CSCCP predicts individual component's chemical structure in a mixture, utilizing an iterative dynamic programming algorithm, and a database organized from a large collection of natural products. Initially, a LC-MS analysis of testing mixtures returns a list of m/z values for the possible components. We then utilize targeted molecular weights calculated from the list of m/z values and known scaffolds of mixtures, as necessary input information for our system. We designed an dynamic programming algorithm to computationally formulate possible chemical structures matching targeted molecular weights, by combining scaffolds analyzed from our scaffold relationship database with a weighted list of side chains. The predicted structures with statistically calculated probability will be provided, so that the most probable chemical structures of natural products and their analogs can be proposed accordingly. Click on the CSCCP listed left and start the prediction!

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