Eva‐Maria Strauch

This study introduces BioEmu, a workflow combining generative AI with molecular simulations to sample protein conformations, showing both broad coverage and specific limitations in capturing conformational heterogeneity.

ConforFold improves recovery of alternative protein conformations by integrating secondary-structure sampling with deep learning, outperforming existing methods like AlphaFlow and Cfold.

CryoPhold integrates AlphaFold, cryo-EM, and molecular simulations to predict protein dynamics and structural hotspots in human proteins like GlyT1 and BRAF mutants.

This paper develops a computational method to identify stabilizing disulfide bonds for prefusion class I fusion proteins, demonstrating its effectiveness in stabilizing the RSV F protein and providing protection in a cotton rat model.

The paper develops a deep learning model for designing protein-protein interaction fragments, demonstrating its ability to recapitulate natural interactions with high accuracy.

This paper introduces a deep learning model for designing one-sided protein-protein interaction motifs by predicting structure and sequence from co-crystal data.

This paper designs small, stable proteins that bind to diverse target proteins using only structural information, achieving nanomolar to picomolar affinities.

The paper designs picomolar SARS-CoV-2 miniprotein inhibitors using computational methods and experimental validation, showing high potency and structural similarity to computational models.