Energy landscapes for clusters of hexapeptides.

We present the results for energy landscapes of hexapeptides obtained using interfaces to the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) program. We have used basin-hopping global optimization and discrete path sampling to explore the landscapes of hexapeptide monomers, dimers, and oligomers containing 10, 100, and 200 monomers modeled using a residue-level coarse-grained potential, Mpipi, implemented in LAMMPS. We find that the dimers of peptides containing amino acid residues that are better at promoting phase separation, such as tyrosine and arginine, have melting peaks at higher temperature in their heat capacity compared to phenylalanine and lysine, respectively.

Energy landscapes for proteins described by the UNRES coarse-grained potential.

The self-assembly of proteins is encoded in the underlying potential energy surface (PES), from which we can predict structure, dynamics, and thermodynamic properties. However, the corresponding analysis becomes increasingly challenging with larger protein sizes, due to the computational time required, which grows significantly with the number of atoms. Coarse-grained models offer an attractive approach to reduce the computational cost.

Global analysis of energy landscapes for materials modeling: A test case for C60.

In this contribution, we employ computational tools from the energy landscape approach to test Gaussian Approximation Potentials (GAPs) for C60. In particular, we apply basin-hopping global optimization and explore the landscape starting from the low-lying minima using discrete path sampling. We exploit existing databases of minima and transition states harvested from previous work using tight-binding potentials.

Exploring energy landscapes for solid-state systems with variable cells at the extended tight-binding level.

The design of novel materials requires a theoretical understanding of dynamical processes in the solid state, including polymorphic transitions and associated pathways. The organization of the potential energy landscape plays a crucial role in such processes, which may involve changes in the periodic boundaries. This study reports the implementation of a general framework for periodic condensed matter systems in our energy landscape analysis software, allowing for variation in both the unit cell and atomic positions.

Enhancing Biomolecular Simulations with Hybrid Potentials Incorporating NMR Data.

Some recent advances in biomolecular simulation and global optimization have used hybrid restraint potentials, where harmonic restraints that penalize conformations inconsistent with experimental data are combined with molecular mechanics force fields. These hybrid potentials can be used to improve the performance of molecular dynamics, structure prediction, energy landscape sampling, and other computational methods that rely on the accuracy of the underlying force field. Here, we develop a hybrid restraint potential based on NapShift, an artificial neural network trained to predict protein nuclear magnetic resonance (NMR) chemical shifts from sequence and structure.

The alchemical energy landscape for a pentameric cluster.

We investigate the energy landscape of an alchemical system of point particles in which the parameters of the interparticle potential are treated as degrees of freedom. Using geometrical optimization, we locate minima and transition states on the landscape for pentamers. We show that it is easy to find the parameters that give the lowest energy minimum and that the distribution of minima on the alchemical landscape is concentrated in particular areas.

Properties of kinetic transition networks for atomic clusters and glassy solids.

A database of minima and transition states corresponds to a network where the minima represent nodes and the transition states correspond to edges between the pairs of minima they connect via steepest-descent paths. Here we construct networks for small clusters bound by the Morse potential for a selection of physically relevant parameters, in two and three dimensions. The properties of these unweighted and undirected networks are analysed to examine two features: whether they are small-world, where the shortest path between nodes involves only a small number or edges; and whether they are scale-free, having a degree distribution that follows a power law.

Exploring the potential energy landscape of the Thomson problem via Newton homotopies.

Locating the stationary points of a real-valued multivariate potential energy function is an important problem in many areas of science. This task generally amounts to solving simultaneous nonlinear systems of equations. While there are several numerical methods that can find many or all stationary points, they each exhibit characteristic problems.

Energy landscapes of planar colloidal clusters.

A short-ranged pairwise Morse potential is used to model colloidal clusters with planar morphologies. Potential and free energy global minima as well as rearrangement paths, obtained by basin-hopping global optimisation and discrete path sampling, are characterised. The potential and free energy landscapes are visualised using disconnectivity graphs.

Designing a Bernal spiral from patchy colloids.

A model potential for colloidal building blocks is defined with two different types of attractive surface sites, described as complementary patches and antipatches. A Bernal spiral is identified as the global minimum for clusters with appropriate arrangements of three patch-antipatch pairs. We further derive a minimalist design rule with only one patch and antipatch, which also produces a Bernal spiral.