Christoph Leberecht

The paper develops a multiscale computational model to understand the regulation of aquaporin 2 recycling and identifies cAMP compartmentalization as a key mechanism regulated by protein kinase A.

The paper uses interpretable machine learning to classify protein structures as native or mirror based on Ramachandran plot analysis with high accuracy.

This study characterizes how aminoacyl-tRNA synthetases distinguish amino acids using computational analysis of crystallographic structures, revealing the role of binding site composition, non-covalent interactions, error correction, and steric effects.

The paper predicts off-targets of a MAPK14 inhibitor using in silico methods and validates them experimentally, achieving a 46% hit rate.

The paper applies GMLVQ to predict early folding residues in proteins, achieving 76.6% AUC and highlighting the importance of secondary structure and hydrophobic networks.

The paper identifies two distinct ATP binding motifs in aminoacyl tRNA synthetases (aaRS) and links their structural features to evolutionary hypotheses about the origin of these enzymes.