Sophie Sacquin‐Mora

This paper evaluates limitations of deep learning in biomolecular structure prediction, highlighting the benefits of explicit ion modeling for improving conformational accuracy.

The paper uses molecular dynamics simulations to study the dynamic interactions between Tau protein and tubulin C-terminal tails, revealing sequence-dependent effects and disorder-disorder interplay.

DynaPIN extracts dynamic interface fingerprints from molecular simulations to better characterize protein interactions beyond static models.

This study uses molecular dynamics simulations to compare mannose binding in DC-SIGN and MRC1 CRDs, revealing differences in binding modes and affinity.

This paper uses coarse-grain simulations to study the conformational dynamics of Tau protein with and without phosphorylations, linking structural features to functional properties.

The paper assesses the overbinding of monovalent cations to phosphorylations in forcefields, identifies it as an artifact, and proposes a parameterization strategy to improve accuracy.

This study uses molecular dynamics simulations to analyze how phosphorylations of tau-R2 affect its binding to tubulin and the stability of the tau-microtubule interface.

The paper introduces Menger_Curvature, a MDAKit implementation for calculating Menger Curvatures and Local Flexibilities in polymers, showing it is faster than RMSF and effective for analyzing protein dynamics.

This study investigates how AT8 phosphorylation affects Tau protein conformation and dynamics using biophysical experiments and simulations.

The paper models the structure of the active NOX2 complex using AlphaFold2 and experimental data, revealing the role of disordered regions in subunit assembly.

This paper uses molecular dynamics simulations to study how counterion bridges formed by phosphate groups affect the conformational dynamics of phosphorylated tau-R2 repeat.

The paper develops a theoretical framework to analyze how protein interaction energy landscapes are shaped by both functional and non-functional partners through cross-docking simulations.

The paper identifies non-catalytic functional residues in proteins by analyzing conformational ensembles from NMR data using coarse-grain simulations.

The paper evaluates cross-docking simulations for predicting protein binding sites, finding that alternate binding sites often correspond to interactions with hidden partners not included in the original dataset.