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Extra info for Advances in Food and Nutrition Research

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J. Nutr. 43(4), 198–204. , and Ohri, D. (2003). Genetic variability and heritability of selected traits during different cuttings of vegetable Chenopodium. Ind. J. Genet. Pl. Breed 63, 359–360. , and Ohri, D. (2005). Seed protein electrophoresis of some cultivated and wild species of Chenopodium. Biol. Plan. 49(4), 505–511. , and Ohri, D. (2006). Chenopodium quinoa—An Indian perspective. Ind. Crops Prod. 23, 73–87. , and Karwe, M. (2007). Effects of processing on the nutraceutical profile of quinoa.

For instance, for 2D representations, the molecules can be represented by fingerprints, SMILES, or SMARTS strings; such files use a small amount of memory. mol2; in all these cases the files contain the 3D coordinates of the structures, thus the conformation can be defined. III. MOLECULAR DATABASES AND CHEMICAL SPACE The advent of experimental techniques such as combinatorial and parallel chemical synthesis, and high-throughput screening has enabled the production of massive amounts of data. These compound databases have played a key role in drug design (Miller, 2002) and other research areas such as Agrochemistry and Food Chemistry.

In general, large databases are used for studying the chemical space or as a data source for virtual screening, whereas smaller datasets (<50 compounds) can be used to generate, for instance, pharmacophore or quantitative structure–activity relationships (QSARs) models. In many cases, the system under study involves interactions of small molecules (ligands) with a particular target(s). When the 3D structure of the target is known from X-ray crystallography, NMR, or homology models, the technique of choice is molecular docking.

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