Disease-guided targeted protein degradation and clearance: matching strategies to pathological protein states
- 1Department of Pharmacy, The First Affiliated Hospital of Harbin Medical University , , ,
- 2Jiangsu Key Laboratory of Drug Design and Optimization, Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University , , ,
Abstract
Targeted protein degradation (TPD) and related targeted-clearance strategies expand therapeutic opportunities by eliminating disease-associated proteins and, in selected settings, damaged organelles. Rather than organizing the field by degrader modality or disease lineage, this review uses the dominant pathological state of the disease-causing species as the unit of analysis. We classify targets along three higher-order dimensions-abundance/functional, physical, and spatial/compartmental state-and resolve them into five operational categories: elevated abundance or aberrant dependency; persistent activation, gain-of-function alterations, or resistance mutations; misfolding or pathological conformations; oligomerization, fibril formation, or insoluble aggregation; and mislocalization, abnormal cell-surface presentation, or organelle damage. Across molecular glues, heterobifunctional degraders, endocytic-lysosomal systems, and autophagy-based approaches, we examine how pathological state constrains recognition chemistry, molecular accessibility, clearance-route compatibility, tissue exposure, and pharmacodynamic assessment. The 2026 approval of vepdegestrant represents an important milestone in the clinical translation of heterobifunctional protein degradation and highlights the therapeutic potential of targeted degradation strategies. We propose a pathological-state-clearance pathway-biomarker framework to guide modality selection, medicinal-chemistry optimization, mechanistic validation, and patient stratification.
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BibTeX
@article{wang2026diseaseguided,
title = {{Disease-guided targeted protein degradation and clearance: matching strategies to pathological protein states}},
author = {Tianyu Wang and Chenbo Ji and Tianyu Zhao},
journal = {Frontiers in medicine},
year = {2026},
month = oct,
doi = {10.3389/fmed.2026.1967704},
url = {https://europepmc.org/article/PMC/PMC13717144},
note = {CC BY},
}
RIS
TY - JOUR
TI - Disease-guided targeted protein degradation and clearance: matching strategies to pathological protein states
AU - Tianyu Wang
AU - Chenbo Ji
AU - Tianyu Zhao
PY - 2026
DA - 2026/10/15
JO - Frontiers in medicine
DO - 10.3389/fmed.2026.1967704
UR - https://europepmc.org/article/PMC/PMC13717144
AB - Targeted protein degradation (TPD) and related targeted-clearance strategies expand therapeutic opportunities by eliminating disease-associated proteins and, in selected settings, damaged organelles. Rather than organizing the field by degrader modality or disease lineage, this review uses the dominant pathological state of the disease-causing species as the unit of analysis. We classify targets along three higher-order dimensions-abundance/functional, physical, and spatial/compartmental state-and resolve them into five operational categories: elevated abundance or aberrant dependency; persistent activation, gain-of-function alterations, or resistance mutations; misfolding or pathological conformations; oligomerization, fibril formation, or insoluble aggregation; and mislocalization, abnormal cell-surface presentation, or organelle damage. Across molecular glues, heterobifunctional degraders, endocytic-lysosomal systems, and autophagy-based approaches, we examine how pathological state constrains recognition chemistry, molecular accessibility, clearance-route compatibility, tissue exposure, and pharmacodynamic assessment. The 2026 approval of vepdegestrant represents an important milestone in the clinical translation of heterobifunctional protein degradation and highlights the therapeutic potential of targeted degradation strategies. We propose a pathological-state-clearance pathway-biomarker framework to guide modality selection, medicinal-chemistry optimization, mechanistic validation, and patient stratification.
SN - 2296-858X
ER -