Descriptive QSAR

The field points must then be fitted to predict the activity. There are generally far more field points than known compound activities to be fitted. The least-squares algorithms used in QSAR studies do not function for such an underdetermined system. A partial least squares (PLS) algorithm is used for this type of fitting. This method starts with matrices of field data and activity data. These matrices are then used to derive two new matrices containing a description of the system and the residual noise in the data. Earlier studies used a similar technique, called principal component analysis (PCA). PLS is generally considered to be superior. 

Ivanduc, O., Balahan, A. T. The graph description of chemical structures. In Topological Indices and Related Descriptors in QSAR and QSPR, Devillers,). 

Raevsky, O. A. QSAR description of molecular strucmre. In QSAR in Drug Design and Toxicology, Hadzi, D., Jerman-Blazic, B. (eds.), Elsevier, Amsterdam, 1987, pp. 31-36. 

Table 4 Most relevant QSAR tools to estimate physicochemical and toxicological properties Tool Description Ref...

The final part is devoted to a survey of molecular properties of special interest to the medicinal chemist. The Theory of Atoms in Molecules by R. F.W. Bader et al., presented in Chapter 7, enables the quantitative use of chemical concepts, for example those of the functional group in organic chemistry or molecular similarity in medicinal chemistry, for prediction and understanding of chemical processes. This contribution also discusses possible applications of the theory to QSAR. Another important property that can be derived by use of QC calculations is the molecular electrostatic potential. J.S. Murray and P. Politzer describe the use of this property for description of noncovalent interactions between ligand and receptor, and the design of new compounds with specific features (Chapter 8). In Chapter 9, H.D. and M. Holtje describe the use of QC methods to parameterize force-field parameters, and applications to a pharmacophore search of enzyme inhibitors. The authors also show the use of QC methods for investigation of charge-transfer complexes. 

Indeed, considering the latter 3D QSAR model, the features that make a molecule suitable to bind to the hERG channel start delineating in a chemically interpretable manner, but, it is rather dear how these kinds of models emphasize mostly the 3D steric aspects of molecules, depending mainly on factors such as the conformation (or the conformational analysis protocol) or the alignment of the molecules. To obtain a description of the characteristics of hERG-blocking molecules in terms of measurable (computable) properties in a way that the physicochemical determinants of the activity can be identified, the classical 2D QSAR approach is well suited. 

The underlying theory of Quantitative Structure-Activity Relationship (QSAR) is that biological activity is directly related to molecular structure. Therefore, molecules with similar structure will possess similar bioactivities for similar proteins/receptors/enzymes and the changes in structure will be represented through the changes in the bioactivities. The best general description of a QSAR model is... 

An Alignment-Free 3D Description of Local Lipophilicity for QSAR Studies... 

The major hurdle to overcome in the development of 3D-QSAR models using steric, electrostatic, or lipophilic fields is related to both conformation selection and subsequent suitable overlay (alignment) of compounds. Therefore, it is of some interest to provide a conformation-ally sensitive lipophilicity descriptor that is alignment-independent. In this chapter we describe the derivation and parametrization of a new descriptor called 3D-LogP and demonstrate both its conformational sensitivity and its effectiveness in QSAR analysis. The 3D-LogP descriptor provides such a representation in the form of a rapidly computable description of the local lipophilicity at points on a user-defined molecular surface. 

The chapter is divided into three sections the first part is concerned with the derivation of 3D-LogP descriptor and the selection of suitable parameters for the computation of the MLP values. This study was performed on a set of rigid molecules in order, at least initially, to avoid the issue of conformation-dependence. In the second part, both the information content and conformational sensitivity of the 3D-LogP description was established using a set of flexible acetylated amino acids and dipeptides. This initial work was carried out using log P as the property to be estimated/predicted. However, it should be made clear that, while the 3D-LogP descriptor can be used for the prediction of log P, this was not the primary intention behind its the development. Rather, as previously indicated, the rationale for this work was the development of a conformationally sensitive but alignment-free lipophilicity descriptor for use in QSAR model development. The use of log P as the property to be estimated/predicted enables one to establish the extent of information loss, if any, in the process used to transform the results of MLP calculations into a descriptor suitable for use in QSAR analyses. 

To test the potential of PLS to predict odour quality, it was used in a QSAR study of volatile phenols. A group of trained sensory panelists used descriptive analysis (28) to provide odour profiles for 17 phenols. The vocabulary consisted of 44 descriptive terms, and a scale fiom 0 (absent) to S (very strong) was used. The panel average sensory scores for the term sweet were extracted and used as the Y-block of data, to be predicted from physico-chemical data. 

Atom description in QSAR models development and use of an atom level index, 22, 1 Autoradiographic investigations of cholinergic and other receptors in the motor endplate, 3, 81 The Binding of drugs to blood plasma macromolecules Recent advances and therapeutic... 

This chapter focuses on computational studies which employ a combination of structure-based and 3D QSAR methods as a mean to predict the affinity of a ligand for its receptor. The comprehensive utility of this approach is exemplified by case studies published in the last few years and from our laboratory. Special emphasis will be placed on a detailed description of the combined structure-ligand-based approach and the successful application of this procedure to the design of novel drug molecules. 

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