Is it possible for short peptide composed of positively- and negatively-charged "hydrophilic" amino acid residue-clusters to form metastable "hydrophobic" packing?

We theoretically and experimentally analyzed a conformational ensemble of a small, characteristic polypeptide consisting of positively- and negatively-charged amino acid residue clusters, (Lys)9(Glu)9(Lys)9, designed based on the supercoiled DNA-recognition (SDR) domain, with the capability of preferentially binding to supercoiled DNA. Advanced molecular dynamics (MD) simulations coupled with a generalized ensemble technique revealed that substantial amounts of ordered, helical structures were present at the boundaries of the Lys and Glu segments in the obtained conformational ensemble. In fact, the helical content of the peptide calculated from our MD simulations was consistent with that estimated from our experimental analysis employing circular dichroism (CD) spectroscopy. The statistical analysis of the structural ensemble revealed the metastable hydrophobic contact clusters, which were stabilized by closely cohesive residue contacts, formed through "hybrid" hydrophobic (methylene groups) and electrostatic (salt bridges) residue contacts. Both short-range and long-range residue contacts were involved in the metastable hydrophobic clusters, constituting the aforementioned local helical conformations and the compact entire structures, respectively. A significant helical propensity was also found in the (Lys)n and (Glu)m boundaries of other conventional protein structures deposited in the Protein Data Bank (PDB), thus indicating the generality of this conformational trend that has been identified herein.

Learning structure-property relationship in crystalline materials: A study of lanthanide-transition metal alloys.

We have developed a descriptor named Orbital Field Matrix (OFM) for representing material structures in datasets of multi-element materials. The descriptor is based on the information regarding atomic valence shell electrons and their coordination. In this work, we develop an extension of OFM called OFM1. We have shown that these descriptors are highly applicable in predicting the physical properties of materials and in providing insights on the materials space by mapping into a low embedded dimensional space. Our experiments with transition metal/lanthanide metal alloys show that the local magnetic moments and formation energies can be accurately reproduced using simple nearest-neighbor regression, thus confirming the relevance of our descriptors. Using kernel ridge regressions, we could accurately reproduce formation energies and local magnetic moments calculated based on first-principles, with mean absolute errors of 0.03 µB and 0.10 eV/atom, respectively. We show that meaningful low-dimensional representations can be extracted from the original descriptor using descriptive learning algorithms. Intuitive prehension on the materials space, qualitative evaluation on the similarities in local structures or crystalline materials, and inference in the designing of new materials by element substitution can be performed effectively based on these low-dimensional representations.

Quantum transport localization through graphene.

Localization of atomic defect-induced electronic transport through a single graphene layer is calculated using a full-valence electronic structure description as a function of the defect density and taking into account the atomic-scale deformations of the layer. The elementary electronic destructive interferences leading to Anderson localization are analyzed. The low-voltage current intensity decreases with increasing length and defect density, with a calculated localization length ζ = 3.5 nm for a defect density of 5%. The difference from the experimental defect density of 0.5% required for an oxide surface-supported graphene to obtain the same ζ is discussed, pointing out how interactions of the graphene supporting surface and surface chemical modifications also control electronic transport localization.

Machine learning reveals orbital interaction in materials.

We propose a novel representation of materials named an 'orbital-field matrix (OFM)', which is based on the distribution of valence shell electrons. We demonstrate that this new representation can be highly useful in mining material data. Experimental investigation shows that the formation energies of crystalline materials, atomization energies of molecular materials, and local magnetic moments of the constituent atoms in bimetal alloys of lanthanide metal and transition-metal can be predicted with high accuracy using the OFM. Knowledge regarding the role of the coordination numbers of the transition-metal and lanthanide elements in determining the local magnetic moments of the transition-metal sites can be acquired directly from decision tree regression analyses using the OFM.

Novel mixture model for the representation of potential energy surfaces.

We demonstrate that knowledge of chemical physics on a materials system can be automatically extracted from first-principles calculations using a data mining technique; this information can then be utilized to construct a simple empirical atomic potential model. By using unsupervised learning of the generative Gaussian mixture model, physically meaningful patterns of atomic local chemical environments can be detected automatically. Based on the obtained information regarding these atomic patterns, we propose a chemical-structure-dependent linear mixture model for estimating the atomic potential energy. Our experiments show that the proposed mixture model significantly improves the accuracy of the prediction of the potential energy surface for complex systems that possess a large diversity in their local structures.

A theoretical investigation of the functional role of the axial methionine ligand of the Cu(A) site in cytochrome c oxidase.

The functional roles of the amino acid residues of the Cu(A) site in bovine cytochrome c oxidase (CcO) were investigated by utilizing hybrid quantum mechanics (QM)/molecular mechanics (MM) calculations. The energy levels of the molecular orbitals (MOs) involving Cu d(zx) orbitals unexpectedly increased, as compared with those found previously with a simplified model system lacking the axial Met residue (i.e., Cu(2)S(2)N(2)). This elevation of MO energies stemmed from the formation of the anti-bonding orbitals, which are generated by hybridization between the d(zx) orbitals of Cu ions and the p-orbitals of the S and O atoms of the axial ligands. To clarify the roles of the axial Met ligand, the inner-sphere reorganization energies of the Cu(A) site were computed, with the Met residue assigned to either the QM or MM region. The reorganization energy slightly increased when the Met residue was excluded from the QM region. The existing experimental data and the present structural modeling study also suggested that the axial Met residue moderately increased the redox potential of the Cu(A) site. Thus, the role of the Met may be to regulate the electron transfer rate through the fine modulation of the electronic structure of the Cu(A) "platform", created by two Cys/His residues coordinated to the Cu ions. This regulation would provide the optimum redox potential/reorganization energy of the Cu(A) site, and thereby facilitate the subsequent cooperative reactions, such as the proton pump and the enzymatic activity, of CcO. This article is part of a Special Issue entitled: Allosteric cooperativity in respiratory proteins.

Evidence-based recommender system for high-entropy alloys.

Existing data-driven approaches for exploring high-entropy alloys (HEAs) face three challenges: numerous element-combination candidates, designing appropriate descriptors, and limited and biased existing data. To overcome these issues, here we show the development of an evidence-based material recommender system (ERS) that adopts Dempster-Shafer theory, a general framework for reasoning with uncertainty. Herein, without using material descriptors, we model, collect and combine pieces of evidence from data about the HEA phase existence of alloys. To evaluate the ERS, we compared its HEA-recommendation capability with those of matrix-factorization- and supervised-learning-based recommender systems on four widely known datasets of up-to-five-component alloys. The k-fold cross-validation on the datasets suggests that the ERS outperforms all competitors. Furthermore, the ERS shows good extrapolation capabilities in recommending quaternary and quinary HEAs. We experimentally validated the most strongly recommended Fe-Co-based magnetic HEA (namely, FeCoMnNi) and confirmed that its thin film shows a body-centered cubic structure.

Explainable machine learning for materials discovery: predicting the potentially formable Nd-Fe-B crystal structures and extracting the structure-stability relationship.

New Nd-Fe-B crystal structures can be formed via the elemental substitution of LA-T-X host structures, including lanthanides (LA), transition metals (T) and light elements, X = B, C, N and O. The 5967 samples of ternary LA-T-X materials that are collected are then used as the host structures. For each host crystal structure, a substituted crystal structure is created by substituting all lanthanide sites with Nd, all transition metal sites with Fe and all light-element sites with B. High-throughput first-principles calculations are applied to evaluate the phase stability of the newly created crystal structures, and 20 of them are found to be potentially formable. A data-driven approach based on supervised and unsupervised learning techniques is applied to estimate the stability and analyze the structure-stability relationship of the newly created Nd-Fe-B crystal structures. For predicting the stability for the newly created Nd-Fe-B structures, three supervised learning models: kernel ridge regression, logistic classification and decision tree model, are learned from the LA-T-X host crystal structures; the models achieved maximum accuracy and recall scores of 70.4 and 68.7%, respectively. On the other hand, our proposed unsupervised learning model based on the integration of descriptor-relevance analysis and a Gaussian mixture model achieved an accuracy and recall score of 72.9 and 82.1%, respectively, which are significantly better than those of the supervised models. While capturing and interpreting the structure-stability relationship of the Nd-Fe-B crystal structures, the unsupervised learning model indicates that the average atomic coordination number and coordination number of the Fe sites are the most important factors in determining the phase stability of the new substituted Nd-Fe-B crystal structures.

Re-examination of half-metallic ferromagnetism for doped LaMnO(3) in a quasiparticle self-consistent GW method.

We apply the quasiparticle self-consistent GW (QSGW) method to a cubic virtual-crystal alloy La(1-x)Ba(x)MnO(3) as a theoretical representative for colossal magnetoresistive perovskite manganites. The QSGW predicts it as a fully polarized half-metallic ferromagnet for a wide range of x and lattice constant. Calculated density of states and dielectric functions are consistent with experiments. In contrast, the energies of the calculated spin wave are very low in comparison with experiments. This is affected neither by rhombohedral deformation nor the intrinsic deficiency in the QSGW method. Thus we end up with a conjecture that phonons related to the Jahn-Teller distortion should hybridize with spin waves more strongly than people thought until now.

Transport properties of a biphenyl-based molecular junction system-the electrode metal dependence.

We investigate the transport properties of a biphenyl-dithiol molecule sandwiched between electrodes made of metal Y (Y = Cu, Ag and Au) using the non-equilibrium Green's function method based on a density functional theory. The electrode metal Y has an influence on the coupling between the molecule and electrodes, and thus on the transmission peak height. For the transmission T(Y) at the Fermi energy, we obtain T(Cu)∼T(Ag)

Computational study of positron annihilation parameters for cation mono-vacancies and vacancy complexes in nitride semiconductor alloys.

We calculate positron annihilation parameters, namely the S and W parameters from the Doppler broadening spectroscopy and the positron lifetime [Formula: see text], for defect-free states as well as cation mono-vacancies and vacancy complexes in nitride semiconductor alloys Al0.5Ga0.5N, In0.5Ga0.5N and Al0.5In0.5N. The obtained distributions of these parameters differ from compound to compound. Especially, the S-W relation for In0.5Ga0.5N is very different from that for Al0.5Ga0.5N. For the cation mono-vacancies, introducing local structural parameters, their correlations with S, W and [Formula: see text] are investigated. The S and [Formula: see text] variations are well described with the size distributions of the vacancies while the W variation is related to the presence of localized d electrons. For the vacancy complexes as well as the cation mono-vacancies, multiple-linear-regression models to describe S, W and [Formula: see text] are successfully constructed using the local structural parameters as descriptors. The S-W and S-[Formula: see text] relations are also compared with those for AlN, GaN and InN.

Contact conductance of a graphene nanoribbon with its graphene nano-electrodes.

Electronically contacted between two graphene nano-electrodes, the contact conductance (G0) of a graphene nanoribbon (GNR) molecular wire is calculated using mono-electronic Elastic Scattering Quantum Chemistry (ESQC) theory. Different nano-electrode contact geometries are considered ranging from a top face to face van der Waals contact to an adiabatic funnel like planar chemical bonding. The Tamm state contributions to the GNR-graphene nano-electrode electronic interactions are discussed as a function of the molecular orbital hybridization. Contrary to the common belief, the adiabatic-like triangle shaped contact nano-graphene electrode does not provide a large G0 as compared to the abrupt contact geometry. The abrupt contact geometry is even worth than a top face to face van der Waals electronic contact with a metal.

Direct theoretical evidence for weaker correlations in electron-doped and Hg-based hole-doped cuprates.

Many important questions for high-Tc cuprates are closely related to the insulating nature of parent compounds. While there has been intensive discussion on this issue, all arguments rely strongly on, or are closely related to, the correlation strength of the materials. Clear understanding has been seriously hampered by the absence of a direct measure of this interaction, traditionally denoted by U. Here, we report a first-principles estimation of U for several different types of cuprates. The U values clearly increase as a function of the inverse bond distance between apical oxygen and copper. Our results show that the electron-doped cuprates are less correlated than their hole-doped counterparts, which supports the Slater picture rather than the Mott picture. Further, the U values significantly vary even among the hole-doped families. The correlation strengths of the Hg-cuprates are noticeably weaker than that of La2CuO4. Our results suggest that the strong correlation enough to induce Mott gap may not be a prerequisite for the high-Tc superconductivity.

Quasiparticle self-consistent GW study of cuprates: electronic structure, model parameters, and the two-band theory for Tc.

Despite decades of progress, an understanding of unconventional superconductivity still remains elusive. An important open question is about the material dependence of the superconducting properties. Using the quasiparticle self-consistent GW method, we re-examine the electronic structure of copper oxide high-Tc materials. We show that QSGW captures several important features, distinctive from the conventional LDA results. The energy level splitting between d(x(2)-y(2)) and d(3z(2)-r(2)) is significantly enlarged and the van Hove singularity point is lowered. The calculated results compare better than LDA with recent experimental results from resonant inelastic xray scattering and angle resolved photoemission experiments. This agreement with the experiments supports the previously suggested two-band theory for the material dependence of the superconducting transition temperature, Tc.

High performance organic field-effect transistors based on single-crystal microribbons and microsheets of solution-processed dithieno[3,2-b:2',3'-d]thiophene derivatives.

We present π-conjugated dithieno[3,2-b:2',3'-d]thiophene derivatives that act as high-performance p-type organic semiconductors. These molecules self-organize into single-crystal microribbons or microsheets. High carrier mobilities of up to 10.2 cm(2) V(-1) s(-1) and high on/off ratios of ~10(7) have been achieved in organic single-crystal field-effect transistors.

Modulation of electronic structures of bases through DNA recognition of protein.

The effects of environmental structures on the electronic states of functional regions in a fully solvated DNA·protein complex were investigated using combined ab initio quantum mechanics/molecular mechanics calculations. A complex of a transcriptional factor, PU.1, and the target DNA was used for the calculations. The effects of solvent on the energies of molecular orbitals (MOs) of some DNA bases strongly correlate with the magnitude of masking of the DNA bases from the solvent by the protein. In the complex, PU.1 causes a variation in the magnitude among DNA bases by means of directly recognizing the DNA bases through hydrogen bonds and inducing structural changes of the DNA structure from the canonical one. Thus, the strong correlation found in this study is the first evidence showing the close quantitative relationship between recognition modes of DNA bases and the energy levels of the corresponding MOs. Thus, it has been revealed that the electronic state of each base is highly regulated and organized by the DNA recognition of the protein. Other biological macromolecular systems can be expected to also possess similar modulation mechanisms, suggesting that this finding provides a novel basis for the understanding for the regulation functions of biological macromolecular systems.

Dependence of the conduction of a single biphenyl dithiol molecule on the dihedral angle between the phenyl rings and its application to a nanorectifier.

The transport properties of a biphenyl dithiol (BPD) molecule sandwiched between two gold electrodes are studied using the nonequilibrium Green's function method based on the density functional theory. In particular, their dependence on the dihedral angle (phi=90 degrees -180 degrees ) between two phenyl rings is investigated. While the dihedral-angle dependence of the density of states projected on the BPD molecular orbitals is small, the transport properties change dramatically with phi. The transmission at the Fermi energy exhibits a minimum at phi=90.0 degrees and greatly increases with phi. The ratio of the maximum obtained at phi=180 degrees to the minimum exceeds 100. As an application of this characteristic transport behavior, a BPD molecule functionalized with NH(2) and NO(2) groups is considered. It is found that this molecule works as a nanorectifier.

Electronic structure of DNA nucleobases and their dinucleotides explored by soft X-ray spectroscopy.

The electronic structures of a series of DNA nucleobases and their dinucleotides were investigated by N 1s X-ray absorption, X-ray photoemission, and resonant X-ray emission spectroscopy. Resonant X-ray emission spectra of the guanine base and its dinucleotide indicate that it has a weak structure at the lowest binding energy; at this energy, it isolates from the main valence band and forms the HOMO state. This indicates that the HOMO state is localized in the guanine base, as claimed by valence and core photoemissions and expected from theoretical predictions. In addition, the XAS and XES profiles of the guanine dinucleotide indicate that disruption of the aromatic character of the six-membered ring results in the localization of the pi state at the imine (-N=) site of the guanine base; this may favor charge transfer among stacked guanine bases and further influence the conductivity of DNA.

Theoretical investigation on electron transport through an organic molecule: effect of the contact structure.

Knowing how the contact geometry influences the conductance of a molecular wire junction requires both a precise determination of the molecule/metallic-electrode interface structure and an evaluation of the conductance for different contact geometries with a fair accuracy. With a greatly improved method to solve the Lippmann-Schwinger equation, we are able to include at least one atomic layer of each electrode into the extended molecule. The artificial effect of the jellium model used for the electrodes is therefore significantly reduced. Our first-principles calculations on the transport properties of a single benzene dithiolate molecule sandwiched between Au(111) surfaces show that the transmission of the bridge site contact, which is the most stable adsorption configuration in equilibrium, displays different features from those of other configurations, and that the inclusion of the surface layers of Au electrodes into the extended molecule shifts and broadens the transmission peaks due to a stronger and more realistic S-Au bonding. We discuss the geometry dependence of the transport properties by analyzing the density of states of the molecular orbitals.