Principal component analysis (PCA) is used to reduce the dimensionalities of high-
dimensional datasets in a variety of research areas. For example, biological …

A goal in the kinetic characterization of a macromolecular system is the description of its
slow relaxation processes via (i) identification of the structural changes involved in these …

Protein conformational fluctuations are highly complex and exhibit long-term correlations.
Here, molecular dynamics simulations of small proteins demonstrate that these …

We apply moving root-mean-square deviation (mRMSD), which does not require a reference
structure, as a method for analyzing protein dynamics. This method can be used to calculate …

A significant challenge faced by atomistic simulations is the difficulty, and often impossibility,
to sample the transitions between metastable states of the free-energy landscape …

Dimensionality reduction methods are usually applied on molecular dynamics simulations of
macromolecules for analysis and visualization purposes. It is normally desired that suitable …

Prediction of protein–ligand binding affinity is a major goal in drug discovery. Generally, free
energy gap is calculated between two states (eg, ligand binding and unbinding). The energy …

Molecular dynamics simulation is a powerful method for investigating the structural stability,
dynamics, and function of biopolymers at the atomic level. In recent years, it has become …

We recently proposed the method of time-structure based independent component analysis
(tICA) to examine the slow dynamics involved in conformational fluctuations of a protein as …

Biomacromolecules often undergo significant conformational rearrangements during
function. In proteins, these motions typically consist in nontrivial, concerted rearrangement of …