| Summary: | Bioactive peptides are often studied by applying computer analysis prior to in vitro and in vivo protocols. This has been made possible by progresses in the development of new computer technologies for chemical data processing. The chemical data analysis involves multivariate methods which are the core of chemometrics/cheminformatics. This review presents an overview of the most popular chemometric/cheminformatic methods (i.e. artificial neural networks, principal component analysis, partial least squares and quantitative structure–activity relationship approaches), used to analyze the food-derived bioactive peptides. We also describe other examples of chemometric/cheminformatic analyses like databases of chemical information, pattern similarity and molecular docking. Although, the multivariate analyses of biopeptides may require different chemometric/cheminformatic methods to construct the best predictive models, they become a useful tool in designing novel biopeptides. This tool gives the premise to integrate in silico and experimental protocols in the complex analysis of food-derived bioactive peptides.
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