Translational PK-PD for targeted protein degradation

Design, synthesis, and biological evaluation of RSL3-based GPX4 degraders with hydrophobic tags

Ferroptosis is a new type of programmed cell death characterized by iron-dependent lipid peroxidation, during which glutathione peroxidase 4 (GPX4) plays an essential role and is well-recognized as a promising therapeutic target for cancer treatment. Although some GPX4 degradation molecules have been developed to induce ferroptosis, the discovery of GPX4 degraders with hydrophobic tagging (HyT) as an innovative approach is more challenging. Herein, we designed and synthesized a series of HyT degraders by linking the GPX4 inhibitor RSL3 with a hydrophobic and bulky group of adamantane. Among them, compound R8 is a potent degrader (DC50, 24h = 0.019 μM) which can effectively degrade GPX4 in a dose- and time-dependent manner. Furthermore, compound R8 exhibited superior in vitro antitumor potency against HT1080 and MDA-MB-231 cell lines with IC50 values of 24 nM and 32 nM respectively, which are 4 times more potent than parental compound RSL3. Mechanistic investigation evidenced that R8 consumes GPX4 protein mainly through the ubiquitin proteasome (UPS) and enables to induce the accumulation of LPO, thereby triggering ferroptosis. Our work presented the novel GPX4 degrader of R8 by HyT strategy, and provided a promising pathway of degradation agents for the treatment of ferroptosis relevant diseases.

Application of Mechanistic Multiparameter Optimization and Large-Scale In Vitro to In Vivo Pharmacokinetics Correlations to Small-Molecule Therapeutic Projects

Computational chemistry and machine learning are used in drug discovery to predict the target-specific and pharmacokinetic properties of molecules. Multiparameter optimization (MPO) functions are used to summarize multiple properties into a single score, aiding compound prioritization. However, over-reliance on subjective MPO functions risks reinforcing human bias. Mechanistic modeling approaches based on physiological relevance can be adapted to meet different potential key objectives of the project (e.g., minimizing dose, maximizing safety margins, and/or minimizing drug-drug interaction risk) while retaining the same underlying model structure. The current work incorporates recent approaches to predict in vivo pharmacokinetic (PK) properties and validates in vitro to in vivo correlation analysis to support mechanistic PK MPO. Examples of use and impact in small-molecule drug discovery projects are provided. Overall, the mechanistic MPO identifies 83% of the compounds considered as short-listed for clinical experiments in the top second percentile, and 100% in the top 10th percentile, resulting in an area under the receiver operating characteristic curve (AUCROC) > 0.95. In addition, the MPO score successfully recapitulates the chronological progression of the optimization process across different scaffolds. Finally, the MPO scores for compounds characterized in pharmacokinetics experiments are markedly higher compared with the rest of the compounds being synthesized, highlighting the potential of this tool to reduce the reliance on in vivo testing for compound screening.

Transforming the Discovery of Targeted Protein Degraders: The Translational Power of Predictive PK/PD Modeling

Targeted protein degraders (TPDs), an emerging therapeutic modality, are attracting considerable interest with the promise to address disease-related proteins that are not druggable with conventional small molecule inhibitors. Despite their novel mechanism of action, the PK/PD relationship of degraders is still approached with a mindset deeply rooted in inhibitor drugs. Here, we establish how predictive mechanistic modeling specifically tailored to TPDs can significantly enhance the value of the available information during lead generation and optimization. By integrating the results from in vitro assays with routinely collected PK data, modeling accurately predicts degradation in vivo. These predictions transform the prioritization of compounds for in vivo studies as well as the selection of optimal dose schedules and most informative measurement time points with the least number of animals. Moreover, the comprehensive modeling framework (1) identifies the PK/PD driver of targeted protein degradation and subsequent downstream pharmacodynamic effects, and (2) uncovers the fundamental difference between degrader and inhibitor PK/PD relationships. The practical utility of our predictive modeling is demonstrated with relevant use cases. This framework will allow researchers to transition from current, mostly serendipity-based approaches to more sound model-informed decision making. Going forward, the presented predictive PK/PD modeling framework lays out a rational path to incorporate inter-species differences in the pharmacology and thus promises to help with getting the dose right in clinical trials.

Inducing Receptor Degradation as a Novel Approach to Target CC Chemokine Receptor 2 (CCR2)

CC chemokine receptor 2 (CCR2) has been linked to many inflammatory and immune diseases, making it a relevant drug target. Yet, all CCR2 antagonists developed so far have failed in clinical trials; thus, novel strategies are needed to target this receptor. Targeted protein degradation represents a novel approach to inhibit protein function by hijacking the cellular degradation machinery, such as the proteasome, to degrade the protein of interest. Here, we aimed to determine the amenability of CCR2 to chemically induced degradation by using a CCR2 fusion protein containing a HaloTag7 and HiBiT tag (CCR2-HaloTag-HiBiT). After characterization of the CCR2 construct, we used luminescence-based assays and immunofluorescence to quantify CCR2 levels, as well as a label-free, phenotypic assay to investigate the functional effect of CCR2 degradation. Treatment with HaloPROTAC3, which selectively degrades HaloTag fusion proteins, led to concentration- and time-dependent degradation of CCR2-HaloTag-HiBiT. HaloPROTAC3 induced degradation via the proteasome, as degradation was fully blocked with proteasomal inhibitors. Finally, functional assays showed that degradation of CCR2-HaloTag-HiBiT leads to a reduced functional response after agonist stimulation. Overall, our results indicate that CCR2 is amenable to targeted degradation, paving the way for the future development of CCR2 chemical degraders.

Quantitative Measurement of Rate of Targeted Protein Degradation

Targeted protein degradation (TPD) is a therapeutic approach that leverages the cell's natural machinery to degrade targets instead of inhibiting them. This is accomplished by using mono- or bifunctional small molecules designed to induce the proximity of target proteins and E3 ubiquitin ligases, leading to ubiquitination and subsequent proteasome-dependent degradation of the target. One of the most significant attributes of the TPD approach is its proposed catalytic mechanism of action, which permits substoichiometric exposure to achieve the desired pharmacological effects. However, apart from one in vitro study, studies supporting the catalytic mechanism of degraders are largely inferred based on potency. A more comprehensive understanding of the degrader catalytic mechanism of action can help aspects of compound development. To address this knowledge gap, we developed a workflow for the quantitative measurement of the catalytic rate of degraders in cells. Comparing a selective and promiscuous BTK degrader, we demonstrate that both compounds function as efficient catalysts of BTK degradation, with the promiscuous degrader exhibiting faster rates due to its ability to induce more favorable ternary complexes. By leveraging computational modeling, we show that the catalytic rate is highly dynamic as the target is depleted from cells. Further investigation of the promiscuous kinase degrader revealed that the catalytic rate is a better predictor of optimal degrader activity toward a specific target compared to degradation magnitude alone. In summary, we present a versatile method for mapping the catalytic activity of any degrader for TPD in cells.

Confounding Factors in Targeted Degradation of Short-Lived Proteins

Targeted protein degradation has recently emerged as a novel option in drug discovery. Natural protein half-life is expected to affect the efficacy of degrading agents, but to what extent it influences target protein degradation has not been systematically explored. Using simple mathematical modeling of protein degradation, we find that the natural half-life of a target protein has a dramatic effect on the level of protein degradation induced by a degrader agent which can pose significant hurdles to screening efforts. Moreover, we show that upon screening for degraders of short-lived proteins, agents that stall protein synthesis, such as GSPT1 degraders and generally cytotoxic compounds, deceptively appear as protein-degrading agents. This is exemplified by the disappearance of short-lived proteins such as MCL1 and MDM2 upon GSPT1 degradation and upon treatment with cytotoxic agents such as doxorubicin. These findings have implications for target selection as well as for the type of control experiments required to conclude that a novel agent works as a bona fide targeted protein degrader.

Breaking Bad Proteins-Discovery Approaches and the Road to Clinic for Degraders

Proteolysis-targeting chimeras (PROTACs) describe compounds that bind to and induce degradation of a target by simultaneously binding to a ubiquitin ligase. More generally referred to as bifunctional degraders, PROTACs have led the way in the field of targeted protein degradation (TPD), with several compounds currently undergoing clinical testing. Alongside bifunctional degraders, single-moiety compounds, or molecular glue degraders (MGDs), are increasingly being considered as a viable approach for development of therapeutics, driven by advances in rational discovery approaches. This review focuses on drug discovery with respect to bifunctional and molecular glue degraders within the ubiquitin proteasome system, including analysis of mechanistic concepts and discovery approaches, with an overview of current clinical and pre-clinical degrader status in oncology, neurodegenerative and inflammatory disease.

Comparison of Tumor Binding Across Tumor Types and Cell Lines to Support Free Drug Considerations for Oncology Drug Discovery

Tumor binding is an important parameter to derive unbound tumor concentration to explore pharmacokinetics (PK) and pharmacodynamics (PD) relationships for oncology disease targets. Tumor binding was evaluated using eleven matrices, including various commonly used ex vivo human and mouse xenograft and syngeneic tumors, tumor cell lines and liver as a surrogate tissue. The results showed that tumor binding is highly correlated among the different tumors and tumor cell lines except for the mouse melanoma (B16F10) tumor type. Liver fraction unbound (fu) has a good correlation with B16F10 tumor binding. Liver also demonstrates a two-fold equivalency, on average, with binding of other tumor types when a scaling factor is applied. Predictive models were developed for tumor binding, with correlations established with LogD (acids), predicted muscle fu (neutrals) and measured plasma protein binding (bases) to estimate tumor fu when experimental data are not available. Many approaches can be applied to obtain and estimate tumor binding values. One strategy proposed is to use a surrogate tumor tissue, such as mouse xenograft ovarian cancer (OVCAR3) tumor, as a surrogate for tumor binding (except for B16F10) to provide an early assessment of unbound tumor concentrations for development of PK/PD relationships.

DegraderTCM: A Computationally Sparing Approach for Predicting Ternary Degradation Complexes

Proteolysis targeting chimeras (PROTACs or degraders) represent a novel therapeutic modality that has raised interest thanks to promising results and currently undergoing clinical testing. PROTACs induce the selective proteasomal degradation of undesired proteins by the formation of ternary complexes (TCs). Having knowledge of the 3D structure of TCs is crucial for the design of PROTAC drugs. Here, we describe DegraderTCM, a new computational method for modeling PROTAC-mediated TCs that requires low computational power and provides sound results in a short time span. We validated DegraderTCM against a selected set of experimentally determined structures and defined a method to predict the PROTAC degradation activity based on the computed TC structure. Finally, we modeled TCs of known degraders holding significance for defining the method's applicability domain. A retrospective analysis of structure-activity relationships unveiled possibilities for utilizing DegraderTCM in the initial stages of designing novel PROTAC drugs.

The 17th EFMC Short Course on Medicinal Chemistry on Small Molecule Protein Degraders

The 17th EFMC Short Course on Medicinal Chemistry took place April 23-26, 2023 in Oegstgeest, near Leiden in the Netherlands. It covered for the first time the exciting topic of Targeted Protein Degradation (full title: Small Molecule Protein Degraders: A New Opportunity for Drug Design and Development). The course was oversubscribed, with 35 attendees and 6 instructors mainly from Europe but also from the US and South Africa, and representing both industry and academia. This report summarizes the successful event, key lectures given and topics discussed.

An integrated modelling approach for targeted degradation: insights on optimization, data requirements and PKPD predictions from semi- or fully-mechanistic models and exact steady state solutions

The value of an integrated mathematical modelling approach for protein degraders which combines the benefits of traditional turnover models and fully mechanistic models is presented. Firstly, we show how exact solutions of the mechanistic models of monovalent and bivalent degraders can provide insight on the role of each system parameter in driving the pharmacological response. We show how on/off binding rates and degradation rates are related to potency and maximal effect of monovalent degraders, and how such relationship can be used to suggest a compound optimization strategy. Even convoluted exact steady state solutions for bivalent degraders provide insight on the type of observations required to ensure the predictive capacity of a mechanistic approach. Specifically for PROTACs, the structure of the exact steady state solution suggests that the total remaining target at steady state, which is easily accessible experimentally, is insufficient to reconstruct the state of the whole system at equilibrium and observations on different species (such as binary/ternary complexes) are necessary. Secondly, global sensitivity analysis of fully mechanistic models for PROTACs suggests that both target and ligase baselines (actually, their ratio) are the major sources of variability in the response of non-cooperative systems, which speaks to the importance of characterizing their distribution in the target patient population. Finally, we propose a pragmatic modelling approach which incorporates the insights generated with fully mechanistic models into simpler turnover models to improve their predictive ability, hence enabling acceleration of drug discovery programs and increased probability of success in the clinic.

Clinical Translation of Targeted Protein Degraders

Targeted protein degradation (TPD) has emerged as a potentially transformational therapeutic modality with considerable promise. Molecular glue degraders remodel the surface of E3 ligases inducing interactions with neosubstrates resulting in their polyubiquitination and proteasomal degradation. Molecular glues are clinically precedented and have demonstrated the ability to degrade proteins-of-interest (POIs) previously deemed undruggable due to the absence of a traditional small molecule binding pocket. Heterobifunctional proteolysis targeting chimeras (PROTACs) possess ligands for an E3 complex and the POIs, which are chemically linked together, and similarly hijack the ubiquitin machinery to deplete the target. There has been a recent surge in the number of degraders entering clinical trials, particularly directed toward cancer. Nearly all utilize CRL4CRBN as the E3 ligase, and a relatively limited diversity of POIs are currently targeted. In this review, we provide an overview of the degraders in clinical trials and provide a perspective on the lessons learned from their development and emerging human data that will be broadly useful to those working in the TPD field.

The rise of degrader drugs

The cancer genomics revolution has served up a plethora of promising and challenging targets for the drug discovery community. The field of targeted protein degradation (TPD) uses small molecules to reprogram the protein homeostasis system to destroy desired target proteins. In the last decade, remarkable progress has enabled the rational development of degraders for a large number of target proteins, with over 20 molecules targeting more than 12 proteins entering clinical development. While TPD has been fully credentialed by the prior development of immunomodulatory drug (IMiD) class for the treatment of multiple myeloma, the field is poised for a "Gleevec moment" in which robust clinical efficacy of a rationally developed novel degrader against a preselected target is firmly established. Here, we endeavor to provide a high-level evaluation of exciting developments in the field and comment on steps that may realize the full potential of this new therapeutic modality.

Proximity-Based Modalities for Biology and Medicine

Molecular proximity orchestrates biological function, and blocking existing proximities is an established therapeutic strategy. By contrast, strengthening or creating neoproximity with chemistry enables modulation of biological processes with high selectivity and has the potential to substantially expand the target space. A plethora of proximity-based modalities to target proteins via diverse approaches have recently emerged, opening opportunities for biopharmaceutical innovation. This Outlook outlines the diverse mechanisms and molecules based on induced proximity, including protein degraders, blockers, and stabilizers, inducers of protein post-translational modifications, and agents for cell therapy, and discusses opportunities and challenges that the field must address to mature and unlock translation in biology and medicine.

Targeted protein degrader development for cancer: advances, challenges, and opportunities

Anticancer-targeted therapies inhibit various kinases implicated in cancer and have been used in clinical settings for decades. However, many cancer-related targets are proteins without catalytic activity and are difficult to target using traditional occupancy-driven inhibitors. Targeted protein degradation (TPD) is an emerging therapeutic modality that has expanded the druggable proteome for cancer treatment. With the entry of new-generation immunomodulatory drugs (IMiDs), selective estrogen receptor degraders (SERDs), and proteolysis-targeting chimera (PROTAC) drugs into clinical trials, the field of TPD has seen explosive growth in the past 10 years. Several challenges remain that need to be tackled to increase successful clinical translation of TPD drugs. We present an overview of the global landscape of clinical trials of TPD drugs over the past decade and summarize the clinical profiles of new-generation TPD drugs. In addition, we highlight the challenges and opportunities for the development of effective TPD drugs for future successful clinical translation.

Protein degraders enter the clinic - a new approach to cancer therapy

Heterobifunctional protein degraders, such as PROteolysis TArgeting Chimera (PROTAC) protein degraders, constitute a novel therapeutic modality that harnesses the cell's natural protein-degradation machinery - that is, the ubiquitin-proteasome system - to selectively target proteins involved in disease pathogenesis for elimination. Protein degraders have several potential advantages over small-molecule inhibitors that have traditionally been used for cancer treatment, including their event-driven (rather than occupancy-driven) pharmacology, which permits sub-stoichiometric drug concentrations for activity, their capacity to act iteratively and target multiple copies of a protein of interest, and their potential to target nonenzymatic proteins that were previously considered 'undruggable'. Following numerous innovations in protein degrader design and rigorous evaluation in preclinical models, protein degraders entered clinical testing in 2019. Currently, 18 protein degraders are in phase I or phase I/II clinical trials that involve patients with various tumour types, with a phase III trial of one initiated in 2022. The first safety, efficacy and pharmacokinetic data from these studies are now materializing and, although considerably more evidence is needed, protein degraders are showing promising activity as cancer therapies. Herein, we review advances in protein degrader development, the preclinical research that supported their entry into clinical studies, the available data for protein degraders in patients and future directions for this new class of drugs.

Delivering on the promise of protein degraders

Over the past 3 years, the first bivalent protein degraders intentionally designed for targeted protein degradation (TPD) have advanced to clinical trials, with an initial focus on established targets. Most of these clinical candidates are designed for oral administration, and many discovery efforts appear to be similarly focused. As we look towards the future, we propose that an oral-centric discovery paradigm will overly constrain the chemical designs that are considered and limit the potential to drug novel targets. In this Perspective, we summarize the current state of the bivalent degrader modality and propose three categories of degrader designs, based on their likely route of administration and requirement for drug delivery technologies. We then describe a vision for how parenteral drug delivery, implemented early in research and supported by pharmacokinetic-pharmacodynamic modelling, can enable exploration of a broader drug design space, expand the scope of accessible targets and deliver on the promise of protein degraders as a therapeutic modality.

Advancing Targeted Protein Degradation via Multiomics Profiling and Artificial Intelligence

Only around 20% of the human proteome is considered to be druggable with small-molecule antagonists. This leaves some of the most compelling therapeutic targets outside the reach of ligand discovery. The concept of targeted protein degradation (TPD) promises to overcome some of these limitations. In brief, TPD is dependent on small molecules that induce the proximity between a protein of interest (POI) and an E3 ubiquitin ligase, causing ubiquitination and degradation of the POI. In this perspective, we want to reflect on current challenges in the field, and discuss how advances in multiomics profiling, artificial intelligence, and machine learning (AI/ML) will be vital in overcoming them. The presented roadmap is discussed in the context of small-molecule degraders but is equally applicable for other emerging proximity-inducing modalities.

A Mechanistic Pharmacodynamic Modeling Framework for the Assessment and Optimization of Proteolysis Targeting Chimeras (PROTACs)

The field of targeted protein degradation is growing exponentially. Yet, there is an unmet need for pharmacokinetic/pharmacodynamic models that provide mechanistic insights, while also being practically useful in a drug discovery setting. Therefore, we have developed a comprehensive modeling framework which can be applied to experimental data from routine projects to: (1) assess PROTACs based on accurate degradation metrics, (2) guide compound optimization of the most critical parameters, and (3) link degradation to downstream pharmacodynamic effects. The presented framework contains a number of first-time features: (1) a mechanistic model to fit the hook effect in the PROTAC concentration-degradation profile, (2) quantification of the role of target occupancy in the PROTAC mechanism of action and (3) deconvolution of the effects of target degradation and target inhibition by PROTACs on the overall pharmacodynamic response. To illustrate applicability and to build confidence, we have employed these three models to analyze exemplary data on various compounds from different projects and targets. The presented framework allows researchers to tailor their experimental work and to arrive at a better understanding of their results, ultimately leading to more successful PROTAC discovery. While the focus here lies on in vitro pharmacology experiments, key implications for in vivo studies are also discussed.

Design and Measurement of Drug Tissue Concentration Asymmetry and Tissue Exposure-Effect (Tissue PK-PD) Evaluation

The "free drug hypothesis" assumes that, in the absence of transporters, the steady state free plasma concentrations equal to that at the site of action that elicit pharmacologic effects. While it is important to utilize the free drug hypothesis, exceptions exist that the free plasma exposures, either at C_max, C_trough, and C_average, or at other time points, cannot represent the corresponding free tissue concentrations. This "drug concentration asymmetry" in both total and free form can influence drug disposition and pharmacological effects. In this review, we first discuss options to assess total and free drug concentrations in tissues. Then various drug design strategies to achieve concentration asymmetry are presented. Last, the utilities of tissue concentrations in understanding exposure-effect relationships and translational projections to humans are discussed for several therapeutic areas and modalities. A thorough understanding in plasma and tissue exposures correlation with pharmacologic effects can provide insightful guidance to aid drug discovery.