Molecular Glue Degraders: Induced Proximity, E3 Ligase Hijacking, and the Path to Clinic

For decades, the pharmaceutical industry has relied on occupancy-driven pharmacology, heavily utilizing small molecules to bind defined hydrophobic active sites—a paradigm that has systematically failed to address over 80% of the human proteome. In response, Targeted Protein Degradation (TPD) has emerged as a disruptive, event-driven pharmacological modality. By hijacking the cell's intrinsic ubiquitin-proteasome system (UPS), TPD bypasses the need for functional active sites, forcing the elimination of previously "undruggable" disease-causing proteins. This comprehensive review systematically deconstructs the current landscape and future trajectory of molecular glue degraders (MGDs). Unlike massive, heterobifunctional PROTACs, molecular glues represent a monovalent, low-molecular-weight approach to induced proximity, offering superior drug-like properties, straightforward oral dosing, and excellent tissue distribution. Key areas of critical evaluation within this manuscript include: Mechanistic Foundations: An exploration of the thermodynamics and kinetics governing transient ternary complex formation (E3-Glue-Target), thermodynamic avidity, and the precise structural determinants (such as \beta-hairpin loops and degron motifs) required for neosubstrate recruitment. Structural Biology of E3 Ligases: A detailed analysis of the CRBN-CRL4 axis (IMiDs and targets like IKZF1/3 and GSPT1), the DCAF15-DDB1 axis (Indisulam and RBM39), and the methodological challenges of predicting target repertoires. Clinical Translation & Toxicity: A critical appraisal of current clinical pipelines, exposing the severe methodological vulnerabilities of relying on classical maximum tolerated dose (MTD) trial designs for catalytic drugs. It addresses the unpredictable off-target neosubstrate degradation that poses the single greatest regulatory threat to modern glue pipelines. Manufacturing Bottlenecks: An evaluation of the unprecedented chemistry, manufacturing, and controls (CMC) complexities. The review highlights the necessity for digital twin continuous manufacturing models to handle MGDs as highly potent active pharmaceutical ingredients (HPAPIs). Ultimately, this review establishes a stringent, forward-looking blueprint for transitioning molecular glue discovery from a history of serendipitous phenotypic screening to deterministic, rational, and AI-driven structure-based drug design.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-12
DOI
https://doi.org/10.5281/zenodo.20670138
Primary Topic
Protein Degradation and Inhibitors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Molecular Glue Degraders: Induced Proximity, E3 Ligase Hijacking, and the Path to Clinic

barot netra
Zenodo (CERN European Organization for Nuclear Research)
Protein Degradation and Inhibitors
article

Molecular Glue Degraders: Induced Proximity, E3 Ligase Hijacking, and the Path to Clinic

barot netra
article en

Abstract

For decades, the pharmaceutical industry has relied on occupancy-driven pharmacology, heavily utilizing small molecules to bind defined hydrophobic active sites—a paradigm that has systematically failed to address over 80% of the human proteome. In response, Targeted Protein Degradation (TPD) has emerged as a disruptive, event-driven pharmacological modality. By hijacking the cell's intrinsic ubiquitin-proteasome system (UPS), TPD bypasses the need for functional active sites, forcing the elimination of previously "undruggable" disease-causing proteins. This comprehensive review systematically deconstructs the current landscape and future trajectory of molecular glue degraders (MGDs). Unlike massive, heterobifunctional PROTACs, molecular glues represent a monovalent, low-molecular-weight approach to induced proximity, offering superior drug-like properties, straightforward oral dosing, and excellent tissue distribution. Key areas of critical evaluation within this manuscript include: Mechanistic Foundations: An exploration of the thermodynamics and kinetics governing transient ternary complex formation (E3-Glue-Target), thermodynamic avidity, and the precise structural determinants (such as \beta-hairpin loops and degron motifs) required for neosubstrate recruitment. Structural Biology of E3 Ligases: A detailed analysis of the CRBN-CRL4 axis (IMiDs and targets like IKZF1/3 and GSPT1), the DCAF15-DDB1 axis (Indisulam and RBM39), and the methodological challenges of predicting target repertoires. Clinical Translation & Toxicity: A critical appraisal of current clinical pipelines, exposing the severe methodological vulnerabilities of relying on classical maximum tolerated dose (MTD) trial designs for catalytic drugs. It addresses the unpredictable off-target neosubstrate degradation that poses the single greatest regulatory threat to modern glue pipelines. Manufacturing Bottlenecks: An evaluation of the unprecedented chemistry, manufacturing, and controls (CMC) complexities. The review highlights the necessity for digital twin continuous manufacturing models to handle MGDs as highly potent active pharmaceutical ingredients (HPAPIs). Ultimately, this review establishes a stringent, forward-looking blueprint for transitioning molecular glue discovery from a history of serendipitous phenotypic screening to deterministic, rational, and AI-driven structure-based drug design.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 9%
Protein Degradation and Inhibitors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.