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

• URL: http://arxiv.org/abs/2405.06654v1
• Date: Wed, 10 Apr 2024 05:29:35 GMT
• Title: PROflow: An iterative refinement model for PROTAC-induced structure prediction
• Abstract summary: Proteolysis targeting chimeras (PROTACs) are small molecules that trigger the breakdown of traditionally undrug'' 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. Existing PROTAC docking methods have been forced to simplify the problem into a distance-constrained protein-protein docking task. 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
• Score: 4.113597666007784
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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.

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