Descriptors from molecular modelling

Another report on ion-pair chromatography, where computed molecular descriptors from molecular modeling were nicely correlated with experimental separation factors, was published by Karlsson, Luthman, Pettersson and Hacksell [81]. They examined factors responsible for separation of aminotetralins on achiral stationary phases in the presence of the chiral additive N-benzyloxycarbonylglycyl-L-proline (L-ZGP), a protected peptide derivative. 

Molecular dipole moments are often used as descriptors in QPSR models. They are calculated reliably by most quantum mechanical techniques, not least because they are part of the parameterization data for semi-empirical MO techniques. Higher multipole moments are especially easily available from semi-empirical calculations using the natural atomic orbital-point charge (NAO-PC) technique [40], but can also be calculated rehably using ab-initio or DFT methods. They have been used for some QSPR models. 

Different from 2D QSAR, classification models reported in the papers cited above do not always allow the identification of descriptors related to the hERG activity however, in some cases, descriptors or molecular features crucial for the assignment to either of the classes were explicitly indicated. This allowed us to tentatively collect them in Table 5.2, which when compared with Table 5.1 provides (as expected) a very similar picture of the molecular properties involved in the blockade of hERG by drugs. Even though the properties listed in Table 5.2 are not associated with a positive or a negative sign (they can only be indicated as relevant for the classification), they... 

A from the center of a positive ionizable group was identified. However, its predictive performance on a test set consisted of eight structurally similar compounds was relatively poor. To achieve a computational model with greater predictability, a descriptor-based QSPR model was also developed. Descriptors related to molecular hydrophobicity as well as hydrogen bond donor, shape and charge features contributed to explain hOCTl inhibitor properties of the analyzed compounds. 

A physical model usually predisposes to physicochemical descriptors, such as p/Ca, log P or molar volume for the whole molecule, or the equivalent descriptors for substituents on a common molecular framework. But different structures can have the same or similar property values, and we are interested in designing structures. So at some stage we must choose structural descriptors (atom types, substructural fragments, connections, or indices from molecular orbital calculations) or at least relate structure to property in order to design the appropriate structure. 

In the following, compound-class-specific correlations between Kow and selected molecular descriptors such as chlorine number, molecular connectivity indices, van der Waals volume and area, molecular volume, and polarizability are reviewed. Further, the model of Bodor, Babanyi, and Wong will be introduced, which allows estimation from molecular structure input for a broad range of compounds. 

As an alternative to describing molecules by their structural features (substruc-tural elements, functional groups) and similarly to CoMFA, this approach uses field points to describe the van der Waals and electrostatic minima and maxima that surround molecules and compares these field points. The field points that are used are derived from molecular electrostatic potential descriptors. The XED model is marketed by Cresset Biomolecular and forms the basis for the proprietary virtual screening technology FieldPrint [95]. 

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