In the field of noncovalent interactions a new paradigm has recently become popular. It stems from the analysis of molecular electrostatic potentials and introduces a label, which has recently attracted enormous attention. The label is σ-hole, and it was first used in connection with halogens. It initiated a renaissance of interest in halogenated compounds, and later on, when found also on other groups of atoms (chalcogens, pnicogens, tetrels and aerogens), it resulted in a new direction of research of intermolecular interactions. In this review, we summarize advances from about the last 10 years in understanding those interactions related to σ-hole. We pay particular attention to theoretical and computational techniques, which play a crucial role in the field.

Computer Modeling of Halogen Bonds and Other σ-Hole Interactions

Based on our critique of requirements for performing an efficient molecular dynamics simulation with the particle-mesh Ewald (PME) implementation in GROMACS 4.5, we present a computational tool to enable the discovery of parameters that produce a given accuracy in the PME approximation of the full electrostatics. Calculations on two parallel computers with different processor and communication structures showed that a given accuracy can be attained over a range of parameter space, and that the attributes of the hardware and simulation system control which parameter sets are optimal. This information can be used to find the fastest available PME parameter sets that achieve a given accuracy. We hope that this tool will stimulate future work to assess the impact of the quality of the PME approximation on simulation outcomes, particularly with regard to the trade-off between cost and scientific reliability in biomolecular applications.

Optimization of parameters for molecular dynamics simulation using smooth particle‐mesh Ewald in GROMACS 4.5

The self-organization of peptides into amyloidogenic oligomers is one of the key events for a wide range of molecular and degenerative diseases. Atomic-resolution characterization of the mechanisms responsible for the aggregation process and the resulting structures is thus a necessary step to improve our understanding of the determinants of these pathologies. To address this issue, we combine the accelerated sampling properties of replica exchange molecular dynamics simulations based on the OPEP coarse-grained potential with the atomic resolution description of interactions provided by all-atom MD simulations, and investigate the oligomerization process of the GNNQQNY for three system sizes: 3-mers, 12-mers and 20-mers. Results for our integrated simulations show a rich variety of structural arrangements for aggregates of all sizes. Elongated fibril-like structures can form transiently in the 20-mer case, but they are not stable and easily interconvert in more globular and disordered forms. Our extensive characterization of the intermediate structures and their physico-chemical determinants points to a high degree of polymorphism for the GNNQQNY sequence that can be reflected at the macroscopic scale. Detailed mechanisms and structures that underlie amyloid aggregation are also provided.

http://normandmousseau.com/publications/125.pdf

A multiscale approach to characterize the early aggregation steps of the amyloid-forming peptide GNNQQNY from the yeast prion sup-35.

We discuss recent advances of the VOTCA package for systematic coarse-graining. Two methods have been implemented, namely the downhill simplex optimization and the relative entropy minimization. We illustrate the new methods by coarse-graining SPC/E bulk water and more complex water-methanol mixture systems. The CG potentials obtained from both methods are then evaluated by comparing the pair distributions from the coarse-grained to the reference atomistic simulations. In addition to the newly implemented methods, we have also added a parallel analysis framework to improve the computational efficiency of the coarse-graining process.

Relative Entropy and Optimization-Driven Coarse-Graining Methods in VOTCA.

https://www.cell.com/biophysj/pdf/S0006-3495(15)00302-1.pdf

A. Feenstra

Papers

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