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Protein protein interactions

Protein-protein interactions

Created Apr 10, 2026

biophysics/interactions

Protein-protein interactions describe when two or more proteins bind to one another.

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A small number of high-energy hot spot interactions can dominate protein-protein binding energy
AF3 binding affinity predictions are orthogonal to those made by force fields and other neural networks
AF3-generation methods can be substantially shrunk without sacrificing prediction quality, except on PPIs
Ab-Ag inverse folding methods benefit from pretraining
Affinity maturation causes antibody-antigen interfaces to be more similar to generic PPI interfaces
All-atom protein structure prediction methods are unable to model PPIs with large buried surface areas
Arginines have a greater propensity to form protein-protein interactions than lysines
Binding affinity of protein-protein interactions correlates with buried surface area
Boltz-2 intermediate representations can predict protein-protein binding affinity
Coevolutionary patterns in multiple sequence alignments do not contribute to protein-protein complex prediction
Correct protomer structure prediction is necessary but insufficient for accurate protein-protein docking
DL structure prediction methods cannot predict CDR conformations unseen during training
Display methods
DockQ
Dropout improves AF2 multimer prediction, including for antibody-antigen complexes
Half of pathogenic mutations in intrinsically disordered regions improve binding to partners, or create new binding partners
Kinked CDRH3 loops
MSA protein language models can identify intermolecular contacts
Molecular glues
Monomeric AF2 is better able to distinguish positive and negative PPIs than AF2-multimer
PROTACs
Protein abundance is inversely correlated with its propensity to form nonfunctional interactions
Protein ensemble prediction methods do not generate conformations that are amenable to PPI docking
Protein language models can predict zero-shot which proteins belong to the same species
Protein-protein interaction interfaces are highly degenerate
Protein-protein interaction interfaces promote cotranslational assembly
Protein-protein interfaces have looser packing than intra-chain interactions
Structure prediction and design tools trained on monomers generalize to oligomers
The Boltz-2 affinity module cannot be effectively repurposed for PPI affinity prediction
Training protein structure prediction neural networks on both positive and negative protein-protein interactions improves PPI discrimination
iPAE is anticorrelated with number of interface H-bonds

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