Molecular databases and chemical space

Contents I. Introduction 34 II. Molecular Descriptors and Physicochemical Properties 36 III. Molecular Databases and Chemical Space 37 IV. Chemoinformatics in Food Chemistry 40 V. Examples of Molecular Similarity, Pharmacophore Modeling, Molecular Docking, and QSAR in Food or Food-Related Components 43 A. Molecular similarity 43 B. Pharmacophore model 47 C. QSAR and QSPR 48 D. Molecular docking 49 VI. Concluding Remarks and Perspectives 52 Acknowledgments 53 References 53... 

Abstract The aim of the present chapter is to present the current research and potential applications of chemoinformatics tools in food chemistry. First, the importance and variety of molecular descriptors and physicochemical properties is delineated, and then a survey and chemical space analysis of representative databases with emphasis on food-related ones is presented. A brief description of methods commonly used in molecular design, followed by examples in food chemistry are presented, such methods include similarity searching, pharmacophore modeling, quantitative... 

Once a database of candidate molecules has been prepared, it may be desirable to select a diverse set of molecules. Diversity algorithms are designed to select sets of molecules in such a way that the chemical space from which they have been extracted is sampled democratically.1291 Molecules are represented in this space using molecular descriptors and dissimilarity between them is quantified using metrics derived from the value of the descriptors. In terms of descriptors that have been used for fragment molecules,... 

Molecular similarity and diversity methods have been developed based on the principle that similar molecules exhibit similar activi-ties/properties (l).Molecular similarity is a key concept in the identification of new molecules that have similar biological activity to one or more molecules of known activity. Molecular diversity concepts are used to explore "chemical space," with the scope of application ranging from a particular structure/reac-tion to a large database of different molecules. The process of evaluating similarity and diver-... 

Figure 2.2 shows some of these methods and how they can be used in combination it also shows the outline of the following sections in this chapter. First, the concept of chemical space, including a sketch of molecular descriptors, physicochemical properties, and databases is presented. Then, a brief description of molecular similarity, pharmacophore modeling, docking, and QSAR models with the incorporation of examples of food-related components is described. These methods are mainly used to develop and analyze SAR and the resultant models can be used to perform virtual screening. Comprehensive reviews of each of these methods are described elsewhere (Alvarez and Shoichet, 2005 Leach and Willet, 2003 Varnek and Tropsha, 2008). 

An identical approach was used by Branca et al. [16] at Merck and led to the identifcationofanovel inhibitor of poly(ADP-ribose) polymerase-1 (PARPl). The 2D descriptors were similar to the CATS all the two-point pharmacophores in each molecule were derived from all possible atom pairs and described in terms of atom types, number of Jt electrons, number of heavy atoms attached, and number of covalent bonds separating the two atoms along the shortest path. Known PARPl inhibitors were collected from patents, publications, and publicly available databases and used to train a support vector machine (SVM) classifier. A SVM constructs the plane that best separates active and inactive compounds in the multidimensional space defined by the molecular descriptors. The results of the SVM were used to classify the compounds in the Merck collection and those predicted to be active were screened. One compound was particularly potent and was chosen as the starting point for a structure-activity relationship (SAR) exploration of this chemical class. Docking studies on the PARPl crystal structure were used to guide the synthetic efforts. 

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