Molecular classification of pesticides including persistent organic pollutants, phenylurea and sulphonylurea herbicides

Pesticide residues in wine were analyzed by liquid chromatography–tandem mass spectrometry. Retentions are modelled by structure–property relationships. Bioplastic evolution is an evolutionary perspective conjugating effect of acquired characters and evolutionary indeterminacy–morphological determination–natural selection principles; its application to design co-ordination index barely improves correlations. Fractal dimensions and partition coefficient differentiate pesticides. Classification algorithms are based on information entropy and its production. Pesticides allow a structural classification by nonplanarity, and number of O, S, N and Cl atoms and cycles; different behaviours depend on number of cycles. The novelty of the approach is that the structural parameters are related to retentions. Classification algorithms are based on information entropy. When applying procedures to moderate-sized sets, excessive results appear compatible with data suffering a combinatorial explosion. However, equipartition conjecture selects criterion resulting from classification between hierarchical trees. Information entropy permits classifying compounds agreeing with principal component analyses. Periodic classification shows that pesticides in the same group present similar properties; those also in equal period, maximum resemblance. The advantage of the classification is to predict the retentions for molecules not included in the categorization. Classification extends to phenyl/sulphonylureas and the application will be to predict their retentions.

QSPR prediction of chromatographic retention times of pesticides: partition and fractal indices

The high-performance liquid-chromatographic retentions of red-wine pesticide residues are modeled by structure-property relationships. The effect of different types of features is analyzed: geometric, lipophilic, etc. The properties are fractal dimensions, partition coefficient, etc., in linear and nonlinear correlation models. Biological plastic evolution is an evolutionary perspective conjugating the effect of acquired characters and relations that emerge among the principles of evolutionary indeterminacy, morphological determination and natural selection. It is applied to design the co-ordination index that is used to characterize pesticide retentions. The parameters used to calculate the co-ordination index are the molar formation enthalpy, molecular weight and surface area. The morphological and co-ordination indices barely improve the correlations. The fractal dimension averaged for non‑buried atoms, partition coefficient, etc. distinguishes the pesticide molecular structures. The structural and constituent classification is based on nonplanarity, and the number of cycles, and O, S, N and Cl atoms. Different behavior depends on the number of cycles.

(Co-)solvent selection for single-wall carbon nanotubes: best solvents, acids, superacids and guest-host inclusion complexes

Analysis of 1-octanol-water, cyclohexane-water and chloroform (CHCl(3))-water partition coefficients P(o-ch-cf) allows calculation of molecular lipophilicity patterns, which show that for a given atom log P(o-ch-cf) is sensitive to the presence of functional groups. Program CDHI does not properly differentiate between non-equivalent atoms. The most abundant single-wall carbon nanotube (SWNT), (10,10), presents a relatively small aqueous solubility and large elementary polarizability, P(o-ch-cf) and kinetic stability. The SWNT solubility is studied in various solvents, finding a class of non-hydrogen-bonding Lewis bases with good solubility. Solvents group into three classes. The SWNTs in some organic solvents are cationic while in water/Triton X mixture are anionic. Categorized solubility is semiquantitatively correlated with solvent parameters. The coefficient of term β is positive while the ones of ε and V negative. The electron affinity of d-glucopyranoses (d-Glcp(n)) suggests the formation of colloids of anionic SWNTs in water. Dipole moment for d-Glcp(n)-linear increases with n until four in agreement with 18-fold helix. The I(n)(z-) and SWNT(-) are proposed to form inclusion complexes with cyclodextrin (CD) and amylose (Amy). Starch, d-Glcp, CD and Amy are proposed as SWNT co-solvents. Guests-hosts are unperturbed. A central channel expansion is suggested.

Valence Topological Charge-Transfer Indices for Dipole Moments

New valence topological charge-transfer indices are applied to the calculation of dipole moments. The algebraic and vector semisum charge-transfer indices are defined. The combination of the charge-transfer indices allows the estimation of the dipole moments. The model is generalized for molecules with heteroatoms. The ability of the indices for the description of the molecular charge distribution is established by comparing them with the dipole moments of a homologous series of phenyl alcohols. Linear and non-linear correlation models are obtained. The new charge-transfer indices improve the multivariable non-linear regression equations for the dipole moment. When comparing with previous results, the variance decreases 92%. No superposition of the corresponding G_k–J_k and – pairs is observed. This diminishes the risk of co-linearity. Inclusion of the oxygen atom in the π-electron system is beneficial for the description of the dipole moment, owing to either the role of the additional p orbitals provided by the heteroatom or the role of steric factors in the π-electron conjugation. Linear and non-linear correlations between the fractal dimension and various descriptors point not only to a homogeneous molecular structure but also to the ability to predict and tailor drug properties.