Casper A. Goverde

Computational design of microbial and animal rhodopsin soluble analogues

This study computationally designs soluble analogues of animal and microbial rhodopsins, showing they are well-folded, thermostable, and retain retinal photocycle functionality.

Structures of the Foamy virus fusion protein reveal an unexpected link with the F protein of paramyxo- and pneumoviruses

The paper reports cryo-EM structures of foamy virus Env in pre- and post-fusion states, revealing structural similarity to paramyxovirus F proteins and suggesting an evolutionary link.

Exploring "dark matter" protein folds using deep learning

This paper introduces a deep learning framework called Genesis to learn protein structural patterns and demonstrates its ability to design novel protein folds with high protease resistance.

BindCraft: one-shot design of functional protein binders

Hallucinating binders by backpropagating through AlphaFold2 weights gave, across 12 targets, binders in 10-100% of the designs tested per target, mostly at nanomolar affinity.

An atlas of protein homo-oligomerization across domains of life

The paper predicts homo-oligomerization across four proteomes using AlphaFold2, finding that 50% of archaea, 45% of bacteria, and 20% of eukaryotes form homomers, with disease mutations enriched at interfaces.

AF2BIND: Predicting ligand-binding sites using the pair representation of AlphaFold2

AF2BIND predicts ligand-binding sites using AlphaFold2's pairwise representation without requiring a ligand, outperforming other models and linking bait amino acids to ligand properties.

De novo protein design by inversion of the AlphaFold structure prediction network

This paper inverts the AlphaFold2 network to perform de novo protein design, showing that while the method generates viable sequences with correct folds, it requires post-design optimization to achieve optimal surface properties.

Computational design of soluble functional analogues of integral membrane proteins

This study designs soluble analogues of integral membrane proteins using deep learning, achieving high thermal stability and functional accuracy.