Protein energy landscape exploration with structure-based models.

Exploring the multi-dimensional energy landscape of a large protein in detail is a computational challenge. Such investigations may include analysis of multiple folding pathways, rate constants for important conformational transitions, locating intermediate states populated during folding, estimating energetic and entropic barriers that separate populated basins, and visualising a high-dimensional surface. The complexity of the landscape can be simplified through coarse-grained structure-based models (SBMs).

Go-Kit: A Tool To Enable Energy Landscape Exploration of Proteins.

Coarse-grained Go̅-like models, based on the principle of minimal frustration, provide valuable insight into fundamental questions in the field of protein folding and dynamics. In conjunction with commonly used molecular dynamics (MD) simulations, energy landscape exploration methods like discrete path sampling (DPS) with Go̅-like models can provide quantitative details of the thermodynamics and kinetics of proteins. Here we present Go-kit, a software that facilitates the setup of MD and DPS simulations of several flavors of Go̅-like models.

Energy Landscape of the Designed Protein Top7.

To fold on biologically relevant time scales, proteins have evolved funnelled energy landscapes with minimal energetic trapping. However, the polymeric nature of proteins and the spatial arrangement of secondary structural elements can create topological traps and slow folding. It is challenging to identify, visualize, and quantify such topological trapping.

The threshold algorithm: Description of the methodology and new developments.

Understanding the dynamics of complex systems requires the investigation of their energy landscape. In particular, the flow of probability on such landscapes is a central feature in visualizing the time evolution of complex systems. To obtain such flows, and the concomitant stable states of the systems and the generalized barriers among them, the threshold algorithm has been developed.

A Threshold-Minimization Scheme for Exploring the Energy Landscape of Biomolecules: Application to a Cyclic Peptide and a Disaccharide.

We present a scheme, called the threshold-minimization method, for globally exploring the energy landscapes of small systems of biomolecular interest where typical exploration moves always require a certain degree of subsequent structural relaxation in order to be efficient, e.g., systems containing small or large circular carbon chains such as cyclic peptides or carbohydrates.

Chiral effects on helicity studied via the energy landscape of short (D, L)-alanine peptides.

The homochirality of natural amino acids facilitates the formation of regular secondary structures such as α-helices and β-sheets. Here, we study the relationship between chirality and backbone structure for the example of hexa-alanine. The most stable stereoisomers are identified through global optimisation.

Atomistic modeling of the low-temperature atom-beam deposition of magnesium fluoride.

We model the deposition and growth of MgF(2) on a sapphire substrate as it occurs in a low-temperature atom-beam-deposition experiment. In the experiment, an (X-ray) amorphous film of MgF(2) is obtained at low temperatures of 170-180 K, and upon heating, this transforms to the expected rutile phase via the CaCl(2)-type structure. We confirm this from our simulations and propose a mechanism for this transformation.