Molecular and Electronic Structure of the Peptide Subunit of Geobacter sulfurreducens Conductive Phi from First Principles

The respiration of metal oxides by the bacterium Geobacter sulfurreducens requires the assembly of a small peptide (the GS pilin) into conductive filaments termed pili. We gained insights into the contribution of the GS pilin to the pilus conductivity by developing a homology model and performing molecular dynamics simulations of the pilin peptide in vacuo and in solution. The results were consistent with a predominantly helical peptide containing the conserved a-helix region required for pilin assembly but carrying a short carboxy-terminal random-coiled segment rather than the large globular head of other bacterial pilins. The electronic structure of the pain was also explored from first principles and revealed a biphasic charge distribution along the pilin and a low electronic HOMO-LUMO gap, even in a wet environment. The low electronic band gap was the result of strong electrostatic fields generated by the alignment of the peptide bond dipoles in the pilin's alpha-helix and by charges from ions in solution and amino acids in the protein. The electronic structure also revealed some level of orbital delocalization in regions of the pilin containing aromatic amino acids and in spatial regions of high resonance where the HOMO and LUMO states are, which could provide an optimal environment for the hopping of electrons under thermal fluctuations. Hence, the structural and electronic features of the pilin revealed in these studies support the notion of a pilin peptide environment optimized for electron conduction.

Identifying regulational alterations in gene regulatory networks by state space representation of vector autoregressive models and variational annealing

Background: In the analysis of effects by cell treatment such as drug dosing, identifying changes on gene network structures between normal and treated cells is a key task. A possible way for identifying the changes is to compare structures of networks estimated from data on normal and treated cells separately. However, this approach usually fails to estimate accurate gene networks due to the limited length of time series data and measurement noise. Thus, approaches that identify changes on regulations by using time series data on both conditions in an efficient manner are demanded. Methods: We propose a new statistical approach that is based on the state space representation of the vector autoregressive model and estimates gene networks on two different conditions in order to identify changes on regulations between the conditions. In the mathematical model of our approach, hidden binary variables are newly introduced to indicate the presence of regulations on each condition. The use of the hidden binary variables enables an efficient data usage; data on both conditions are used for commonly existing regulations, while for condition specific regulations corresponding data are only applied. Also, the similarity of networks on two conditions is automatically considered from the design of the potential function for the hidden binary variables. For the estimation of the hidden binary variables, we derive a new variational annealing method that searches the configuration of the binary variables maximizing the marginal likelihood. Results: For the performance evaluation, we use time series data from two topologically similar synthetic networks, and confirm that our proposed approach estimates commonly existing regulations as well as changes on regulations with higher coverage and precision than other existing approaches in almost all the experimental settings. For a real data application, our proposed approach is applied to time series data from normal Human lung cells and Human lung cells treated by stimulating EGF-receptors and dosing an anticancer drug termed Gefitinib. In the treated lung cells, a cancer cell condition is simulated by the stimulation of EGF-receptors, but the effect would be counteracted due to the selective inhibition of EGF-receptors by Gefitinib. However, gene expression profiles are actually different between the conditions, and the genes related to the identified changes are considered as possible off-targets of Gefitinib. Conclusions: From the synthetically generated time series data, our proposed approach can identify changes on regulations more accurately than existing methods. By applying the proposed approach to the time series data on normal and treated Human lung cells, candidates of off-target genes of Gefitinib are found. According to the published clinical information, one of the genes can be related to a factor of interstitial pneumonia, which is known as a side effect of Gefitinib.

First-principles studies of complex magnetism in Mn nanostructures on the Fe(001) surface

The magnetic properties of Mn nanostructures on the Fe(001) surface have been studied using the noncollinear first-principles real space-linear muffin-tin orbital-atomic sphere approximation method within density-functional theory. We have considered a variety of nanostructures such as adsorbed wires, pyramids, and flat and intermixed clusters of sizes varying from two to nine atoms. Our calculations of interatomic exchange interactions reveal the long-range nature of exchange interactions between Mn-Mn and Mn-Fe atoms. We have found that the strong dependence of these interactions on the local environment, the magnetic frustration, and the effect of spin-orbit coupling lead to the possibility of realizing complex noncollinear magnetic structures such as helical spin spiral and half-skyrmion.

First principles calculations for vacancies and antisites in PbSe and PbTe: bulk and nanowire.

The energetic stability and the electronic properties of vacancies (VX) and antisites (XY) in PbSe and PbTe are investigated. PbSe and PbTe are narrow band gap semiconductors and have the potential to be used in infrared detectors, laser, and diodes. They are also of special interest for thermoelectric devices (TE). The calculations are based in the Density Functional Theory (DFT) and the General Gradient Approximation (GGA) for the exchange-correlation term, as implemented in the VASP code. The core and valence electrons are described by the Projected Augmented Wave (PAW) and the Plane Wave (PW) methods, respectively. The defects are studied in the bulk and nanowire (NW) system. Our results show that intrinsec defects (vacancies and antisites) in PbTe have lower formation energies in the NW as compared to the bulk and present a trend in migrate to the surface of the NW. For the PbSe we obtain similar results when compare the formation energy for the bulk and NW. However, the Pb vacancy and the antisites are more stable in the core of the NW. The intrinsec defects are shallow defects for the bulk system. For both PbSe and PbTe VPb is a shallow acceptor defect and VSe and VT e are shallow donor defects for the PbSe and PbTe, respectively. Similar electronic properties are observed for the antisites. For the Pb in the anion site we obtain an n-type semiconductor for both PbSe and PbTe, SeP b is a p-type for the PbSe, and T eP b is a n-type for PbTe. Due the quantum con¯nement effects present in the NW (the band gap open), these defects have different electronic properties for the NW as compared to the bulk. Now these defects give rise to electronic levels in the band gap of the PbTe NW and the VT e present a metallic character. For the PbSe NW a p-type and a n-type semiconductor is obtained for the VP b and P bSe, respectively. On the other hand, deep electronic levels are present in the band gap for the VSe and SePb. These results show that due an enhanced in the electronic density of states (DOS) near the Fermi energy, the defective PbSe and PbTe are candidates for efficient TE devices.