Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …

Molecular simulations, which simulate the motions of particles according to fundamental
laws of physics, have been applied to a wide range of fields from physics and materials …

Biotechnological innovations have vastly improved the capacity to perform large-scale
protein studies, while the methods we have for identifying and quantifying individual proteins …

The application of computational approaches in drug discovery has been consolidated in
the last decades. These families of techniques are usually grouped under the common …

Coarse-grained (CG) molecular simulations have become a standard tool to study molecular
processes on time and length scales inaccessible to all-atom simulations. Parametrizing CG …

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 …

The dissociation rate (k off) associated with ligand unbinding events from proteins is a
parameter of fundamental importance in drug design. Here we review recent major …

Crystal nucleation is relevant across the domains of fundamental and applied sciences.
However, in many cases, its mechanism remains unclear due to a lack of temporal or spatial …

Atomistic Molecular Dynamics (MD) simulations provide researchers the ability to model
biomolecular structures such as proteins and their interactions with drug-like small …

Self-assembled metallo-organic cages have emerged as promising biomimetic platforms
that can encapsulate whole substrates akin to an enzyme active site. Extensive experimental …