Orly Avraham

Protein language models can capture protein quaternary state

The paper trains a protein language model to predict protein quaternary states from sequences, showing it can distinguish multimers from monomers but performs worse than structure-based methods.

PatchMAN docking: Modeling peptide-protein interactions in the context of the receptor surface

PatchMAN models peptide-protein interactions by aligning structural motifs on the receptor surface, achieving high accuracy in docking without using sequence information.

Harnessing protein folding neural networks for peptide-protein docking

The paper applies AlphaFold2 to model peptide-protein interactions using a poly glycine linker, showing accurate predictions without sequence alignment.

Sylites: Multipurpose markers for the visualization of inhibitory synapses

The paper introduces Sylites, fluorogenic probes for visualizing inhibitory synapses with high contrast and selectivity, enabling precise nanoscopic measurements and 3D distribution analysis in brain tissue.