Retrained Classification of Tyrosinase Inhibitors and “In Silico” Potency Estimation by Using Atom-Type Linear Indices

In this paper, the authors present an effort to increase the applicability domain (AD) by means of retraining models using a database of 701 great dissimilar molecules presenting anti-tyrosinase activity and 728 drugs with other uses. Atom-based linear indices and best subset linear discriminant analysis (LDA) were used to develop individual classification models. Eighteen individual classification-based QSAR models for the tyrosinase inhibitory activity were obtained with global accuracy varying from 88.15-91.60% in the training set and values of Matthews correlation coefficients (C) varying from 0.76-0.82. The external validation set shows globally classifications above 85.99% and 0.72 for C. All individual models were validated and fulfilled by OECD principles. A brief analysis of AD for the training set of 478 compounds and the new active compounds included in the re-training was carried out. Various assembled multiclassifier systems contained eighteen models using different selection criterions were obtained, which provide possibility of select the best strategy for particular problem. The various assembled multiclassifier systems also estimated the potency of active identified compounds. Eighteen validated potency models by OECD principles were used.

Modelling Liquid Flow Through Carbon Nanotubes

In this paper, the structure of a liquid and character of its flow in carbon nanotube is investigated. A review of the literature and the results of experiments show that the simulation of fluid flow for nanoscale systems should be based on the continuum hypothesis taking into account the quantized character of the liquid in the length scale of intermolecular distances. Consideration of the flow characteristics allowed construction of the analogy of behavior of the liquid in a nanotube with a flow of a viscoplastic Bingham fluid. A model of mass transfer of liquid in a nanotube, based on the possibility of forming an empty interlayer between the moving fluid particles and the particles of the wall of the nanotube, is presented.

An Efficient Algorithm for Automating Classification of Chemical Reactions into Classes in Ugi’s Reaction Scheme

There are two approaches for classification of chemical reactions: Model-Driven and Data-Driven. In this paper, the authors develop an efficient algorithm based on a model-driven approach developed by Ugi and co-workers for classification of chemical reactions. The authors’ algorithm takes reaction matrix of a chemical reaction as input and generates its appropriate class as output. Reaction matrices being symmetric, matrix implementation of Ugi’s scheme using upper/lower tri-angular matrix is of O(n2) in terms of space complexity. Time complexity of similar matrix implementation is O(n4), both in worst case as well as in average case. The proposed algorithm uses two fixed size look-up tables in a novel way and requires constant space complexity. Time complexity both in worst and average cases of the algorithm is linear.

Hydrogen-Bonded Interactions in the Systems L-Cysteine - H2SeO3 and L-Cysteine -H2SeO4

Using the density functional theory method at the B3LYP/6-31G(d,p) level of theory, the formation of hydrogen-bonded complexes of L-cysteine with selenious and selenic acids has been studied. In both cases of selenium-containing acids, the complexes occur preferably by cysteine carboxylic group, therewith the enthalpy of formation values consist from –19 to –21 kcal/mol, and free energy from –6 to –9 kcal/mol. Probably, the initial act of interaction in the system hydroxyl-containing selenium compound - a-amino acid, proceeding with mutual orientation of the reactants molecules and intermolecular hydrogen bonds formation, serves as a prerequisite for the thiol group capability of participating in the subsequent stages (including more completed transformations) of biologically important reactions.

Graph-Theoretical Indices based on Simple, General and Complete Graphs

Valence molecular connectivity indices are based on the concept of valence delta, d v, that can be derived from general chemical graphs or chemical pseudographs. A general graph or pseudograph has multiple edges and loops and can be used to encode, through the valence delta, chemical entities. Two graph-theoretical concepts derived from chemical pseudographs are the intrinsic (I) and the electrotopological state (E) values, which are the used to define the valence delta of the pseudoconnectivity indices, ?I,S. Complete graphs encode, through a new valence delta, the core electrons of any atoms in a molecule. The connectivity indices, either valence connectivity or pseudoconnectivity, are the starting point to develop the dual connectivity indices. The dual indices show that not only can they assume negative values but also cover a wide range of numerical values. The central parameter of the molecular connectivity theory, the valence delta, defines a completely new set of connectivity indices, which can be distinguished by their configuration and advantageously used to model different properties and activities of compounds.

Application of Molecular Topology to the Prediction of Water Quality Indices of Alkylphenol Pollutants

In this paper, topological-mathematical models based on multilineal regression analysis have been built as a model of the degradability of 26 alkylphenols through the Chemical Oxygen Demand (COD) and Biochemical Oxigen Demand (BOD5). Two models with three-variable were selected (r2= 0.8793 and q2=0.8075 for log(1/COD) and r2= 0.8928 and q2=0.8327 for log(1/BOD5). The models were validated by cross-validation, internal validation and randomization tests. The results, which stand in good accordance with the obtained results, confirm the robustness of the method.

Theoretical Studies on the Structure and Spectroscopic Properties of 2,4-D (2,4-Diclorofenoxiacetic Acid)

The 2,4-dichlorophenoxyacetic acid (2,4-D) is applied to and recovered from the leaf surfaces of garden bean and corn plants. This paper examines the theoretical study of the 2,4-D IR and UV spectra as well as the determination of its optimized molecular structure. Theoretical calculations are performed at the density functional theory (DFT) levels. The different structural and electronic effects determining the molecular stability of the conformers are discussed in a comparative fashion. The optimized geometry was calculated via the B3LYP method with 6-311G(d,p) and 6-311++G(d,p) basis sets and the FT-IR spectra was calculated by the density functional B3LYP method with the 6-311++G(d,p) basis set. The scaled theoretical wavenumbers show good agreement with the experimental values. A detailed interpretation of the infrared spectra of 2,4-D is reported.

Characterization of Polycyclic Aromatic Hydrocarbon Profiles by Multivariate Statistical Analysis

In the present study, statistical methods based on multivariate analyses such as the Descriptive Discriminant Analysis (DDA) and Principal Component Analysis (PCA) were applied to determine relationships between particle sizes and the composition of the associated semi-volatile compounds, in addition to evaluating these observations in relation to the emission sources, study areas, sampling campaigns and season. Results from the DDA showed that the PAHs distributions give the best discrimination capacity within the data set, whereas the PAH distribution in intermediate particle fractions incorporates noise in the statistical analysis. The PCA was useful in identifying the main emission sources in each study area. It showed that in the city of La Plata the most important pollution sources are traffic emissions and the industrial activity associated with oil and petrochemical plants. In Leipzig, the main sources are those associated with traffic and also a power plant. The combined PCA and DDA methods applied to PAH distributions is a valuable tool in characterizing types of emissions burdens and also in obtaining a differentiation of sample identity according to study areas and sampling times.

Toxicity of Halogen, Sulfur and Chlorinated Aromatic Compounds

In this paper, quantitative–structure–toxicity–relationship (QSTR) models are developed for predicting the toxicity of halogen, sulfur and chlorinated aromatic compounds. Two sets of compounds, containing mainly halogen and sulfur inorganic compounds in the first set and chlorinated aromatic compounds in the second, are investigated for their toxicity level with the aid of the conceptual Density Functional Theory (DFT) method. Both sets are tested with the conventional density functional descriptors and with a newly proposed net electrophilicity descriptor. Associated R2, R2CV and R2adj values reveal that in the first set, the proposed net electrophilicity descriptor (??±) provides the best result, whereas in the second set, electrophilicity index (?) and a newly proposed descriptor, net electrophilicity index (??±) provide a comparable performance. The potential of net electrophilicity index to act as descriptor in development of QSAR model is also discussed.

Modeling of Fluid Interaction Produced by Water Hammer

This paper compares the computational performance of two numerical methods for two models of Transient Flow. One model was defined by method of the Eulerian based expressed in a method of characteristics “MOC”, finite difference form. The other model was defined by method of Regression. Each method was encoded into an existing hydraulic simulation model. Results indicated that the accuracy of the methods was comparable but that the “MOC” was more computationally efficient for analysis of large water transmission line. Practical investigations in this article have shown mainly this tendency.