PROflow: An iterative refinement model for PROTAC-induced structure prediction

TL;DR

PROflow is a novel iterative refinement model that predicts PROTAC-induced protein complex structures by modeling full PROTAC flexibility, outperforming existing methods and enabling large-scale design screening.

Contribution

It introduces a pseudo-data generation scheme and a new iterative refinement approach for accurate PROTAC-induced structure prediction.

Findings

PROflow outperforms state-of-the-art docking methods.

It achieves statistically significant correlations with degradation activities.

Enables large-scale screening of PROTAC designs.

Abstract

Proteolysis targeting chimeras (PROTACs) are small molecules that trigger the breakdown of traditionally ``undruggable'' proteins by binding simultaneously to their targets and degradation-associated proteins. A key challenge in their rational design is understanding their structural basis of activity. Due to the lack of crystal structures (18 in the PDB), existing PROTAC docking methods have been forced to simplify the problem into a distance-constrained protein-protein docking task. To address the data issue, we develop a novel pseudo-data generation scheme that requires only binary protein-protein complexes. This new dataset enables PROflow, an iterative refinement model for PROTAC-induced structure prediction that models the full PROTAC flexibility during constrained protein-protein docking. PROflow outperforms the state-of-the-art across docking metrics and runtime. Its inference speed enables the large-scale screening of PROTAC designs, and computed properties of predicted structures achieve statistically significant correlations with published degradation activities.