[1] Human mitochondrial protein complexes revealed by large-scale coevolution analysis and deep learning-based structure modeling
[2] Current protein structure predictors do not produce meaningful folding pathways
[3] Harnessing protein folding neural networks for peptide-protein docking
[4] Improved prediction of protein-protein interactions using AlphaFold2
[5] AlphaFold2: A role for disordered protein prediction?
[6] AlphaFold2 transmembrane protein structure prediction shines
[7] Can AlphaFold2 predict protein-peptide complex structures accurately?
[8] Improved prediction of protein-protein interactions using AlphaFold2
[9] Possible Implications of AlphaFold2 for Crystallographic Phasing by Molecular Replacement
[10] Improved Docking of Protein Models by a Combination of Alphafold2 and ClusPro
[11] Identification of Iron-Sulfur (Fe-S) and Zn-binding Sites Within Proteomes Predicted by DeepMind’s AlphaFold2 Program Dramatically Expands the Metalloproteome

Glossary

Intrinsically Disordered Proteins (IDPs) are a large class of proteins without a rigid structure which accomplish their function despite (or thanks to) their dynamic behavior. They can become rigid in complexes with other molecules.