“Classical” and “Magnetic” Aromaticities as new Descriptors for Heteroaromatics in QSAR. Part 3 [1]. Principal Properties for Heteroaromatics

Cyto- and enzyme toxicities of ionic liquids modelled on the basis of VolSurf+ descriptors and their principal properties

Five in silico principal properties (PPs) for 218 heterocyclic cations and four PPs for 38 organic and inorganic anionic counterparts of ionic liquids (ILs) were derived by the VolSurf+ approach. VolSurf+ physicochemical descriptors take into account several cationic structural features of ILs such as heterocyclic aromatic and non-aromatic cationic cores, alkyl chain length, presence of oxygen atoms in the substituents as well as the properties of a wide variety of inorganic and organic anions. Combination of these cation and anion PPs can provide descriptors for over 8000 ILs, thus allowing the development of QSPR models for IL cytotoxicity (IPC-81 rat cell line) and enzyme toxicity (acetylcholinesterase inhibition). The adoption of a Partial Least Squares approach, relating PPs and toxicities, provided affordable predictions for ILs in both learning and external validation sets, implying the possibility to extend the predictive model to a set of 520 ILs. This allows us to establish priorities in selecting ILs for experimental hazard assessment as required by the REACH regulation.

A multivariate insight into ionic liquids toxicities

A multivariate insight into the toxicities of ionic liquids provides a comprehensive picture and guidelines for the evaluation of their eco- and bio-sustainability.

Solvent impact on the aromaticity of benzene analogues: implicit versus explicit solvent approach

Solvent impact on the structural index of aromaticity was modelled by polarised continuum field approximation (IEFPCM) and hybrid quantum chemistry (QM/MM) method. Significant solvent related relaxation of the solutes geometries were noticed especially for highly polar species. The significant reduction of the aromaticity was observed for some aromatic compounds in water solution compared to gas phase. The rationale of this fact was provided based on dipole moment changes, energy penalty for polarisation of solute and the distribution of frontier orbital densities. The incoherent predictions of explicit and implicit solvation models are noticed since in some cases the PCM approach artificially exaggerate the geometry relaxation in solution which is not observed if explicit solvent molecules are taken into account.

Principal components describing biological activities and molecular diversity of heterocyclic aromatic ring fragments

Ten physicochemical variables have been calculated for each of 100 different aromatic rings. These variables were selected because of their potential involvement in the molecular recognition of drug-receptor binding interactions, and they include size, lipophilicity, dipole magnitude and orientation, HOMO and LUMO energies, and electronic point charges. A total of 59 different aromatic ring systems were studied including monocyclics and [5.5]-, [6.5]- and [6.6]-fused bicyclics. A principal components analysis of b1ese results generated four principal components which account for 84% of the total variance in the data. These principal components provide a quantitative measure of molecular diversity, and their relevance for structure-activity relationships is discussed. The principal components correlate with the in vitro biological activity of heterocyclic aromatic fragments within a series of previously reported HIV-1 reverse transcriptase inhibitors.

Selection of Polychlorinated Biphenyls for use in Quantitative Structure-Activity Modelling

Abstract By characterizing the 154 tetra- through heptachlorinated biphenyl (PCB) congeners with a multitude of physico-chemical descriptors, a model representing chemical similarities and differences is achieved. The multivariate characterization of the PCBs was based on 47 physico-chemical descriptor variables, which were summarised by using principal component analysis (PCA). By applying statistical design to the orthogonal scores from the PCA, a 2(4)-factorial design was used to select a set of 16 congeners. In addition, four congeners were added to provide information about the interior region of the chemical domain of PCBs. This set of 20 structurally different congeners is suggested to be used in future quantitative structure-activity relationships (QSARs) for screening of the toxicological and biochemical effects of the PCBs.