On Entropy-Based Molecular Descriptors: Statistical Analysis of Real and Synthetic Chemical Structures

This paper presents an analysis of entropy-based molecular descriptors. Specifically, we use real chemical structures, as well as synthetic isomeric structures, and investigate properties of and among descriptors with respect to the used data set by a statistical analysis. Our numerical results provide evidence that synthetic chemical structures are notably different to real chemical structures and, hence, should not be used to investigate molecular descriptors. Instead, an analysis based on real chemical structures is favorable. Further, we find strong hints that molecular descriptors can be partitioned into distinct classes capturing complementary information.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

Quantitative structure-toxicity relationships for chlorophenols to bioluminescent lux-marked bacteria using atom-based semi-empirical molecular-orbital descriptors

Literature data on the toxicity of chlorophenols for three luminescent bacteria (Vibrio fischeri, and the lux-marked Pseudomonas fluorescens 10586s pUCD607 and Burkholderia spp. RASC c2 (Tn4431)) have been analyzed in relation to a set of computed molecular physico-chemical properties. The quantitative structure-toxicity relationships of the compounds in each species showed marked differences when based upon semi-empirical molecular-orbital molecular and atom based properties. For mono-, di- and tri-chlorophenols multiple linear regression analysis of V. fischeri toxicity showed a good correlation with the solvent accessible surface area and the charge on the oxygen atom. This correlation successfully predicted the toxicity of the heavily chlorinated phenols, suggesting in V. fischeri only one overall mechanism is present for all chlorophenols. Good correlations were also found for RASC c2 with molecular properties, such as the surface area and the nucleophilic super-delocalizability of the oxygen. In contrast the best QSTR for P. fluorescens contained the 2nd order connectivity index and ELUMO suggesting a different, more reactive mechanism. Cross-species correlations were examined, and between V. fischeri and RASC c2 the inclusion of the minimum value of the nucleophilic susceptibility on the ring carbons produced good results. Poorer correlations were found with P. fluorescens highlighting the relative similarity of V. fischeri and RASC c2, in contrast to that of P. fluorescens.

Quantitative structure-hydrophobicity relationships of molecular fragments and beyond

Quantitative structure-property relationship (QSPR) models were firstly established for the hydrophobic substituent constant (πX) using the theoretical descriptors derived solely from electrostatic potentials (EPSs) at the substituent atoms. The descriptors introduced are found to be related to hydrogen-bond basicity, hydrogen-bond acidity, cavity, or dipolarity/polarizability terms in linear solvation energy relationship, which endows the models good interpretability. The predictive capabilities of the models constructed were also verified by rigorous Monte Carlo cross-validation. Then, eight groups of meta- or para- disubstituted benzenes and one group of substituted pyridines were investigated. QSPR models for individual systems were achieved with the ESP-derived descriptors. Additionally, two QSPR models were also established for Rekker's fragment constants (foct), which is a secondary-treatment quantity and reflects average contribution of the fragment to logP. It has been demonstrated that the descriptors derived from ESPs at the fragments, can be well used to quantitatively express the relationship between fragment structures and their hydrophobic properties, regardless of the attached parent structure or the valence state. Finally, the relations of Hammett σ constant and ESP quantities were explored. It implies that σ and π, which are essential in classic QSAR and represent different type of contributions to biological activities, are also complementary in interaction site.