Fabian Sesterhenn

Targeted finetuning enables co-folding models to learn ligand-induced protein conformational states

The paper shows targeted finetuning can enable co-folding models to learn ligand-induced conformational states not present in training data.

Systematic identification of structure-specific protein-protein interactions

This study systematically identifies structure-specific protein-protein interactions using LiP-MS, demonstrating its application to alpha-synuclein in Parkinson's disease.

A generic framework for hierarchical de novo protein design

This paper introduces a framework for de novo protein design that automatically generates structural templates and evaluates their stability through experimental characterization.

Rosetta FunFolDes - a general framework for the computational design of functional proteins

This paper introduces a computational framework for designing functional proteins by integrating folding and sequence design, showing that functional motifs can be embedded without requiring the global energy minimum.

rstoolbox: management and analysis of computationally designed structural ensembles.

rstoolbox provides tools for analyzing protein design ensembles, enabling efficient processing of decoy sets and benchmarking of design protocols.