Back to search

Article

Machine learning modeling of protein-intrinsic features predicts tractability of targeted protein degradation

2021-09-29

Abstract excerpt

Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell’s endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by TPD approaches, termed “degradability”, is largely unknown. Recent systematic studies to map the degradable kinome have shown differences in degradation between kinas...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
170e44ed-5392-5b84-b8cb-4a50dad058db
DOI
10.1101/2021.09.27.462040
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Machine learning modeling of protein-intrinsic features predicts tractability of targeted protein degradationDOI 10.1101/2021.09.27.462040
Select a neighboring publication to make it the new centre.