6 papers
On the potential of machine learning to examine the relationship between sequence, structure, dynamics and function of intrinsically disordered proteins
Kresten Lindorff-Larsen, Birthe B. Kragelund
Intrinsically disordered proteins (IDPs) constitute a broad set of proteins with few uniting and many diverging properties. IDPs-and intrinsically disordered regions (IDRs) intersp…
Linking thermodynamics and measurements of protein stability
Kresten Lindorff-Larsen, Kaare Teilum
We review the background, theory and general equations for the analysis of equilibrium protein unfolding experiments, focusing on denaturant and heat-induced unfolding. The primary…
Dissecting the statistical properties of the Linear Extrapolation Method of determining protein stability
Kresten Lindorff-Larsen
When protein stability is measured by denaturant induced unfolding the linear extrapolation method is usually used to analyse the data. This method is based on the observation that…
What will computational modelling approaches have to say in the era of atomistic cryo-EM data?
James S. Fraser, Kresten Lindorff-Larsen, Massimiliano Bonomi
The focus of this viewpoint is to identify, in the era of atomistic resolution cryo-electron microscopy data, the areas in which computational modelling and molecular simulations w…
How to learn from inconsistencies: Integrating molecular simulations with experimental data
Simone Orioli, Andreas Haahr Larsen, Sandro Bottaro +1
Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly us…
Frequency adaptive metadynamics for the calculation of rare-event kinetics
Yong Wang, Omar Valsson, Pratyush Tiwary +2
The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predicti…