐WS13, Yan et al. demonstrated that targeting of Glyc62GRP94 in RTK‐overexpressing tumors, such as in EGFR++ triple‐negative breast cancer (TNBC) and in HER2++ breast cancer, is safe and effective in tumor‐bearing mice [29]. Others have used PU‐WS13 in a model of alcohol‐induced liver damage to show it alleviates inflammatory responses in primary macrophages [67]. Moreover, in a mouse model of influenza A virus infection with secondary bacterial pneumonia results indicated that PU‐WS13 enhanced pneumococcal clearance from lung tissues and ameliorated lung pathology [68]. In disease models of inflammation, PU‐WS13 reduced the pro‐inflammatory profile of M2 macrophages [66]. Lastly, PU‐WS13 suppressed Dengue virus replication and the cytopathic effects caused by Dengue and Zika virus infection [69].
Aggregating these findings, we propose epichaperomes as targets of pharmacotherapeutic significance in several diseases. Unlike a genetic lesion, the target is the aberrant complement of PPIs within a specific disease context, i.e. a cell‐specific interactome, which may be correctable through epichaperome disruption (Figure 1.4). In this context, epichaperome disruptors represent a unique approach to “protein interactome‐based therapy” acting specifically on pathologic epichaperome scaffolds. The specificity of this approach spares the normal folding functions of chaperones, and in turn leaves proteostasis of normal cells unaffected.
1.5 Labeled Epichaperome Probes as Diagnostics
Chemical biology‐derived tools, such as fluorescently labeled derivatives of PU‐H71 and PU‐AD, can be used to detect and quantify epichaperomes (Figure 1.5a,b). Furthermore, these molecules have potential as diagnostic tools, as epichaperome levels positively correlate with cancer sensitivity to epichaperome‐disrupting compounds, such as PU‐H71 and PU‐AD [12, 17, 32, 36]. For example, a fluorescein isothiocyanate (FITC) labeled PU‐H71 (see Figure 1.1) was used in combination with flow cytometry for single cell measurements of epichaperomes in the context of cultured cancer cells [17, 23] as well as in primary specimens in the context of hematologic malignancies [22, 26] (see Figure 1.5b). Sugita et al. used this probe to identify a patient with an unclassified myeloproliferative disorder who could benefit from epichaperome therapy [26]. They found both blasts and granulocytes showed high epichaperome abundance, in contrast to the normal lymphocytes derived from the male‐matched unrelated donor. Prior to being evaluated for epichaperome therapy, the patient had an allogeneic stem cell transplantation, thus the presence of the donor lymphocytes. The patient was in complete remission for a year after stem cell transplantation but showed evidence of early relapse and started treatment with three cycles of azacitidine. However, disease recurred, along with significant splenomegaly and later progressed to acute myeloid leukemia with fibrosis. The patient developed progressive
