Receptor interaction descriptors

Martin et al. typically use about 18 substituent properties lipophilicity, about five shape descriptors, about seven chemical functionality descriptors, and about five receptor interaction descriptors. These properties were selected because they are readily calculated for virtually any chemical fragment, while still capturing many of the important efifeas mentioned above. 

In 1996, Sheridan et al. [16] were the first to use pharmacophoric atom types for an autocorrelation approach. This technique is suited to characterize ligand-receptor interactions in a general way, allowing for more different but equally interacting molecules to be identified as similar. Sheridan et al. also extended the topological Carhart approach to the 3D case, and this was soon followed up by a binary representation of such a descriptor [17]. In 2003, Stiefl and Baumann [18] reported an autocorrelation approach using surface points representing pharmacophoric features. 

Moreover, a final 3D-QSAR model vahdation was done using a prospective study with an external test set. The 82 compounds from the data set were used in a lead optimization project. A CoMFA model gave an (cross validated) value of 0.698 for four relevant PLS components and a conventional of 0.938 were obtained for those 82 compounds. The steric descriptors contributed 54% to the total variance, whereas the electrostatic field explained 46%. The CoMSIA model led to an (cross vahdated) value of 0.660 for five PLS components and a conventional of 0.933. The contributions for steric, electrostatic, and hydrophobic fields were 25, 44, and 31%. As a result, it was proved that the basic S4-directed substituents should be replaced against more hydrophobic building blocks to improve pharmacokinetic properties. The structural and chemical interpretation of CoMFA and CoMSIA contour maps directly pointed to those regions in the Factor Xa binding site, where steric, electronic, or hydrophobic effects play a dominant role in ligand-receptor interactions. 

To accoimt for steric effects in molecule-receptor interactions, the weighted information indices by volume have been proposed [Ray et al, 1985]. These molecular descriptors are calculated in the same way as the indices of neighbourhood symmetry defined above using the atomic van der Waals volumes to get the probabilities of the equivalence classes. In other words, the van der Waals voliunes of the atoms belonging to each equivalent class are summed to give a molecule subvolume, then divided by the total molecule volume. For example, the weighted information content by volume is defined as ... 

Molecular orbital fields are descriptors particularly useful when an ionic or charge transfer reaction is part of the ligand-receptor interaction in this case, electrostatic fields are not able to fully represent the electronic characteristics of molecules. 

The chemical structure representation in Apex-3D is based on the concept of a descriptor center that represents a part of the hypothetical biophore. Descriptor centers can be atoms, sets of atoms, pseudo-atoms, or substructures that participate in ligand-receptor interactions. The interaction is derived from electrostatic, hydrophobic, dispersion force, and charge-transfer information that comes from quantum-chemical calculations or from atomic conkibutions to hydrophobicity or molar refractivity. 

In QSAR of enzyme inhibition reactions, quantum-chemically calculated electrostatic or MO-related descriptors have been widely used. The former are expected to describe the complex formation between enzyme and the substrate, whereas the latter reflect the chemical reactivity of the substrate at the site. Already in 1967, Klopman and Hudson [83] developed a polyelectronic perturbation theory, according to which the drug-receptor interactions can be under either charge or orbital control. Thus the net atomic... 

The toxicity of compounds has often been related to the polarizability of compounds. This descriptor is related to the intermolecular interactions in biological environments and can be ascribed both to the drug-receptor interactions as well as to the properties determining the bioavailability of a compound [112], Thus it was shown that even the CNDO/2 calculated molecular polarizability (a) can be successfully correlated with the acute toxicity in a series of 20 nitriles [113] ... 

Before addressing some aspects of, broadly speaking, ligand-receptor interactions, a critical evaluation of protein structure determination was felt in order. This is then followed by accounts of docking and scoring, pharmacophore identification 3D searching, substructure searching, and molecular descriptors. 

The first four chapters and Chapter 6 are connected with 3D molecular descriptors and their uses for QSAR and molecular similarity studies associated with molecular modeling of agonist-receptor interactions, with drug design, and with the discovery of new lead compounds for various types of biological activities. 

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