K. Lindorff-Larsen

The paper identifies structural destabilization and degradation of MLH1 variants in Lynch syndrome, linking reduced cellular levels to loss-of-function and suggesting stability predictions for diagnostic use.

The paper introduces a Bayesian-Maximum-Entropy method to reweight IDP ensembles using NMR chemical shifts, showing it provides consistent results even when other fitting assessment methods fail.

The paper introduces PSX, a software tool for calculating deuterium-exchange effects in SANS measurements from protein coordinates, showing that the common 90% exchange assumption is often an overestimate.

The paper calculates radius of gyration and hydrodynamic radius from computationally generated conformational ensembles of intrinsically disordered proteins and integrates SAXS and NMR data using Bayesian/Maximum Entropy methods.

The paper classifies PTEN missense variants as pathogenic or benign using experimental and computational methods, finding that ~60% of pathogenic variants destabilize the protein.

This study investigates how polyglutamine tract length affects the structure and function of the androgen receptor, revealing hydrogen bonds that stabilize a helical conformation linked to transcriptional activity and disease.

The paper introduces a hybrid protein folding model, ProfasiGo, combining all-atom physics-based and structure-based potentials, and applies it to study folding free energy landscapes of four proteins.

This study refines the native state ensemble of NCBD using chemical shifts and NOEs to accurately model its conformational dynamics.

This study benchmarks molecular dynamics simulations of salt bridge stability in GB1 using NMR data, finding that simulations overestimate salt bridge stability compared to experimental results.

The paper determines the conformational ensemble of RNA tetranucleotides using NMR data and molecular dynamics simulations with a reweighting scheme.