Sören von Bülow

AF-CALVADOS uses AlphaFold to simulate multi-domain proteins at the proteome level, showing good performance across ordered and disordered regions.

This study develops a high-throughput method to quantify interactions driving condensate formation in intrinsically disordered proteins and shows amino acid content primarily determines partitioning behavior.

The paper identifies and models interactions between transactivation domains and arginine-glycine-rich regions using proteome-scale data and simulations, revealing electrostatic mechanisms driving TF-RBP coupling.

This paper introduces IDPFold2, a framework for predicting conformational ensembles of proteins, including multidomain proteins and complexes, and shows it outperforms existing methods.

The paper develops a machine learning model to predict phase separation propensities of disordered proteins from sequence, identifying 5% of human IDRs likely to undergo homotypic phase separation.

This paper introduces a coarse-grained RNA model to simulate protein-RNA condensates and shows it captures key interaction aspects.

The paper introduces a coarse-grained model for multi-domain proteins that accurately simulates conformational properties and phase separation behavior.

The paper investigates the molecular functions of YTHDF proteins across land plants, showing conserved ancestral functions and lineage-specific diversification in Arabidopsis.

GlycoSHIELD is a pipeline that grafts glycan conformers onto protein structures to model glycan impact on protein dynamics and interactions.

This study uses cryo electron tomography and simulations to analyze the structure of SARS-CoV-2 spike protein in situ, revealing three hinges in the stalk domain that enable orientational flexibility.