Advancing Targeted Protein Degradation Via Multiomics Profiling and Artificial Intelligence

Overview

Journal J Am Chem Soc

Publisher American Chemical Society

Specialty Chemistry

Date 2023 Jan 27

PMID 36706315

Authors

Miquel Duran-Frigola

Marko Cigler

Georg E Winter

Affiliations

Soon will be listed here.

Abstract

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.

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