Bias in, bias out–AlphaFold-Multimer and the structural complexity of protein interfaces
JM Strom, K Luck - Current Opinion in Structural Biology, 2025 - Elsevier
Highlights•Protein interfaces involving disordered protein regions are underrepresented in
training data for structure prediction models.•Benchmarking of structure prediction models …
training data for structure prediction models.•Benchmarking of structure prediction models …
[HTML][HTML] SpatialPPIv2: Enhancing protein–protein interaction prediction through graph neural networks with protein language models
W Hu, M Ohue - Computational and Structural Biotechnology Journal, 2025 - Elsevier
Protein–protein interactions (PPIs) are fundamental to cellular functions, and accurately
predicting such interactions is crucial for understanding biological mechanisms and …
predicting such interactions is crucial for understanding biological mechanisms and …
[HTML][HTML] Unified Sampling and Ranking for Protein Docking with DFMDock
Diffusion models have shown promise in addressing the protein docking problem.
Traditionally, these models are used solely for sampling docked poses, with a separate …
Traditionally, these models are used solely for sampling docked poses, with a separate …
Have protein-ligand co-folding methods moved beyond memorisation?
Deep learning has driven major breakthroughs in protein structure prediction, however the
next critical advance is accurately predicting how proteins interact with other molecules …
next critical advance is accurately predicting how proteins interact with other molecules …
SpatialPPI 2.0: Enhancing Protein-Protein Interaction Prediction through Inter-Residue Analysis in Graph Attention Networks
W Hu, M Ohue - bioRxiv, 2024 - biorxiv.org
Protein-protein interactions (PPIs) are fundamental to cellular functions, and accurate
prediction of these interactions is crucial to understanding biological mechanisms and …
prediction of these interactions is crucial to understanding biological mechanisms and …