PRosettaC: Rosetta Based Modeling of PROTAC Mediated Ternary Complexes

E3 ubiquitin ligases and their therapeutic potential in disease Management

Ubiquitination is a vital post-translational modification that regulates protein stability and various cellular processes through the addition of ubiquitin molecules. Central to this process are E3 ubiquitin ligases, which determine the specificity of ubiquitination by coordinating the attachment of ubiquitin to target proteins, influencing their degradation, localization, and activity. E3 ubiquitin ligases are involved in numerous cellular pathways, including DNA repair, cell proliferation, and immune responses. Dysregulation of E3 ubiquitin ligases is often associated with cancer, contributing to tumor progression and resistance to therapies. The development of targeted protein degraders, such as proteolysis-targeting chimeras (PROTACs), represents a significant advancement in drug discovery, leveraging the specificity of E3 ubiquitin ligases to selectively eliminate pathogenic proteins. However, challenges remain in translating this knowledge into effective therapies, including issues related to tissue-specific targeting and off-target effects. The limitations also include a limited understanding of ligase-substrate interactions that includes both the identification of novel E3 ligases and their substrates, as well as understanding the dynamic, context-dependent nature of these interactions, which can vary across tissue types or disease states This review emphasizes the therapeutic potential of E3 ubiquitin ligases, exploring their diverse roles in disease, their contribution to targeted degradation strategies while highlighting the need for further research to overcome current limitations and enhance therapeutic efficacy.

A comprehensive primer and review of PROTACs and their In Silico design

The cutting-edge technique of Proteolysis Targeting Chimeras, or PROTACs, has gained significant attention as a viable approach for specific protein degradation. This innovative technology has vast potential in fields such as cancer therapy and drug development. The development of effective and specific therapies for a range of diseases is within reach with PROTACs, which can target previously "undruggable" proteins while circumventing the off-target effects of conventional small molecule inhibitors. This manuscript aims to discuss the application of in silico techniques to the design of these groundbreaking molecules and develop PROTAC complexes, in order to identify potential PROTAC candidates with favorable drug-like properties. Additionally, this manuscript reviews the strengths and weaknesses of these methods to demonstrate their utility and highlights the challenges and future prospects of in silico PROTAC design. The present review provides a valuable and beginner-friendly resource for researchers and drug developers interested in using in silico methods for PROTAC design, specifically ternary structure prediction.

In silico modeling of targeted protein degradation

Targeted protein degradation (TPD) techniques, particularly proteolysis-targeting chimeras (PROTAC) and molecular glue degraders (MGD), have offered novel strategies in drug discovery. With rapid advancement of computer-aided drug design (CADD) and artificial intelligence-driven drug discovery (AIDD) in the biomedical field, a major focus has become how to effectively integrate these technologies into the TPD drug discovery pipeline to accelerate development, shorten timelines, and reduce costs. Currently, the main research directions for applying CADD and AIDD in TPD include: 1) ternary complex modeling; 2) linker generation; 3) strategies to predict degrader targets, activities and ADME/T properties; 4) In silico degrader design and discovery. Models developed in these areas play a crucial role in target identification, drug design, and optimization at various stages of the discovery process. However, the limited size and quality of datasets related to TPD present challenges, leaving room for further improvement in these models. TPD involves the complex ubiquitin-proteasome system, with numerous factors influencing outcomes. Most current models adopt a static perspective to interpret and predict relevant tasks. In the future, it may be necessary to shift toward dynamic approaches that better capture the intricate relationships among these components. Furthermore, incorporating new and diverse chemical spaces will enhance the precision design and application of TPD agents.

Advancing target validation with PROTAC technology

INTRODUCTION

Targeted protein degradation (TPD) is a cutting-edge technology that provides new avenues for drug discovery and development. PROteolysis TArgeting Chimeras (PROTACs) are the most established and advanced TPD strategy, enabling the selective degradation of disease-associated and 'undruggable' proteins of interest (POIs) by leveraging the cell's natural protein degradation machinery. To confirm that PROTAC-induced proximity drives protein degradation, target validation and ternary complex formation must be thoroughly assessed.

AREAS COVERED

In this perspective, the authors detail some of the most widely used in silico, structural, in vitro, and in cellulo methods to validate PROTAC target engagement and ternary complex formation. Additionally, they discuss the growing use of PROTACs as chemical probes for novel target identification and validation.

EXPERT OPINION

Target validation is essential in the PROTAC approach, and ongoing studies should prioritize confirming ternary complex formation using assays conducted under physiologically relevant cellular conditions. Proteomics analyses are among the most valuable tools for elucidating PROTAC mechanisms, selectivity, and outcomes. The authors are optimistic about the future of PROTACs in drug development and their use as probes to confirm target engagement. PROTAC technology holds vast opportunities for future exploration, offering significant potential to further both chemical and biological research.

Harnessing the Power of Natural Products for Targeted Protein Degradation

Natural products have garnered significant attention due to their complex chemical structures and remarkable pharmacological activities. With inherent recognition capabilities for protein surfaces, natural products serve as ideal candidates for designing proteolysis-targeting chimeras (PROTACs). The utilization of natural products in PROTAC development offers distinct advantages, including their rich chemical diversity, multitarget activities, and sustainable sourcing. This comprehensive review explores the vast potential of harnessing natural products in PROTAC research. Moreover, the review discusses the application of natural degradant technology, which involves utilizing natural product-based compounds to selectively degrade disease-causing proteins, as well as the implementation of computer-aided drug design (CADD) technology in identifying suitable targets for degradation within the realm of natural products. By harnessing the power of natural products and leveraging computational tools, PROTACs derived from natural products have the potential to revolutionize drug discovery and provide innovative therapeutic interventions for various diseases.

Optimization of the PROTAC linker region of the proteasome substrate receptor hRpn13 rationalized by structural modeling with molecular dynamics

Proteasome substrate receptor hRpn13 is a promising target for cancer therapy. hRpn13 proteolysis-targeting chimera (PROTACs) induce apoptosis by targeting the hRpn13 proteolytic product hRpn13Pru, which contains an intact ubiquitin- and proteasome-binding Pru domain. We generated a PROTAC series based on hRpn13Pru-targeting XL5 by varying the linker that connects it to a warhead against the VHL-based ubiquitin E3 ligase machinery. Among eight tested derivatives, XL5-VHL-7 with a -(CH2)5- alkyl linker promoted hRpn13Pru degradation and induced cellular apoptosis with 2-fold improved potency compared to the original PROTAC. By using this PROTAC series with slight chemical modifications in the linker region, we were able to evaluate the efficacy of structural modeling with molecular dynamics for refining PROTACs. Overall, we found that the experimental data correlated with efficacy predictions based on molecular dynamics and structural modeling. Moreover, we could observe hRpn13:PROTAC:VHL complexes by 2D NMR that support the structural modeling and stronger affinity of XL5-VHL-7 compared to the original hRpn13 PROTAC. Our NMR data further indicate that hRpn13 Pru affinity for XL5-VHL-7 is higher within the VHL complex present than with XL5-VHL-7 alone. Altogether, we develop an hRpn13 PROTAC with 2-fold increased potency by optimizing the linker and demonstrate the current benefit and limitations for including modeling with molecular dynamics to aid PROTAC optimization.

Ternary Complex Modeling, Induced Fit Docking and Molecular Dynamics Simulations as a Successful Approach for the Design of VHL-Mediated PROTACs Targeting the Kinase FLT3

Proteolysis targeting chimeras (PROTACs) have proven to be a novel approach for the degradation of disease-causing proteins in drug discovery. One of the E3 ligases for which efficient PROTACs have been described is the Von Hippel-Lindau factor (VHL). However, the development of PROTACs has so far often relied on a minimum of computational tools, so that it is mostly based on a trial-and-error process. Therefore, there is a great need for resource- and time-efficient structure-based or computational approaches to streamline PROTAC design. In this study, we present a combined computational approach that integrates static ternary complex formation, induced-fit docking, and molecular dynamics (MD) simulations. Our methodology was tested using four experimentally derived ternary complex structures of VHL PROTACs, reported for BRD4, SMARCA2, FAK, and WEE1. In addition, we applied the validated approach to model a recently in-house developed FLT3-targeted PROTAC (MA49). The results show that static ternary models generated with a protein-protein docking method implemented in the software MOE have a high predictive power for reproducing the experimental 3D structures. The induced-fit docking of different active PROTACs to their respective models showed the reliability of this model for the development of new VHL-mediated degraders. In particular, the induced-fit docking was sensitive to structural changes in the PROTACs, as evidenced by the failed binding modes of the PROTAC negative controls. Furthermore, MD simulations confirmed the stability of the generated complexes and emphasized the importance of dynamic studies for understanding the relationship between PROTAC structure and function.

Quantum Mechanics-Based Ranking of Predicted Proteolysis Targeting Chimeras-Mediated Ternary Complexes

Targeted protein degradation has become the most pursued alternative modality to small-molecule inhibition over the past decade. The traditional strategy of blocking protein activity by tightly binding to a functional substrate pocket has progressed toward proteolysis-targeting chimeras (PROTACs), bivalent molecules that induce the knockdown of targeted proteins. Herein, a combined protocol is described for modeling ternary complexes via well-established approaches. We performed local protein-protein docking using Rosetta protocol and sampled the conformational landscape of a specific PROTAC molecule that was compatible with the generated protein-protein docking poses, followed by double and independent single-linkage/nearest-neighbor clustering for representative selection. Subsequently, we combined the fragment molecular orbital and density functional tight-binding methods to facilitate fast quantum mechanics-based energy calculations of the clustered ternary complexes. Finally, the computed energy values were utilized to score and select the best ternary poses, achieving good agreement with available crystallographic data.

PROTAC-induced protein structural dynamics in targeted protein degradation

PROteolysis TArgeting Chimeras (PROTACs) are small molecules that induce target protein degradation via the ubiquitin-proteasome system. PROTACs recruit the target protein and E3 ligase; a critical first step is forming a ternary complex. However, while the formation of a ternary complex is crucial, it may not always guarantee successful protein degradation. The dynamics of the PROTAC-induced degradation complex play a key role in ubiquitination and subsequent degradation. In this study, we computationally modelled protein complex structures and dynamics associated with a series of PROTACs featuring different linkers to investigate why these PROTACs, all of which formed ternary complexes with Cereblon (CRBN) E3 ligase and the target protein bromodomain-containing protein 4 (BRD4BD1), exhibited varying degrees of degradation potency. We constructed the degradation machinery complexes with Culling-Ring Ligase 4A (CRL4A) E3 ligase scaffolds. Through atomistic molecular dynamics simulations, we illustrated how PROTAC-dependent protein dynamics facilitating the arrangement of surface lysine residues of BRD4BD1 into the catalytic pocket of E2/ubiquitin cascade for ubiquitination. Despite featuring identical warheads in this PROTAC series, the linkers were found to affect the residue-interaction networks, and thus governing the essential motions of the entire degradation machine for ubiquitination. These findings offer a structural dynamic perspective on ligand-induced protein degradation, providing insights to guide future PROTAC design endeavors.

A Medicinal Chemistry Perspective on Protein Tyrosine Phosphatase Nonreceptor Type 2 in Tumor Immunology

PTPN2 (protein tyrosine phosphatase nonreceptor type 2) is an important member of the protein tyrosine phosphatase (PTP) family. It plays a crucial role in dephosphorylating tyrosine-phosphorylated proteins and modulating critical signaling pathways associated with T-cell receptors, IL-2, IFNγ, and various cytokines. In recent years, the PTPN2's biological role has been clarified, particularly since its association with tumor immunology was gradually revealed in 2017, making it a star target for cancer immunotherapy. The dual inhibitor AC484, which targets both PTPN2 and PTP1B, is currently undergoing phase I clinical trials. This advancement has attracted great interest from researchers to develop new drugs based on its unique structure. This review outlines the structural modification processes of PTPN2-targeted agents, focusing primarily on inhibitors and degraders. Finally, this review endeavors to provide a comprehensive perspective on the evolving field of PTPN2-targeted drug discovery for tumor immunotherapy, offering valuable insights for future drug development.

SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation

Targeted protein degradation (TPD) induced by small molecules has emerged as a rapidly evolving modality in drug discovery, targeting proteins traditionally considered "undruggable." This strategy induces the degradation of target proteins rather than inhibiting their activity, achieving desirable therapeutic outcomes. Proteolysis-targeting chimeras (PROTACs) and molecular glue degraders (MGDs) are the primary small molecules that induce TPD. Both types of molecules form a ternary complex linking an E3 ubiquitin ligase with a target protein, a crucial step for drug discovery. While significant advances have been made in in-silico binary structure prediction for proteins and small molecules, ternary structure prediction remains challenging due to obscure interaction mechanisms and insufficient training data. Traditional methods relying on manually assigned rules perform poorly and are computationally demanding due to extensive random sampling. In this work, we introduce DeepTernary, a novel deep learning-based approach that directly predicts ternary structures in an end-to-end manner using an encoder-decoder architecture. DeepTernary leverages an SE(3)-equivariant graph neural network (GNN) with both intra-graph and ternary inter-graph attention mechanisms to capture intricate ternary interactions from our collected high-quality training dataset, TernaryDB. The proposed query-based Pocket Points Decoder extracts the 3D structure of the final binding ternary complex from learned ternary embeddings, demonstrating state-of-the-art accuracy and speed in existing PROTAC benchmarks without prior knowledge from known PROTACs. It also achieves notable accuracy on the more challenging MGD benchmark under the blind docking protocol. Remarkably, our experiments reveal that the buried surface area calculated from DeepTernary-predicted structures correlates with experimentally obtained degradation potency-related metrics. Consequently, DeepTernary shows potential in effectively assisting and accelerating the development of TPDs for previously undruggable targets.

Molecular Glue-Design-Evaluator (MOLDE): An Advanced Method for In-Silico Molecular Glue Design

Protein function modulation using small-molecule binding is an important therapeutic strategy for many diseases. However, many proteins remain undruggable due to the lack of suitable binding pockets for small-molecule binding. Proximity-induced protein degradation using molecular glues has recently been identified as an important strategy to target undruggable proteins. Molecular glues were discovered serendipitously and as such currently lack an established approach for in-silico-driven rationale design. In this work, we aim to establish an in-silico method for designing molecular glues. To achieve this, we leverage known molecular glue-mediated ternary complexes and derive a rationale for the in-silico design of molecular glues. Establishing an in-silico rationale for molecular glue design would significantly contribute to the literature and accelerate the discovery of molecular glues for targeting previously undruggable proteins. Our work presented here and named Molecular Glue-Designer-Evaluator (MOLDE) contributes to the growing literature of in-silico approaches to drug design in-silico literature.

MEGA PROTAC, MEGA DOCK-based PROTAC mediated ternary complex formation pipeline with sequential filtering and rank aggregation

Proteolysis-targeting chimaeras (PROTACs), which induce proteolysis by recruiting an E3 ligase to dock into a target protein, are acquiring popularity as a novel pharmacological modality because of the unique features of PROTAC, including high potency, low dosage, and effective on undruggable targets. While PROTACs are promising prospects as chemical probes and therapeutic agents, their discovery usually necessitates the synthesis of numerous analogues to explore variations on the chemical linker structure exhaustively. Without extensive trial and error, it is unknown how to link the two protein-recruiting moieties to facilitate the formation of a productive ternary complex. Although molecular docking-based and optimization pipelines have been designed to predict ternary complexes, guiding rational PROTAC design, they have suffered from limited predictive performance in the quality of the ternary structure and their ranks. Here, MEGA PROTAC has been designed to enhance the performance in quality and ranking of ternary structures. MEGA PROTAC employs MEGADOCK to execute docking for protein-protein complexes (PPCs). The docking establishes an initial exploration area for PPCs. A sequential filtration strategy combined with rank aggregation is employed to choose a subset of PPCs for grid search. Once candidate PPCs are selected, a grid search method is used separately for translation and rotation. The remaining proteins have been grouped into clusters, and MEGA PROTAC further filters these clusters based on the energy score of the proteins within each cluster. MEGA PROTAC utilises rank aggregation to choose the best clusters and then employs MEGADOCK to dock PROTAC into the selected PPCs, forming a ternary structure. Finally, MEGA PROTAC was tested on 22 cases to compare with the state-of-the-art method, Bayesian optimisation for ternary complex prediction (BOTCP). MEGA PROTAC outperformed BOTCP on 16 test cases out of 22 cases, achieving a higher maximum DockQ score with an 18% higher mean and 35% higher median. Also, MEGA PROTAC exhibited 75% superior ranks and a reduced cluster number for maximum DockQ score compared to BOTCP. Also, MEGA PROTAC outperforms BOTCP by achieving a twofold improvement in locating the first acceptable DockQ scores, with a more significant proportion of near-native structures within the detected cluster.

Analyzing the Linker Structure of PROTACs throughout the Induction Process: Computational Insights

Linker structures are a crucial component of proteolysis-targeting chimeras (PROTACs) and have traditionally been designed based on empirical methods, which presents significant challenges in the development of PROTACs. Current optimization strategies typically focus on reducing the number of rotatable bonds in the linker to limit conformational freedom. However, this approach overlooks the complexity of the target protein degradation process. Retrospective analyses suggest that merely adjusting the rotatable bonds in the linker is insufficient to control the conformational freedom of the PROTACs, indicating the need for new optimization strategies. By integration of computational methods such as molecular dynamics simulations, this study investigates the role of the linker throughout the induction process, particularly its impact on the formation and stability of the ternary complex. This approach offers potential for overcoming the limitations of traditional strategies, reducing reliance on empirical methods, and enhancing the overall efficiency and effectiveness of PROTAC design.

An outlook on structural biology after AlphaFold: tools, limits and perspectives

AlphaFold and similar groundbreaking, AI-based tools, have revolutionized the field of structural bioinformatics, with their remarkable accuracy in ab-initio protein structure prediction. This success has catalyzed the development of new software and pipelines aimed at incorporating AlphaFold's predictions, often focusing on addressing the algorithm's remaining challenges. Here, we present the current landscape of structural bioinformatics shaped by AlphaFold, and discuss how the field is dynamically responding to this revolution, with new software, methods, and pipelines. While the excitement around AI-based tools led to their widespread application, it is essential to acknowledge that their practical success hinges on their integration into established protocols within structural bioinformatics, often neglected in the context of AI-driven advancements. Indeed, user-driven intervention is still as pivotal in the structure prediction process as in complementing state-of-the-art algorithms with functional and biological knowledge.

PROTAC-induced Protein Structural Dynamics in Targeted Protein Degradation

PROteolysis TArgeting Chimeras (PROTACs) are small molecules that induce target protein degradation via the ubiquitin-proteasome system. PROTACs recruit the target protein and E3 ligase; a critical first step is forming a ternary complex. However, while the formation a ternary complex is crucial, it may not always guarantee successful protein degradation. The dynamics of the PROTAC-induced degradation complex play a key role in ubiquitination and subsequent degradation. In this study, we computationally modelled protein complex structures and dynamics associated with a series of PROTACs featuring different linkers to investigate why these PROTACs, all of which formed ternary complexes with Cereblon (CRBN) E3 ligase and the target protein bromodomain-containing protein 4 (BRD4 BD1 ), exhibited varying degrees of degradation potency. We constructed the degradation machinery complexes with Culling-Ring Ligase 4A (CRL4A) E3 ligase scaffolds. Through atomistic molecular dynamics simulations, we illustrated how PROTAC-dependent protein dynamics facilitating the arrangement of surface lysine residues of BRD4 BD1 into the catalytic pocket of E2/ubiquitin cascade for ubiquitination. Despite featuring identical warheads in this PROTAC series, the linkers were found to affect the residue-interaction networks, and thus governing the essential motions of the entire degradation machine for ubiquitination. These findings offer a structural dynamic perspective on ligand-induced protein degradation, providing insights to guide future PROTAC design endeavors.

Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding-based methodology

Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that 'stitches' the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode. Fragmenstein either takes the atomic coordinates of ligands from a experimental fragment screen and combines the atoms together to produce a novel merged virtual compound, or uses them to predict the bound complex for a provided molecule. The molecule is then energy minimised under strong constraints to obtain a structurally plausible conformer. The code is available at https://github.com/oxpig/Fragmenstein .Scientific contributionThis work shows the importance of using the coordinates of known binders when predicting the conformation of derivative molecules through a retrospective analysis of the COVID Moonshot data. This method has had a prior real-world application in hit-to-lead screening, yielding a sub-micromolar merger from parent hits in a single round. It is therefore likely to further benefit future drug design campaigns and be integrated in future pipelines.

PROTAC-DB 3.0: an updated database of PROTACs with extended pharmacokinetic parameters

Proteolysis-targeting chimera (PROTAC) is an emerging therapeutic technology that leverages the ubiquitin-proteasome system to target protein degradation. Due to its event-driven mechanistic characteristics, PROTAC has the potential to regulate traditionally non-druggable targets. Recently, AI-aided drug design has accelerated the development of PROTAC drugs. However, the rational design of PROTACs remains a considerable challenge. Here, we present an updated online database, PROTAC-DB 3.0. In this third version, we have expanded the database to include 6111 PROTACs (87% increase compared to the 2.0 version). Additionally, the database now contains 569 warheads (small molecules targeting the protein), 2753 linkers, and 107 E3 ligands (small molecules recruiting E3 ligases). The number of target-PROTAC-E3 ternary complex structures has also increased to 959. Recognizing the importance of druggability in PROTAC design, we have incorporated pharmacokinetic data to PROTAC-DB 3.0. To enhance user experience, we have added features for sorting based on molecular similarity and literature publication date. PROTAC-DB 3.0 is accessible at http://cadd.zju.edu.cn/protacdb/.

Design and optimization strategies of PROTACs and its Application, Comparisons to other targeted protein degradation for multiple oncology therapies

Recent years have witnessed notable breakthroughs in the field of biotherapeutics. Proteolysis Targeting Chimeras (PROTACs) are novel molecules which used to degrade particular proteins despite the blockage by small drug molecules, which leads to a predicted therapeutic activity. This is a unique finding, especially at the cellular level targets degradations. Clinical trials and studies on PROTACs are in progress for oncology indications for demonstration of high potency and activity. PROTAC molecules are having excellent tissue distribution properties and their capacity to mutate the proteins and target overexpressed. This concept has attained wide attention from modern researchers in oncological drug discovery with particular physical qualities not offered by other therapeutic approaches. The modular nature of the PROTACs enables their methodical optimization and logical design. A thorough review was conducted in order to delve deeper into the subject and gain a better understanding of its development, computational supports, important factors for the optimization of developed PROTAC candidates, pharmacokinetic and pharmacodynamic (PK-PD) aspects, safety risks such as the degradation of undesired proteins, and other PROTAC-related issues and their target immunotherapeutic response. Furthermore discussed about the benefits, possible challenges, viewpoints, comparison with other targeted protein degraders (LYTACs, AUTOTACs) and the most current research results of PROTACs technology in multiple oncology therapies. Abbreviations: PROTACs, Proteolysis Targeting Chimeras; PK, Pharmacokinetic; PD, Pharmacodynamic; MetAP-2, (methionine aminopeptidase 2); BCL6, B-cell lymphoma 6; GCN5, General Control Nonderepressible 5; BKT, Bruton's tyrosine kinase; BET, Bromodomain and extra-terminal; AR, Androgen or Androgen receptor; ER, Estrogen or Estrogen receptor; FDA, Food and Drug Administration; mCRPC, Metastatic castration-resistant prostate cancer; STAT3, Signal Transducer and Activator of Transcription 3; FAK, Focal adhesion kinase; POI, Protein of interest; PEG, Polyethylene glycol; UPS, Ubiquitin-Proteasome System; VHL, Von Hippel-Lindau; CRBN, Cereblon; MDM2, Mouse Double Minute 2 homologue; cIAP, Cellular Inhibitor of Apoptosis; RNF, Ring Finger Protein; BRD, Bromodomain; CDK, Cyclin-dependent kinase; PAMPA, Parallel Artificial Membrane Permeability studies; BRET, Bioluminescence Resonance Energy Transfer; MCL, Mantle cell lymphoma; MCL-1, Myeloid Cell Leukemia 1; BCL-XL, B-cell lymphoma extra-large; TRK, Tropomyosin Receptor Kinase; RTKs, Transmembrane Receptor Tyrosine Kinase; NTRK, Neurotrophic Tyrosine Receptor Kinase; DHT, Dihydrotestosterone; EGFR, Epidermal Growth Factor Receptor; EGFR-TKIs, EGFR tyrosine kinase inhibitors; NSCLC, non-small cell lung cancer; BCR, B-cell receptor; CML, Chronic myelogenous leukemia; TKI, Tyrosine kinase inhibitors; MoA, Mechanism of action; TPD, Targetted protein degraders; LYTACs, Lysosome targeting chimeras; ASGPR, Asialoglycoprotein receptor; AUTOTACs, Autophagy-Targeting Chimeras; ATTECs, Autophagy-tethering compounds; CRISPR-Cas9, Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR-associated protein 9; TALEN, Transcription Activator-Like Effector Nuclease; ZFN, Zinc Finger Nuclease.

Development of PROTACs targeting estrogen receptor: an emerging technique for combating endocrine resistance

Despite the success of endocrine therapies in treating ER-positive breast cancer, the development of resistance remains a significant challenge. Estrogen receptor targeting proteolysis-targeting chimeras (ER PROTACs) offer a unique approach by harnessing the ubiquitin-proteasome system to degrade ER, potentially bypassing resistance mechanisms. In this review, we present the drug design, efficacy and early clinical trials of these ER PROTACs. This review underscores the academic and industrial opportunities presented by this emerging technology, as well as the challenges that must be addressed to translate these findings into effective clinical therapies.

Rationalize the Functional Roles of Protein-Protein Interactions in Targeted Protein Degradation by Kinetic Monte Carlo Simulations

Targeted protein degradation is a promising therapeutic strategy to tackle disease-causing proteins that lack binding pockets for traditional small-molecule inhibitors. Its first step is to trigger the proximity between a ubiquitin ligase complex and a target protein through a heterobifunctional molecule, such as proteolysis targeting chimeras (PROTACs), leading to the formation of a ternary complex. The properties of protein-protein interactions play an important regulatory role during this process, which can be reflected by binding cooperativity. Unfortunately, although computer-aided drug design has become a cornerstone of modern drug development, the endeavor to model-targeted protein degradation is still in its infancy. The development of computational tools to understand the impacts of protein-protein interactions on targeted protein degradation, therefore, is highly demanded. To reach this goal, we constructed a nonredundant structural benchmark of the most updated ternary complexes and applied a kinetic Monte Carlo method to simulate the association between ligases and PROTAC-targeted proteins in the benchmark. Our results show that proteins in most complexes with positive cooperativity tend to associate into native-like configurations more often. In contrast, proteins very likely failed to associate into native-like configurations in complexes with negative cooperativity. Moreover, we compared protein-protein association through different interfaces generated from molecular docking. The native-like binding interface shows a higher association probability than all the other alternative interfaces only in the complex with positive cooperativity. These observations support the idea that the formation of ternary complexes is closely regulated by the binary interactions between proteins. Finally, we applied our method to cyclin-dependent kinases 4 and 6 (CDK4/6). We found that their interactions with the ligase are not as similar as their structures. Altogether, our study paves the way for understanding the role of protein-protein interactions in the PROTAC-induced ternary complex formation. It can potentially help in searching for degraders that selectively target specific proteins.

Development of PROTACs using computational approaches

Proteolysis-targeting chimeras (PROTACs) are drugs designed to degrade target proteins via the ubiquitin-proteasome system. With the application of computational biology/chemistry technique in drug design, numerous computer-aided drug design and artificial intelligence (AI)-driven drug design (CADD/AIDD) methods have recently emerged to facilitate the development of PROTAC drugs. We systematically review the role of in silico tools in PROTAC drug design, emphasizing how computational software can model PROTAC action and structure, predict activity, and assist in molecule design. We also discuss current challenges in the rational design of PROTACs from an in silico perspective, such as deviations from small-molecule druggability and the limited availability of training data. We provide an overview of recent discoveries and emerging research in this field, and discuss their potential impact on PROTAC design strategies.

Advances in designing ternary complexes: Integrating in-silico and biochemical methods for PROTAC optimisation in target protein degradation

Target protein degradation (TPD) is an emerging approach to mitigate disease-causing proteins. TPD contains several strategies, and one of the strategies that gained immersive importance in recent times is Proteolysis Targeting Chimeras (PROTACs); the PROTACs recruit small molecules to induce the poly-ubiquitination of disease-causing protein by hijacking the ubiquitin-proteasome system (UPS) by bringing the E3 ligase and protein of interest (POI) into appropriate proximity. The steps involved in designing and evaluating the PROTACs remain critical in optimising the PROTACs to degrade the POI. It is observed that using in-silico and biochemical methods to study the ternary complexes (TCs) of the POI-PROTAC-E3 ligase is essential to understanding the structural activity, cooperativity, and stability of formed TCs. A better understanding of the above-mentioned leads to an appropriate rationale for designing the PROTACs targeting the disease-causing proteins. In this review, we tried to summarise the approaches used to design the ternary complexes, i.e., in-silico and in-vitro methods, to understand the behaviour of the PROTAC-induced ternary complexes.

Targeted protein degradation: advances in drug discovery and clinical practice

Targeted protein degradation (TPD) represents a revolutionary therapeutic strategy in disease management, providing a stark contrast to traditional therapeutic approaches like small molecule inhibitors that primarily focus on inhibiting protein function. This advanced technology capitalizes on the cell's intrinsic proteolytic systems, including the proteasome and lysosomal pathways, to selectively eliminate disease-causing proteins. TPD not only enhances the efficacy of treatments but also expands the scope of protein degradation applications. Despite its considerable potential, TPD faces challenges related to the properties of the drugs and their rational design. This review thoroughly explores the mechanisms and clinical advancements of TPD, from its initial conceptualization to practical implementation, with a particular focus on proteolysis-targeting chimeras and molecular glues. In addition, the review delves into emerging technologies and methodologies aimed at addressing these challenges and enhancing therapeutic efficacy. We also discuss the significant clinical trials and highlight the promising therapeutic outcomes associated with TPD drugs, illustrating their potential to transform the treatment landscape. Furthermore, the review considers the benefits of combining TPD with other therapies to enhance overall treatment effectiveness and overcome drug resistance. The future directions of TPD applications are also explored, presenting an optimistic perspective on further innovations. By offering a comprehensive overview of the current innovations and the challenges faced, this review assesses the transformative potential of TPD in revolutionizing drug development and disease management, setting the stage for a new era in medical therapy.

How to target membrane proteins for degradation: Bringing GPCRs into the TPD fold

We are now in the middle of a so-called "fourth wave" of drug innovation: multispecific medicines aimed at diseases and targets previously thought to be "undruggable"; by inducing proximity between two or more proteins, for example, a target and an effector that do not naturally interact, such modalities have potential far beyond the scope of conventional drugs. In particular, targeted protein degradation (TPD) strategies to destroy disease-associated proteins have emerged as an exciting pipeline in drug discovery. Most efforts are focused on intracellular proteins, whereas membrane proteins have been less thoroughly explored despite the fact that they comprise roughly a quarter of the human proteome with G-protein coupled receptors (GPCRs) notably dysregulated in many diseases. Here, we discuss the opportunities and challenges of developing degraders for membrane proteins with a focus on GPCRs. We provide an overview of different TPD platforms in the context of membrane-tethered targets, and we present recent degradation technologies highlighting their potential application to GPCRs.

Characterizing the Cooperative Effect of PROTAC Systems with End-Point Binding Free Energy Calculation

Proteolytic targeting chimeras (PROTACs), as an emerging type of drug, function by proximity-based modalities that narrow the distance between a target protein and the E3 ubiquitin ligase to facilitate the ubiquitination labeling of the target protein for degradation. Although it is evidenced that the cooperativity of the PROTAC ternary interaction is one of the key factors affecting the degradation rate of a target protein, PROTAC design utilizing this indicator is still challenging because of the complicated/flexible interactions in a target-PROTAC-E3 ternary system. Therefore, developing reliable and practicable computational methods is of great interest for PROTAC design. Hence, in this study, we investigate the feasibility of using the end-point binding free energy calculation method, represented by molecular mechanics/Poisson-Boltzmann (generalized-Born) surface area (MM/PB(GB)SA), for characterizing cooperativity (including the stabilization and hook effects) of the PROTAC systems. The result shows that MM/GBSA is a good predictor in characterizing these effects under a relatively long molecular dynamics adjustment (50-100 ns) and low dielectric constant (εin = 1), with the Pearson correlation coefficient (rp) > 0.5 and 0.6 for the stabilization and hook effect, respectively. This study provides a feasible strategy for characterizing the cooperativity of the PROTAC systems, facilitating the rational design of PROTAC molecules.

Computational methods and key considerations for in silico design of proteolysis targeting chimera (PROTACs)

Proteolysis-targeting chimeras (PROTACs), as heterobifunctional molecules, have garnered significant attention for their ability to target previously undruggable proteins. Due to the challenges in obtaining crystal structures of PROTAC molecules in the ternary complex, a plethora of computational tools have been developed to aid in PROTAC design. These computational tools can be broadly classified into artificial intelligence (AI)-based or non-AI-based methods. This review aims to provide a comprehensive overview of the latest computational methods for the PROTAC design process, covering both AI and non-AI approaches, from protein selection to ternary complex modeling and prediction. Key considerations for in silico PROTAC design are discussed, along with additional considerations for deploying AI-based models. These considerations are intended to guide subsequent model development in the PROTAC design process. Finally, future directions and recommendations are provided.

Characteristic roadmap of linker governs the rational design of PROTACs

Proteolysis targeting chimera (PROTAC) technology represents a groundbreaking development in drug discovery, leveraging the ubiquitin‒proteasome system to specifically degrade proteins responsible for the disease. PROTAC is characterized by its unique heterobifunctional structure, which comprises two functional domains connected by a linker. The linker plays a pivotal role in determining PROTAC's biodegradative efficacy. Advanced and rationally designed functional linkers for PROTAC are under development. Nonetheless, the correlation between linker characteristics and PROTAC efficacy remains under-investigated. Consequently, this study will present a multidisciplinary analysis of PROTAC linkers and their impact on efficacy, thereby guiding the rational design of linkers. We will primarily discuss the structural types and characteristics of PROTAC linkers, and the optimization strategies used for their rational design. Furthermore, we will discuss how factors like linker length, group type, flexibility, and linkage site affect the biodegradation efficiency of PROTACs. We believe that this work will contribute towards the advancement of rational linker design in the PROTAC research area.

Rationalize the Functional Roles of Protein-Protein Interactions in Targeted Protein Degradation by Kinetic Monte-Carlo Simulations

Targeted protein degradation is a promising therapeutic strategy to tackle disease-causing proteins that lack binding pockets for traditional small-molecule inhibitors. Its first step is to trigger the proximity between a ubiquitin ligase complex and a target protein through a heterobifunctional molecule, such as proteolysis targeting chimeras (PROTACs), leading to the formation of a ternary complex. The properties of protein-protein interactions play an important regulatory role during this process, which can be reflected by binding cooperativity. Unfortunately, although computer-aided drug design has become a cornerstone of modern drug development, the endeavor to model targeted protein degradation is still in its infancy. The development of computational tools to understand the impacts of protein-protein interactions on targeted protein degradation, therefore, is highly demanded. To reach this goal, we constructed a non-redundant structural benchmark of the most updated ternary complexes and applied a kinetic Monte-Carlo method to simulate the association between ligases and PROTAC-targeted proteins in the benchmark. Our results show that proteins in most complexes with positive cooperativity tend to associate into native-like configurations more often. In contrast, proteins very likely failed to associate into native-like configurations in complexes with negative cooperativity. Moreover, we compared the protein-protein association through different interfaces generated from molecular docking. The native-like binding interface shows a higher association probability than all the other alternative interfaces only in the complex with positive cooperativity. These observations support the idea that the formation of ternary complexes is closely regulated by the binary interactions between proteins. Finally, we applied our method to cyclin-dependent kinases 4 and 6 (CDK4/6). We found that their interactions with the ligase are not as similar as their structures. Altogether, our study paves the way for understanding the role of protein-protein interactions in PROTACE-induced ternary complex formation. It can potentially help in searching for degraders that selectively target specific proteins.

DNA-templated spatially controlled proteolysis targeting chimeras for CyclinD1-CDK4/6 complex protein degradation

Constraining proximity-based drugs, such as proteolysis-targeting chimeras (PROTACs), into its bioactive conformation can significantly impact their selectivity and potency. However, traditional methods for achieving this often involve complex and time-consuming synthetic procedures. Here, we introduced an alternative approach by demonstrating DNA-templated spatially controlled PROTACs (DTACs), which leverage the programmability of nucleic-acid based self-assembly for efficient synthesis, providing precise control over inhibitors' spacing and orientation. The resulting constructs revealed distance- and orientation-dependent selectivity and degradation potency for the CyclinD1-CDK4/6 protein complex in cancer cells. Notably, an optimal construct DTAC-V1 demonstrated the unprecedented synchronous degradation of entire CyclinD1-CDK4/6 complex. This resulted in the effective cell cycle arrest in G1 phase, and further therapeutic studies showed its potent anti-tumor effects compared to inhibitors alone. These findings present a novel framework for PROTACs design, offering critical insights that may inform the development of other proximity-induced therapeutic modalities.

Targeted Protein Degradation (TPD) for Immunotherapy: Understanding Proteolysis Targeting Chimera-Driven Ubiquitin-Proteasome Interactions

Targeted protein degradation or TPD, is rapidly emerging as a treatment that utilizes small molecules to degrade proteins that cause diseases. TPD allows for the selective removal of disease-causing proteins, including proteasome-mediated degradation, lysosome-mediated degradation, and autophagy-mediated degradation. This approach has shown great promise in preclinical studies and is now being translated to treat numerous diseases, including neurodegenerative diseases, infectious diseases, and cancer. This review discusses the latest advances in TPD and its potential as a new chemical modality for immunotherapy, with a special focus on the innovative applications and cutting-edge research of PROTACs (Proteolysis TArgeting Chimeras) and their efficient translation from scientific discovery to technological achievements. Our review also addresses the significant obstacles and potential prospects in this domain, while also offering insights into the future of TPD for immunotherapeutic applications.

Benchmarking Methods for PROTAC Ternary Complex Structure Prediction

Proteolysis targeting chimeras (PROTACs) are bifunctional compounds that recruit an E3 ligase to a target protein to induce ubiquitination and degradation of the target. Rational optimization of PROTAC requires a structural model of the ternary complex. In the absence of an experimental structure, computational tools have emerged that attempt to predict PROTAC ternary complexes. Here, we systematically benchmark three commonly used tools: PRosettaC, MOE, and ICM. We find that these PROTAC-focused methods produce an array of ternary complex structures, including some that are observed experimentally, but also many that significantly deviate from the crystal structure. Molecular dynamics simulations show that PROTAC complexes may exist in a multiplicity of configurational states and question the use of experimentally observed structures as a reference for accurate predictions. The pioneering computational tools benchmarked here highlight the promises and challenges in the field and may be more valuable when guided by clear structural and biophysical data. The benchmarking data set that we provide may also be valuable for evaluating other and future computational tools for ternary complex modeling.

DiffPROTACs is a deep learning-based generator for proteolysis targeting chimeras

PROteolysis TArgeting Chimeras (PROTACs) has recently emerged as a promising technology. However, the design of rational PROTACs, especially the linker component, remains challenging due to the absence of structure-activity relationships and experimental data. Leveraging the structural characteristics of PROTACs, fragment-based drug design (FBDD) provides a feasible approach for PROTAC research. Concurrently, artificial intelligence-generated content has attracted considerable attention, with diffusion models and Transformers emerging as indispensable tools in this field. In response, we present a new diffusion model, DiffPROTACs, harnessing the power of Transformers to learn and generate new PROTAC linkers based on given ligands. To introduce the essential inductive biases required for molecular generation, we propose the O(3) equivariant graph Transformer module, which augments Transformers with graph neural networks (GNNs), using Transformers to update nodes and GNNs to update the coordinates of PROTAC atoms. DiffPROTACs effectively competes with existing models and achieves comparable performance on two traditional FBDD datasets, ZINC and GEOM. To differentiate the molecular characteristics between PROTACs and traditional small molecules, we fine-tuned the model on our self-built PROTACs dataset, achieving a 93.86% validity rate for generated PROTACs. Additionally, we provide a generated PROTAC database for further research, which can be accessed at https://bailab.siais.shanghaitech.edu.cn/service/DiffPROTACs-generated.tgz. The corresponding code is available at https://github.com/Fenglei104/DiffPROTACs and the server is at https://bailab.siais.shanghaitech.edu.cn/services/diffprotacs.

[Protein induced proximity and targeted degradations by new degraders: concepts, developments, challenges for clinical applications]

The review is focused on recent drug discovery advances based on targeted protein degradation strategies. This new area of research has exploded leading to the development of potential drugs useful in a large variety of human diseases. They first target disease relevant proteins difficult to counteract with other classical strategies and extend now to aggregates, organelles, nucleic acids or lipidic droplets. These degraders engaged either the ubiquitin-proteasome system for PROTACs and molecular glues (first generation), or the lysosomal system via endosome-lysosome degradation (LYTACs) and autophagy-lysosome degradation (ATTEC, AUTAC, AUTOTAC) (following generations of degraders). PROTACs have expanded from the orthodox heterobifunctional ones to new derivatives such as homo-PROTACs, pro-PROTACs, CLIPTACs, HaloPROTACs, PHOTOTACs, Bac-PROTACs, AbTACs, ARN-PROTACs. The small molecular-weight molecular glues induce the formation of new ternary complexes which implicate the targeted protein and an ubiquitin ligase E3 allowing the protein ubiquinitation followed by its proteasomal degradation. Lysosomal degraders (LYTAC, ATTEC, AUTAC, AUTOTAC) specifically recognize extracellular and membrane proteins or dysfunctional organelles and transport them into lysosomes where they are degraded. They overcome the limitations observed with proteasomal degradations induced by PROTAC and molecular glues and demonstrate their potential to treat human diseases, especially neurodegenerative ones. Pharmaceutical companies are engaged at the world level to develop these new potential drugs targeting cancers, immuno-inflammatory and neurodegenerative diseases as well as a variety of other ones. Efficiency and risks for these novel therapeutic strategies are discussed.

Structural Basis of Conformational Dynamics in the PROTAC-Induced Protein Degradation

Pronounced conformational dynamics is unveiled upon analyzing multiple crystal structures of the same proteins recruited to the same E3 ligases by PROTACs, and yet, is largely permissive for targeted protein degradation due to the intrinsic mobility of E3 assemblies creating a large ubiquitylation zone. Mathematical modelling of ternary dynamics on ubiquitylation probability confirms the experimental finding that ternary complex rigidification need not correlate with enhanced protein degradation. Salt bridges are found to prevail in the PROTAC-induced ternary complexes, and may contribute to a positive cooperativity and prolonged half-life. The analysis highlights the importance of presenting lysines close to the active site of the E2 enzyme while constraining ternary dynamics in PROTAC design to achieve high degradation efficiency.

Application and challenges of nitrogen heterocycles in PROTAC linker

The absence of effective active pockets makes traditional molecularly targeted drug strategies ineffective against 80 % of human disease-related proteins. The PROTAC technology effectively makes up for the deficiency of traditional molecular targeted drugs, which produces drug activity by degrading rather than inhibiting the target protein. The degradation of PROTAC is not only affected by POI ligand and E3 ligand, but by the selection of suitable linker which can play an important role in the efficiency and selectivity of the degradation. In the early exploring stage of the PROTAC, flexible chains were priorly applied as the linker of PROTAC. Although PROTAC with flexible chains as linkers sometimes perform well in vitro bioactivity evaluations, the introduction of lipophilic flexible chains reduces the hydrophilicity of these molecules, resulting in generally poor pharmacokinetic characteristics and pharmacological activities in vivo. In addition, recent reports have also shown that some PROTAC with flexible chains have some risks to causing hemolysis in vivo. Therefore, PROTAC with flexible chains show less druggability and large difficulty to entering the clinical trial stage. On the other hand, the application of nitrogen heterocycles in the design of PROTAC linkers has been widely reported in recent years. More and more reports have shown that the introduction of nitrogen heterocycles in the linker not only can effectively improves the metabolism of PROTAC in vivo, but also can enhance the degradation efficiency and selectivity of PROTAC. These PROTAC with nitrogen heterocycle linkers have attracted much attention of pharmaceutical chemists. The introduction of nitrogen heterocycles in the linker deserves priority consideration in the primary design of the PROTAC based on various druggabilities including pharmacokinetic characteristics and pharmacological activity. In this work, we summarized the optimization process and progress of nitrogen heterocyclic rings as the PROTAC linker in recent years. However, there were still limited understanding of how to discover, design and optimize PROTAC. For example, the selection of the types of nitrogen heterocycles and the optimization sites of this linker are challenges for researchers, choosing between four to six-membered nitrogen heterocycles, selecting from saturated to unsaturated ones, and even optimizing the length and extension angle of the linker. There is a truly need for theoretical explanation and elucidation of the PROTAC to guide the developing of more effective and valuable PROTAC.

PROTACable Is an Integrative Computational Pipeline of 3-D Modeling and Deep Learning To Automate the De Novo Design of PROTACs

Proteolysis-targeting chimeras (PROTACs) that engage two biological targets at once are a promising technology in degrading clinically relevant protein targets. Since factors that influence the biological activities of PROTACs are more complex than those of a small molecule drug, we explored a combination of computational chemistry and deep learning strategies to forecast PROTAC activity and enable automated design. A new method named PROTACable was developed for the de novo design of PROTACs, which includes a robust 3-D modeling workflow to model PROTAC ternary complexes using a library of E3 ligase and linker and an SE(3)-equivariant graph transformer network to predict the activity of newly designed PROTACs. PROTACable is available at https://github.com/giaguaro/PROTACable/.

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.

Discovery of Novel Potent and Fast BTK PROTACs for the Treatment of Osteoclasts-Related Inflammatory Diseases

Bruton's tyrosine kinase (BTK) is an attractive target in inflammatory and autoimmune diseases. However, the effectiveness of BTK inhibitors is limited by side effects and drug resistance. In this study, we report the development of novel BTK proteolysis targeting chimeras (PROTACs) with different classes of BTK-targeting ligands (e.g., spebrutinib) other than ibrutinib. Compound 23 was identified as a potent and fast BTK PROTAC degrader, exhibiting outstanding degradation potency and efficiency in Mino cells (DC50, 4 h = 1.29 ± 0.3 nM, t1/2, 20 nM = 0.59 ± 0.20 h). Furthermore, compound 23 forms a stable ternary complex, as confirmed by the HTRF assay. Notably, 23 down-regulated the BTK-PLCγ2-Ca2+-NFATc1 signaling pathway activated by RANKL, thus inhibiting osteoclastogenesis and attenuating alveolar bone resorption in a mouse periodontitis model. These findings suggest that compound 23 is a potent and promising candidate for osteoclast-related inflammatory diseases, expanding the potential of BTK PROTACs.

Design and Evaluation of PROTACs Targeting Acyl Protein Thioesterase 1

PROTAC linker design remains mostly an empirical task. We employed the PRosettaC computational software in the design of sulfonyl-fluoride-based PROTACs targeting acyl protein thioesterase 1 (APT1). The software efficiently generated ternary complex models from empirically-designed PROTACs and suggested alkyl linkers to be the preferred type of linker to target APT1. Western blotting analysis revealed efficient degradation of APT1 and activity-based protein profiling showed remarkable selectivity of an alkyl linker-based PROTAC amongst serine hydrolases. Collectively, our data suggests that combining PRosettaC and chemoproteomics can effectively assist in triaging PROTACs for synthesis and providing early data on their potency and selectivity.

Journey of Von Hippel-Lindau (VHL) E3 ligase in PROTACs design: From VHL ligands to VHL-based degraders

The scientific community has shown considerable interest in proteolysis-targeting chimeras (PROTACs) in the last decade, indicating their remarkable potential as a means of achieving targeted protein degradation (TPD). Not only are PROTACs seen as valuable tools in molecular biology but their emergence as a modality for drug discovery has also garnered significant attention. PROTACs bind to E3 ligases and target proteins through respective ligands connected via a linker to induce proteasome-mediated protein degradation. The discovery of small molecule ligands for E3 ligases has led to the prevalent use of various E3 ligases in PROTAC design. Furthermore, the incorporation of different types of linkers has proven beneficial in enhancing the efficacy of PROTACs. By far more than 3300 PROTACs have been reported in the literature. Notably, Von Hippel-Lindau (VHL)-based PROTACs have surfaced as a propitious strategy for targeting proteins, even encompassing those that were previously considered non-druggable. VHL is extensively utilized as an E3 ligase in the advancement of PROTACs owing to its widespread expression in various tissues and well-documented binders. Here, we review the discovery of VHL ligands, the types of linkers employed to develop VHL-based PROTACs, and their subsequent modulation to design advanced non-conventional degraders to target various disease-causing proteins. Furthermore, we provide an overview of other E3 ligases recruited in the field of PROTAC technology.

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.

Targeted degrader technologies as prospective SARS-CoV-2 therapies

COVID-19 remains a severe public health threat despite the WHO declaring an end to the public health emergency in May 2023. Continual development of SARS-CoV-2 variants with resistance to vaccine-induced or natural immunity necessitates constant vigilance as well as new vaccines and therapeutics. Targeted protein degradation (TPD) remains relatively untapped in antiviral drug discovery and holds the promise of attenuating viral resistance development. From a unique structural design perspective, this review covers antiviral degrader merits and challenges by highlighting key coronavirus protein targets and their co-crystal structures, specifically illustrating how TPD strategies can refine existing SARS-CoV-2 3CL protease inhibitors to potentially produce superior protease-degrading agents.

Revolutionizing Drug Targeting Strategies: Integrating Artificial Intelligence and Structure-Based Methods in PROTAC Development

PROteolysis TArgeting Chimera (PROTAC) is an emerging technology in chemical biology and drug discovery. This technique facilitates the complete removal of the target proteins that are "undruggable" or challenging to target through chemical molecules via the Ubiquitin-Proteasome System (UPS). PROTACs have been widely explored and outperformed not only in cancer but also in other diseases. During the past few decades, several academic institutes and pharma companies have poured more efforts into PROTAC-related technologies, setting the stage for several major degrader trial readouts in clinical phases. Despite their promising results, the formation of robust ternary orientation, off-target activity, poor permeability, and binding affinity are some of the limitations that hinder their development. Recent advancements in computational technologies have facilitated progress in the development of PROTACs. Researchers have been able to utilize these technologies to explore a wider range of E3 ligases and optimize linkers, thereby gaining a better understanding of the effectiveness and safety of PROTACs in clinical settings. In this review, we briefly explore the computational strategies reported to date for the formation of PROTAC components and discuss the key challenges and opportunities for further research in this area.

Discovery of PVD-06 as a Subtype-Selective and Efficient PTPN2 Degrader

Protein tyrosine phosphatase nonreceptor Type 2 (PTPN2) is an attractive target for cancer immunotherapy. PTPN2 and another subtype of PTP1B are highly similar in structure, but their biological functions are distinct. Therefore, subtype-selective targeting of PTPN2 remains a challenge for researchers. Herein, the development of small molecular PTPN2 degraders based on a thiadiazolidinone dioxide-naphthalene scaffold and a VHL E3 ligase ligand is described, and the PTPN2/PTP1B subtype-selective degradation is achieved for the first time. The linker structure modifications led to the discovery of the subtype-selective PTPN2 degrader PVD-06 (PTPN2/PTP1B selective index > 60-fold), which also exhibits excellent proteome-wide degradation selectivity. PVD-06 induces PTPN2 degradation in a ubiquitination- and proteasome-dependent manner. It efficiently promotes T cell activation and amplifies IFN-γ-mediated B16F10 cell growth inhibition. This study provides a convenient chemical knockdown tool for PTPN2-related research and a paradigm for subtype-selective PTP degradation through nonspecific substrate-mimicking ligands, demonstrating the therapeutic potential of PTPN2 subtype-selective degradation.

Rational Prediction of PROTAC-Compatible Protein-Protein Interfaces by Molecular Docking

Proteolysis targeting chimeras (PROTACs) are heterobifunctional ligands that mediate the interaction between a protein target and an E3 ligase, resulting in a ternary complex, whose interaction with the ubiquitination machinery leads to target degradation. This technology is emerging as an exciting new avenue for therapeutic development, with several PROTACs currently undergoing clinical trials targeting cancer. Here, we describe a general and computationally efficient methodology combining restraint-based docking, energy-based rescoring, and a filter based on the minimal solvent-accessible surface distance to produce PROTAC-compatible PPIs suitable for when there is no a priori known PROTAC ligand. In a benchmark employing a manually curated data set of 13 ternary complex crystals, we achieved an accuracy of 92% when starting from bound structures and 77% when starting from unbound structures, respectively. Our method only requires that the ligand-bound structures of the monomeric forms of the E3 ligase and target proteins be given to run, making it general, accurate, and highly efficient, with the ability to impact early-stage PROTAC-based drug design campaigns where no structural information about the ternary complex structure is available.

Targeted Protein Degradation: Advances, Challenges, and Prospects for Computational Methods

The therapeutic approach of targeted protein degradation (TPD) is gaining momentum due to its potentially superior effects compared with protein inhibition. Recent advancements in the biotech and pharmaceutical sectors have led to the development of compounds that are currently in human trials, with some showing promising clinical results. However, the use of computational tools in TPD is still limited, as it has distinct characteristics compared with traditional computational drug design methods. TPD involves creating a ternary structure (protein-degrader-ligase) responsible for the biological function, such as ubiquitination and subsequent proteasomal degradation, which depends on the spatial orientation of the protein of interest (POI) relative to E2-loaded ubiquitin. Modeling this structure necessitates a unique blend of tools initially developed for small molecules (e.g., docking) and biologics (e.g., protein-protein interaction modeling). Additionally, degrader molecules, particularly heterobifunctional degraders, are generally larger than conventional small molecule drugs, leading to challenges in determining drug-like properties like solubility and permeability. Furthermore, the catalytic nature of TPD makes occupancy-based modeling insufficient. TPD consists of multiple interconnected yet distinct steps, such as POI binding, E3 ligase binding, ternary structure interactions, ubiquitination, and degradation, along with traditional small molecule properties. A comprehensive set of tools is needed to address the dynamic nature of the induced proximity ternary complex and its implications for ubiquitination. In this Perspective, we discuss the current state of computational tools for TPD. We start by describing the series of steps involved in the degradation process and the experimental methods used to characterize them. Then, we delve into a detailed analysis of the computational tools employed in TPD. We also present an integrative approach that has proven successful for degrader design and its impact on project decisions. Finally, we examine the future prospects of computational methods in TPD and the areas with the greatest potential for impact.

Elucidation of genome-wide understudied proteins targeted by PROTAC-induced degradation using interpretable machine learning

Proteolysis-targeting chimeras (PROTACs) are hetero-bifunctional molecules that induce the degradation of target proteins by recruiting an E3 ligase. PROTACs have the potential to inactivate disease-related genes that are considered undruggable by small molecules, making them a promising therapy for the treatment of incurable diseases. However, only a few hundred proteins have been experimentally tested for their amenability to PROTACs, and it remains unclear which other proteins in the entire human genome can be targeted by PROTACs. In this study, we have developed PrePROTAC, an interpretable machine learning model based on a transformer-based protein sequence descriptor and random forest classification. PrePROTAC predicts genome-wide targets that can be degraded by CRBN, one of the E3 ligases. In the benchmark studies, PrePROTAC achieved a ROC-AUC of 0.81, an average precision of 0.84, and over 40% sensitivity at a false positive rate of 0.05. When evaluated by an external test set which comprised proteins from different structural folds than those in the training set, the performance of PrePROTAC did not drop significantly, indicating its generalizability. Furthermore, we developed an embedding SHapley Additive exPlanations (eSHAP) method, which extends conventional SHAP analysis for original features to an embedding space through in silico mutagenesis. This method allowed us to identify key residues in the protein structure that play critical roles in PROTAC activity. The identified key residues were consistent with existing knowledge. Using PrePROTAC, we identified over 600 novel understudied proteins that are potentially degradable by CRBN and proposed PROTAC compounds for three novel drug targets associated with Alzheimer's disease.

Methods for computer-assisted PROTAC design

Proximity-induced pharmacology is an emerging field in chemical biology and drug discovery where a small molecule induces non-natural interactions between two proteins, leading to specific phenotypic responses. Proteolysis targeting chimeras (PROTACs) are the most mature examples, where ligands for an E3 ligase and a target protein are linked to induce the ubiquitination and subsequent degradation of the target. The discovery of PROTACs typically relies on a trial-and-error approach where chemical handles and linker chemistry, length and attachment points are systematically varied in the hope that one of the combinations will produce an active molecule. Novel computational methods and tools are developed in an attempt to rationalize and accelerate this process and differ significantly from traditional structure-based drug design approaches. In this chapter, we review three different solutions for computer-assisted PROTAC design: MOE, ICM and PRosettaC. Specifically, we describe protocols to predict the structure of ternary complexes (E3 ligase-PROTAC-target protein) and to screen virtually libraries of PROTAC candidates. We also provide troubleshooting tips. Rational PROTAC design is still in its infancy. By opening this space to users and developers, we hope that this methods article will contribute to much needed advancement in the field.

Affinity and cooperativity modulate ternary complex formation to drive targeted protein degradation

Targeted protein degradation via "hijacking" of the ubiquitin-proteasome system using proteolysis targeting chimeras (PROTACs) has evolved into a novel therapeutic modality. The design of PROTACs is challenging; multiple steps involved in PROTAC-induced degradation make it difficult to establish coherent structure-activity relationships. Herein, we characterize PROTAC-mediated ternary complex formation and degradation by employing von Hippel-Lindau protein (VHL) recruiting PROTACs for two different target proteins, SMARCA2 and BRD4. Ternary-complex attributes and degradation activity parameters are evaluated by varying components of the PROTAC's architecture. Ternary complex binding affinity and cooperativity correlates well with degradation potency and initial rates of degradation. Additionally, we develop a ternary-complex structure modeling workflow to calculate the total buried surface area at the interface, which is in agreement with the measured ternary complex binding affinity. Our findings establish a predictive framework to guide the design of potent degraders.