Computational study of ligand binding in lipid transfer proteins: Structures, interfaces, and free energies of protein-lipid complexes

Plant nonspecific lipid transfer proteins (nsLTPs) bind a wide variety of lipids, which allows them to perform disparate functions. Recent reports on their multifunctionality in plant growth processes have posed new questions on the versatile binding abilities of these proteins. The lack of binding specificity has been customarily explained in qualitative terms on the basis of a supposed structural flexibility and nonspecificity of hydrophobic protein-ligand interactions. We present here a computational study of protein-ligand complexes formed between five nsLTPs and seven lipids bound in two different ways in every receptor protein. After optimizing geometries inmolecular dynamics calculations, we computed Poisson- Boltzmann electrostatic potentials, solvation energies, properties of the protein-ligand interfaces, and estimates of binding free energies of the resulting complexes. Our results provide the first quantitative information on the ligand abilities of nsLTPs, shed new light into protein-lipid interactions, and reveal new features which supplement commonly held assumptions on their lack of binding specificity.

Renewable energies Driven by Feed-on Tariffs. Photovoltaic vs Wind Energy Development in Spain

Although others regulations regarding feed-in tariffs for photovoltaics (PV) existed in Spain previously, the one that meant a paradigm change was the introduction in 2007 of law R.D.661/2007 which established a feed-in tariff of 41,75 cents/kWh if the installed capacity was greater than 100KWp and 44,04 cents/kWh if it was smaller. The high level of the subsidies together with the lack of a limit for the total installed capacity originates the well-known Spanish photovoltaic boom. In September 2008 the installed PV capacity accounted for 3.2GWp (while the official objective stated in the national renewable roadmap was only 400MWp). To avoid this situation a new law, R.D. 1578/2008, was proclaimed which established a decreasing feed-in tariff of 32 cents/kWh (for ground installations) and 34 cents/kWh (for rooftops) and it limited the annual installed capacity to 500MWp. Although it was successful in limiting the PV subsidies total costs, the successive and sudden changes in regulations resulted very harmful to the local PV industry. In this article, the strong influence of feed-in tariff in the development of PV installed capacity and market evolution in Spain will be analyzed in detail. In addition, a comparison with other subsidized technologies which installed capacity has had a smoother evolution, as wind energy, will be presented.

Electricity price forecasting accounting for renewable energies: optimal combined forecasts

Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as Spain, Germany and Denmark, renewable energy is having a deep impact on the local power markets. In this paper, we propose an optimal model from the perspective of forecasting accuracy, and it consists of a combination of several univariate and multivariate time series methods that account for the amount of energy produced with clean energies, particularly wind and hydro, which are the most relevant renewable energy sources in the Iberian Market. This market is used to illustrate the proposed methodology, as it is one of those markets in which wind power production is more relevant in terms of its percentage of the total demand, but of course our method can be applied to any other liberalised power market. As far as our contribution is concerned, first, the methodology proposed by García-Martos et al(2007 and 2012) is generalised twofold: we allow the incorporation of wind power production and hydro reservoirs, and we do not impose the restriction of using the same model for 24h. A computational experiment and a Design of Experiments (DOE) are performed for this purpose. Then, for those hours in which there are two or more models without statistically significant differences in terms of their forecasting accuracy, a combination of forecasts is proposed by weighting the best models(according to the DOE) and minimising the Mean Absolute Percentage Error (MAPE). The MAPE is the most popular accuracy metric for comparing electricity price forecasting models. We construct the combi nation of forecasts by solving several nonlinear optimisation problems that allow computation of the optimal weights for building the combination of forecasts. The results are obtained by a large computational experiment that entails calculating out-of-sample forecasts for every hour in every day in the period from January 2007 to Decem ber 2009. In addition, to reinforce the value of our methodology, we compare our results with those that appear in recent published works in the field. This comparison shows the superiority of our methodology in terms of forecasting accuracy.

Optimal Combined Forecasts for Electricity Prices: Influence of Clean Energies

In this work, an electricity price forecasting model is developed. The performance of the proposed approach is improved by considering renewable energies (wind power and hydro generation) as explanatory variables. Additionally, the resulting forecasts are obtained as an optimal combination of a set of several univariate and multivariate time series models. The large computational experiment carried out using out-of-sample forecasts for every hour and day allows withdrawing statistically sound conclusions

Fast ignition driven by quasi-monoenergetic ions: Optimal ion type and reduction of ignition energies with an ion beam array

Fast ignition of inertial fusion targets driven by quasi-monoenergetic ion beams is investigated by means of numerical simulations. Light and intermediate ions such as lithium, carbon, aluminum and vanadium have been considered. Simulations show that the minimum ignition energies of an ideal configuration of compressed Deuterium-Tritium are almost independent on the ion atomic number. However, they are obtained for increasing ion energies, which scale, approximately, as Z2, where Z is the ion atomic number. Assuming that the ion beam can be focused into 10 ?m spots, a new irradiation scheme is proposed to reduce the ignition energies. The combination of intermediate Z ions, such as 5.5 GeV vanadium, and the new irradiation scheme allows a reduction of the number of ions required for ignition by, roughly, three orders of magnitude when compared with the standard proton fast ignition scheme.

Ionization energies of amphoteric-doped Cu2ZnSnS4: Photovoltaic application

The substitution of Cu, Sn or Zn in the quaternary Cu2ZnSnS4 semiconductor by impurities that introduce intermediate states in the energy bandgap could have important implications either for photovoltaic or spintronic applications. This allows more generation–recombination channels than for the host semiconductor. We explore and discuss this possibility by obtaining the ionization energies from total energy first-principles calculations. The three substitutions of Cu, Sn and Zn by impurities are analyzed. From these results we have found that several impurities have an amphoteric behavior with the donor and acceptor energies in the energy bandgap. In order to analyze the role of the ionization energies in both the radiative and non-radiative processes, the host energy bandgap and the acceptor and the donor energies have been obtained as a function of the inward and outward impurity-S displacements. We carried out the analysis for both the natural and synthetic CZTS. The results show that the ionization energies are similar, whereas the energy band gaps are different.