Live phylogeny with polytomies: Finding the most compact parsimonious trees

Construction of phylogenetic trees has traditionally focused on binary trees where all species appear on leaves, a problem for which numerous efficient solutions have been developed. Certain application domains though, such as viral evolution and transmission, paleontology, linguistics, and phylogenetic stemmatics, often require phylogeny inference that involves placing input species on ancestral tree nodes (live phylogeny), and polytomies. These requirements, despite their prevalence, lead to computationally harder algorithmic solutions and have been sparsely examined in the literature to date. In this article we prove some unique properties of most parsimonious live phylogenetic trees with polytomies, and their mapping to traditional binary phylogenetic trees. We show that our problem reduces to finding the most compact parsimonious tree for n species, and describe a novel efficient algorithm to find such trees without resorting to exhaustive enumeration of all possible tree topologies.     

Theoretical study of dynamic electron-spin-polarization via the doublet-quartet quantum-mixed state and time-resolved ESR spectra of the quartet high-spin state

The mechanism of the unique dynamic electron polarization of the quartet (S = 3/2) high-spin state via a doublet-quartet quantum-mixed state and detail theoretical calculations of the population transfer are reported. By the photo-induced electron transfer, the quantum-mixed charge-separate state is generated in acceptor-donor-radical triad (A-D-R). This mechanism explains well the unique dynamic electron polarization of the quartet state of A-D-R. The generation of the selectively populated quantum-mixed state and its transfer to the strongly coupled pure quartet and doublet states have been treated both by a perturbation approach and by exact numerical calculations. The analytical solutions show that generation of the quantum-mixed states with the selective populations after de-coherence and/or accompanying the (complete) dephasing during the charge-recombination are essential for the unique dynamic electron polarization. Thus, the elimination of the quantum coherence (loss of the quantum information) is the key process for the population transfer from the quantum-mixed state to the quartet state. The generation of high-field polarization on the strongly coupled quartet state by the charge-recombination process can be explained by a polarization transfer from the quantum-mixed charge-separate state. Typical time-resolved ESR patterns of the quantum-mixed state and of the strongly coupled quartet state are simulated based on the generation mechanism of the dynamic electron polarization. The dependence of the spectral pattern of the quartet high-spin state has been clarified for the fine-structure tensor and the exchange interaction of the quantum-mixed state. The spectral pattern of the quartet state is not sensitive towards the fine-structure tensor of the quantum-mixed state, because this tensor contributes only as a perturbation in the population transfer to the spin-sublevels of the quartet state. Based on the stochastic Liouville equation, it is also discussed why the selective population in the quantum-mixed state is generated for the "finite field" spin-sublevels. The numerical calculations of the elimination of the quantum coherence (de-coherence and/or dephasing) are demonstrated. A new possibility of the enhanced intersystem crossing pathway in solution is also proposed.     

Machine-Learning Adsorption on Binary Alloy Surfaces for Catalyst Screening

Over the last few years, machine learning is gradually becoming an essential approach for the investigation of heterogeneous catalysis. As one of the important catalysts, binary alloys have attracted extensive attention for the screening of bifunctional catalysts. Here we present a holistic framework for machine learning approach to rapidly predict adsorption energies on the surfaces of metals and binary alloys. We evaluate different machine-learning methods to understand their applicability to the problem and combine a tree-ensemble method with a compressed-sensing method to construct decision trees for about 60000 adsorption data. Compared to linear scaling relations, our approach enables to make more accurate predictions lowering predictive root-mean-square error by a factor of two and more general to predict adsorption energies of various adsorbates on thousands of binary alloys surfaces, thus paving the way for the discovery of novel bimetallic catalysts.     

毛细管色谱柱定量分析的研究

用毛细管色谱柱进行定量分析,必须测定正确的"定量校正值"。本文提出了用标准的二元混合物测定这种校正值的方法;并探讨了不同的操作条件对定量校正值的影响。     

Phylogenetic inference from binary sequences reduced by primary DNA sequences

Given a bi-classification of nucleotides, we can obtain a reduced binary sequence of a primary DNA sequence. This binary sequence will undoubtedly retain some biological information and lose the rest. Here we want to know what kind of and how much biological information an individual binary sequence carries. Three classifications of nucleotides are explored in the present article. Phylogenetic trees are built from these binary sequences by the Neighbor-Joining (NJ) method, with evolutionary distance evaluated on the basis of a symbolic sequence complexity. We find that, for all data sets studied, binary sequences reduced by the purine/pyrimidine classification give reliable phylogeny (almost the same as that from the primary sequences), while the other two result in discrepancies at different levels. Some possible reasons and a simple model of sequence evolutionary are introduced to interpret this phenomenon.     

Computing the maximal canonical form for trees in polynomial time

Known algorithms computing a canonical form for trees in linear time use specialized canonical forms for trees and no canonical forms defined for all graphs. For a graph \(G=(V,E)\) the maximal canonical form is obtained by relabelling the vertices with \(1,\ldots ,|V|\) in a way that the binary number with \(|V|^2\) bits that is the result of concatenating the rows of the adjacency matrix is maximal. This maximal canonical form is not only defined for all graphs but even plays a special role among the canonical forms for graphs due to some nesting properties allowing orderly algorithms. We give an \(O(|V|^2)\) algorithm to compute the maximal canonical form of a tree.     

Use of robust classification techniques for the prediction of human cytochrome P450 2D6 inhibition

A new in silico model is developed to predict cytochrome P450 2D6 inhibition from 2D chemical structure. Using a diverse training set of 100 compounds with published inhibition constants, an ensemble approach to recursive partitioning is applied to create a large number of classification trees, each of which yields a yes/no prediction about inhibition for a given compound. These binary classifications are combined to provide an overall prediction, which answers the yes/no question about inhibition and provides a measure of confidence about that prediction. Compared to single-tree models, the ensemble approach is less sensitive to noise in the experimental data as well as to changes in the training set. Internal validation tests indicated an overall classification accuracy of 75%, whereas predictions applied to an external set of 51 compounds yielded 80% accuracy, with all inhibitors correctly identified. The speed and 2D nature of this model make it appropriate for high-throughput processing of large chemical libraries, and the confidence level provides a continuous scale on which to prioritize compounds.     

Simulations of microphase separation in crosslinked polymer blends

We investigate using bond‐fluctuation simulations the behavior of crosslinked symmetric binary A‐B polymer blends. The variation of the A‐B‐interaction parameter leads to microphase separation. We study it by focussing on the structure factor which we determine for different crosslink densities and for different values of the A‐B‐interaction parameter. The structure factor peaks at smaller values of the scattering vector q than predicted by de Gennes. This finding is in line with recent experiments, which, however, could not clarify its origin. We relate the finding to the topological disorder inherent in the network structure, which allows for large deformations during the separation process.     

Study of surface tension and surface properties of binary alcohol/n-alkyl acetate mixtures

The Butler equation is employed to describe quantitatively the nature, properties, and compositions of surface layers in binary liquid mixtures. Bulk mole fraction, surface molar area, and surface tension of pure components are necessary inputs for this equation. In addition, the UNIFAC group contribution method is applied to account for the nonideality of the bulk liquid as well as that of the surface layer. The average relative error obtained from the comparison of experimental and calculated surface tension values for 12 binary systems is less than 1%. Therefore, the model has good accuracy in comparison with other predictive equations. In addition to finding more information about the surface structure of binary mixtures, surface mole fraction was calculated using relative Gibbs adsorption values and an extended Langmuir model (EL). The obtained results show a good consistency between two models employed, i.e., the Gibbs adsorption model and EL model, based on the UNIFAC method.     

Time-dependent density functional theory/discrete reaction field spectra of open shell systems: The visual spectrum of [FeIII(PyPepS)2]- in aqueous solution

We report the calculated visible spectrum of [FeIII(PyPepS)2]- in aqueous solution. From all-classical molecular dynamics simulations on the solute and 200 water molecules with a polarizable force field, 25 solute/solvent configurations were chosen at random from a 50 ps production run and subjected the systems to calculations using time-dependent density functional theory (TD-DFT) for the solute, combined with a solvation model in which the water molecules carry charges and polarizabilities. In each calculation the first 60 excited states were collected in order to span the experimental spectrum. Since the solute has a doublet ground state several excitations to states are of type "three electrons in three orbitals," each of which gives rise to a manifold of a quartet and two doublet states which cannot properly be represented by single Slater determinants. We applied a tentative scheme to analyze this type of spin contamination in terms of Delta and Delta transitions between the same orbital pairs. Assuming the associated states as pure single determinants obtained from restricted calculations, we construct conformation state functions (CFSs), i.e., eigenfunctions of the Hamiltonian Sz and S2, for the two doublets and the quartet for each Delta,Delta pair, the necessary parameters coming from regular and spin-flip calculations. It appears that the lower final states remain where they were originally calculated, while the higher states move up by some tenths of an eV. In this case filtering out these higher states gives a spectrum that compares very well with experiment, but nevertheless we suggest investigating a possible (re)formulation of TD-DFT in terms of CFSs rather than determinants.     

Multi-state epoxidation of ethene by cytochrome P450: a quantum chemical study.

The epoxidation of ethene by a model for Compound I of cytochrome P450, studied by the use of density functional B3LYP calculations, involves two-state reactivity (TSR) with multiple electromer species, hence "multi-state epoxidation". The reaction is found to proceed in stepwise and effectively concerted manners. Several reactive states are involved; the reactant is an (oxo)iron(IV) porphyrin cation radical complex with two closely lying spin states (quartet and doublet), both of which react with ethene to form intermediate complexes with a covalent C-O bond and a carbon-centered radical (radical intermediates). The radical intermediates exist in two electromers that differ in the oxidation state of iron; Por(+)(*)Fe(III)OCH(2)CH(2)(*) and PorFe(IV)OCH(2)CH(2)(*) (Por = porphyrin). These radical intermediates exist in both the doublet- and quartet spin states. The quartet spin intermediates have substantial barriers for transformation to the quartet spin PorFe(III)-epoxide complex (2.3 kcal mol(-)(1) for PorFe(IV)OCH(2)CH(2)(*) and 7.2 kcal mol(-)(1) for Por(+)(*)Fe(III)OCH(2)CH(2)(*)). In contrast, the doublet spin radicals collapse to the corresponding PorFe(III)-epoxide complex with virtually no barriers. Consequently, the lifetimes of the radical intermediates are much longer on the quartet- than on the doublet spin surface. The loss of isomeric identity in the epoxide and rearrangements to other products arise therefore mostly, if not only, from the quartet process, while the doublet state epoxidation is effectively concerted (Scheme 7). Experimental trends are discussed in the light of the computed mechanistic scheme, and a comparison is made with closely related mechanistic schemes deduced from experiment.     

Modeling and benchmark data set for the inhibition of c-Jun N-terminal kinase-3

The goal of this paper is to present and describe a novel 2D- and 3D-QSAR (quantitative structure-activity relationship) binary classification data set for the inhibition of c-Jun N-terminal kinase-3 with previously unpublished activities for a diverse set of compounds. JNK3 is an important pharmaceutical target because it is involved in many neurological disorders. Accordingly, the development of JNK3 inhibitors has gained increasing interest. 2D and 3D versions of the data set were used, consisting of 313 (70 actives) and 249 (60 actives) compounds, respectively. All compounds, for which activity was only determined for the racemate, were removed from the 3D data set. We investigated the diversity of the data sets by an agglomerative clustering with feature trees and show that the data set contains several different scaffolds. Furthermore, we show that the benchmarks can be tackled with standard supervised learning algorithms with a convincing performance. For the 2D problem, a random decision forest classifier achieves a Matthew's correlation coefficient of 0.744, the 3D problem could be modeled with a Matthew's correlation coefficient of 0.524 with 3D pharmacophores and a support vector machine. The performance of both data sets was evaluated within a nested 10-fold cross-validation. We therefore suggest that the data set is a reasonable basis for generating QSAR models for JNK3 because of its diverse composition and the performance of the classifiers presented in this study.     

Ties in proximity and clustering compounds

Hierarchical clustering algorithms such as Wards or complete-link are commonly used in compound selection and diversity analysis. Many such applications utilize binary representations of chemical structures, such as MACCS keys or Daylight fingerprints, and dissimilarity measures, such as the Euclidean or the Soergel measure. However, hierarchical clustering algorithms can generate ambiguous results owing to what is known in the cluster analysis literature as the ties in proximity problem, i.e., compounds or clusters of compounds that are equidistant from a compound or cluster in a given collection. Ambiguous ties can occur when clustering only a few hundred compounds, and the larger the number of compounds to be clustered, the greater the chance for significant ambiguity. Namely, as the number of "ties in proximity" increases relative to the total number of proximities, the possibility of ambiguity also increases. To ensure that there are no ambiguous ties, we show by a probabilistic argument that the number of compounds needs to be less than 2(n 1/4), where n is the total number of proximities, and the measure used to generate the proximities creates a uniform distribution without statistically preferred values. The common measures do not produce uniformly distributed proximities, but rather statistically preferred values that tend to increase the number of ties in proximity. Hence, the number of possible proximities and the distribution of statistically preferred values of a similarity measure, given a bit vector representation of a specific length, are directly related to the number of ties in proximities for a given data set. We explore the ties in proximity problem, using a number of chemical collections with varying degrees of diversity, given several common similarity measures and clustering algorithms. Our results are consistent with our probabilistic argument and show that this problem is significant for relatively small compound sets.     

Computer-aided product design of alternative solvents based on phase equilibrium synergism in mixtures

A systematic methodology is proposed to find binary azeotropic mixtures as new alternative solvents for the extraction process of volatile aroma molecules widely used in perfume and cosmetic industries. We investigated the use of the reverse engineering approach with computer-aided product design (CAPD) instead of the traditional “trial and error” approach. First, the design problem is defined from the real functionalities of the classical solvents. The latter are translated into physicochemical properties and the corresponding boundary values for each property are defined. The reverse engineering method coupled with CAPD consists in using optimization techniques for building molecular structures that match as best as possible the complete set of target physicochemical properties, thus defining for each candidate a performance index. Property values are evaluated by using group contribution methods for each molecular structure generated by a CAPD tool or by using database values. Acknowledging the contradictory relationship between two selected physicochemical properties, that is, low boiling temperature and high flash point, which is rarely found in pure components, binary azeotropic mixtures were studied to enhance the global performance of solvent candidates. Dimethyl carbonate used as a solvent for the extraction of aroma molecules from plants exhibits between the boiling temperature and the flash point. It was selected as the key component for designing binary azeotropic mixtures. The global performance of the binary azeotropic mixtures was verified by means of calculations of the vapor–liquid and liquid–liquid equilibrium using modified universal functional activity coefficient (UNIFAC) method as a thermodynamic method.     

Chiral recognition of protected amino acids by means of fluorescent binary complex pyrene/heptakis-(6-amino)-(6-deoxy)-β-cyclodextrin

The ability of the binary complex pyrene (Py)/heptakis-(6-amino)-(6-deoxy)-β-cyclodextrin (am-β-CD) to act as a chiral selector was tested at two pH values (8.0 and 9.0). Phenylalanine (Phe), methionine (Met) and histidine (His) were used as chiral model molecules. The stability of ternary complexes Py/am-β-CD/amino acid was determined by means of spectrofluorimetric measurements. The data collected showed an increase in stability going from the binary to ternary complex and above all the possibility to use the binary complex as a chiral selector. Finally, data collected at two pH values showed that the binary complex is a better chiral selector when charged rather than in its neutral form.     

气相中W~+活化CO_2分解的自旋禁阻反应机理

用密度泛函理论中的UB3LYP方法,对W采用相对论校正赝势基组(SDD),对C、O采用6-311+G(3d)基组,研究了气相中不同自旋态W+活化CO2分解的反应机理.计算结果表明,W+活化CO2分解反应以六重态进入反应通道,经过六重态势能面到四重态势能面的系间窜越(ISC),最后产物WO+和CO以四重态离开反应通道.运用Harvey方法优化出最低能量交叉点(MECP),并计算了MECP处的自旋-轨道耦合(SOC)常数(494.95cm-1),势能面的交叉和在MECP处较强的自旋-轨道耦合作用降低了自旋禁阻反应能垒,为反应提供了一条低能反应路径,反应总放热量为122.33kJ.mol-1.     

Optimal separation sequence for three-component mixtures

In this paper, the problem of finding the optimal separation sequence for a three-component mixture in a cascade of two binary separation stages is considered. The minimal energy that is needed for a separation in a two-stage mechanical separation subject to a given flow rate of the input mixture is obtained. Optimization is achieved by selecting the optimal sequence of binary separations and by distributing mass-exchange surfaces between separation stages optimally. For a heat-driven two-stage separation system, it is shown that the rate of flow of the input mixture cannot be higher than some bound. This bound (the maximal possible rate of heat-driven separation) and the separation sequence when it is achieved are derived.     

Equilibrium adsorption at crystal-melt interfaces in Lennard-Jones alloys

Although the properties of crystal-melt interfaces have been extensively studied in pure materials, effects of alloying on the interfacial free energy remain relatively poorly understood. In this work we make use of Monte Carlo computer simulations for model binary Lennard-Jones alloys to explore the effects which variations in atomic-size mismatch and the chemical contributions to mixing energies have upon density and composition profiles, as well as the resulting magnitudes of equilibrium adsorption coefficients in concentrated alloys. We study four different model systems covering a range of chemical and size mismatch, finding relatively small adsorption values which are nevertheless statistically different from zero.     

测定晶体结构的系统试差法的研究(Ⅱ)系统位相超解方程的改进

本文证明了的大小是由结构决定的。与原点无关,在这种认识的基础上,提出了用归一化结构振幅|E|估量它的三种模式。特别是通过四位相结构不变量的二级Noighborhood原理解决三位相不变量间的匹配问题而算出的,这是在没有位相数据的情况下对它的理想的估量。予期它能改进系统试差法中位相超解方程的功能,提高测得位相的准确性。     

Theoretical study of activation Fe–O bond of FeO by CO in the gas phase

The entire reaction mechanism for the gas phase CO–CO₂ conversion by FeO⁺ is discussed by means of the density functional theory and the intrinsic reaction coordinate approach. The calculated results have strongly indicated that the reaction of is a spin-forbidden reaction between the quartet and the sextet potential energy surfaces (PESs). There is a crossing point between the quartet and the sextet potential energy surfaces which may play a significant role in this reaction, by which the activation energy can be decreased from −15.1 to −56.4 kJ mol⁻¹ at the reaction system.