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

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

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Data-driven large-scale genomic analysis reveals an intricate phylogenetic and functional landscape in J-domain proteins

Motifs for making tricycles

Towards automating de novo protein design for novel functionalities: controlling protein folds and protein-protein interactions

Deep learning approaches for conformational flexibility and switching properties in protein design

Scaffolding protein functional sites using deep learning

Molten globule-like transition state of protein barnase measured with calorimetric force spectroscopy

Statistical potentials from the Gaussian scaling behaviour of chain fragments buried within protein globules

A generic framework for hierarchical de novo protein design

Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

Computational design of novel protein–protein interactions – An overview on methodological approaches and applications