Toward a Computational Ecotoxicity Assay.

Thousands of anthropogenic chemicals are released into the environment each year, posing potential hazards to human and environmental health. Toxic chemicals may cause a variety of adverse health effects, triggering immediate symptoms or delayed effects over longer periods of time. It is thus crucial to develop methods that can rapidly screen and predict the toxicity of chemicals to limit the potential harmful impacts of chemical pollutants. Computational methods are being increasingly used in toxicity predictions. Here, the method of molecular docking is assessed for screening potential toxicity of a variety of xenobiotic compounds, including pesticides, pharmaceuticals, pollutants, and toxins derived from the chemical industry. The method predicts the binding energy of pollutants to a set of carefully selected receptors under the assumption that toxicity in many cases is related to interference with biochemical pathways. The strength of the applied method lies in its rapid generation of interaction maps between potential toxins and the targeted enzymes, which could quickly yield molecular-level information and insight into potential perturbation pathways, aiding in the prioritization of chemicals for further tests. Two scoring functions are compared: Autodock Vina and the machine-learning scoring function RF-Score-VS. The results are promising, although hampered by the accuracy of the scoring functions. The strengths and weaknesses of the docking protocol are discussed, as well as future directions for improving the accuracy for the purpose of toxicity predictions.

Construction of a closed polymer network for computer simulations.

Computer simulations are an important tool for linking the behaviour of polymer materials to the properties of the constituent polymer chains. In simulations, one normally uses periodic boundary conditions to mimic a macroscopic system. For a cross-linked polymer network, this will impose restrictions on the motion of the polymer chains at the borders of the simulation cell. We present a new method for constructing a three-dimensional closed network without periodic boundaries by embedding the system onto the surface of a sphere in four dimensions. This method can also be used to construct finite-sized gel particles for simulating the swelling of particles in a surrounding solvent. The method is described in algorithmic detail to allow the incorporation of the method into different types of simulation programs. We also present the results of Brownian dynamics simulations, analyzing the end-to-end distribution, radial distribution function, and the pore size distribution for different volume fractions and for chains with varying stiffness.

Unravelling the mechanism of pH-regulation in dinoflagellate luciferase.

Dinoflagellates are the dominant source of bioluminescence in coastal waters. The luminescence reaction involves the oxidation of luciferin by a luciferase enzyme, which only takes place at low pH. The pH-dependence has previously been linked to four conserved histidines. It has been suggested that their protonation might induce a conformational change in the enzyme, thereby allowing substrate access to the binding pocket. Yet, the precise mechanism of luciferase activation has remained elusive. Here, we use computational tools to predict the open structure of the luciferase in Lingulodinium polyedra and to decipher the nature of the opening mechanism. Through accelerated molecular dynamics simulations, we demonstrate that the closed-open conformational change likely takes place via a tilt of the pH-regulatory helix-loop-helix domain. Moreover, we propose that the molecular basis for the transition is electrostatic repulsion between histidine-cation pairs, which destabilizes the closed conformation at low pH. Finally, by simulating truncated mutants, we show that eliminating the C-terminus alters the shape of the active site, effectively inactivating the luciferase.

Tracer diffusion in a polymer gel: simulations of static and dynamic 3D networks using spherical boundary conditions.

We have investigated an alternative to the standard periodic boundary conditions for simulating the diffusion of tracer particles in a polymer gel by performing Brownian dynamics simulations using spherical boundary conditions. The gel network is constructed by randomly distributing tetravalent cross-linking nodes and connecting nearest pairs. The final gel structure is characterised by the radial distribution functions, chain lengths and end-to-end distances, and the pore size distribution. We have looked at the diffusion of tracer particles with a wide range of sizes, diffusing in both static and dynamic networks of two different volume fractions. It is quantitatively shown that the dynamical effect of the network becomes more important in facilitating the diffusional transport for larger particle sizes, and that one obtains a finite diffusion also for particle sizes well above the maximum in the pore size distribution.