The dynamical interplay between a megadalton peptide nanocage and solutes probed by microsecond atomistic MD; implications for design.

Understanding the assembly and dynamics of protein-based supramolecular capsids and cages is of fundamental importance and could lead to applications in synthetic biology and biotechnology. Here we present long and large atomistic molecular dynamics simulations of de novo designed self-assembling protein nanocages (SAGEs) in aqueous media. Microsecond simulations, comprised of ≈42 million atoms for three pre-formed SAGEs of different charges, in the presence of solutes and solvent have been completed.

Elfin: An algorithm for the computational design of custom three-dimensional structures from modular repeat protein building blocks.

Computational protein design methods have enabled the design of novel protein structures, but they are often still limited to small proteins and symmetric systems. To expand the size of designable proteins while controlling the overall structure, we developed Elfin, a genetic algorithm for the design of novel proteins with custom shapes using structural building blocks derived from experimentally verified repeat proteins. By combining building blocks with compatible interfaces, it is possible to rapidly build non-symmetric large structures (>1000 amino acids) that match three-dimensional geometric descriptions provided by the user.

Atomistic non-adiabatic dynamics of the LH2 complex with a GPU-accelerated ab initio exciton model.

We recently outlined an efficient multi-tiered parallel ab initio excitonic framework that utilizes time dependent density functional theory (TDDFT) to calculate ground and excited state energies and gradients of large supramolecular complexes in atomistic detail - enabling us to undertake non-adiabatic simulations which explicitly account for the coupled anharmonic vibrational motion of all the constituent atoms in a supramolecular system. Here we apply that framework to the 27 coupled bacterio-chlorophyll-a chromophores which make up the LH2 complex, using it to compute an on-the-fly nonadiabatic surface-hopping (SH) trajectory of electronically excited LH2. Part one of this article is focussed on calibrating our ab initio exciton Hamiltonian using two key parameters: a shift δ, which corrects for the error in TDDFT vertical excitation energies; and an effective dielectric constant ε, which describes the average screening of the transition-dipole coupling between chromophores.

Adaptive free energy sampling in multidimensional collective variable space using boxed molecular dynamics.

The past decade has seen the development of a new class of rare event methods in which molecular configuration space is divided into a set of boundaries/interfaces, and then short trajectories are run between boundaries. For all these methods, an important concern is how to generate boundaries. In this paper, we outline an algorithm for adaptively generating boundaries along a free energy surface in multi-dimensional collective variable (CV) space, building on the boxed molecular dynamics (BXD) rare event algorithm.

High performance virtual drug screening on many-core processors.

Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules.

A GPU-accelerated immersive audio-visual framework for interaction with molecular dynamics using consumer depth sensors.

With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human-computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data.

Rapid decomposition and visualisation of protein-ligand binding free energies by residue and by water.

Recent advances in computational hardware, software and algorithms enable simulations of protein-ligand complexes to achieve timescales during which complete ligand binding and unbinding pathways can be observed. While observation of such events can promote understanding of binding and unbinding pathways, it does not alone provide information about the molecular drivers for protein-ligand association, nor guidance on how a ligand could be optimised to better bind to the protein. We have developed the waterswap (C.

Computational assay of H7N9 influenza neuraminidase reveals R292K mutation reduces drug binding affinity.

The emergence of a novel H7N9 avian influenza that infects humans is a serious cause for concern. Of the genome sequences of H7N9 neuraminidase available, one contains a substitution of arginine to lysine at position 292, suggesting a potential for reduced drug binding efficacy. We have performed molecular dynamics simulations of oseltamivir, zanamivir and peramivir bound to H7N9, H7N9-R292K, and a structurally related H11N9 neuraminidase.

Analysis and assay of oseltamivir-resistant mutants of influenza neuraminidase via direct observation of drug unbinding and rebinding in simulation.

The emergence of influenza drug resistance is a major public health concern. The molecular basis of resistance to oseltamivir (Tamiflu) is investigated using a computational assay involving multiple 500 ns unrestrained molecular dynamics (MD) simulations of oseltamivir complexed with mutants of H1N1-2009 influenza neuraminidase. The simulations, accelerated using graphics processors (GPUs), and using a fully explicit model of water, are of sufficient length to observe multiple drug unbinding and rebinding events.

A massively multicore parallelization of the Kohn-Sham energy gradients.

In a previous article [Brown et al., J Chem Theory Comput 2009, 4, 1620], we described a quadrature-based formulation of the Kohn-Sham Coulomb problem that allows for efficient parallelization over thousands of small processor cores. Here, we present the analytic gradients of this modified Kohn-Sham scheme, and describe the parallel implementation of the gradients on a numerical accelerator architecture.

Massively Multicore Parallelization of Kohn-Sham Theory.

A multicore parallelization of Kohn-Sham density functional theory is described, using an accelerator technology made by ClearSpeed Technology. Efficiently scaling parallelization over 2304 cores is achieved. To deliver this degree of parallelism, the Coulomb problem is reformulated to use Poisson density fitting with numerical quadrature of the required three-index integrals; extensive testing reveals negligible errors from the additional approximations.