Chemometrics and cheminformatics in the analysis of biologically active peptides from food sources

• Chemometrics/cheminformatics is used to analyze small molecules, including biopeptides.
• ANN, PCA and PLS may be used to study bioactive peptides from food sources.
• QSAR is one of the useful techniques in peptide structure–activity prediction.
• Cheminformatic databases and other tools suitable in biopeptide analyses are also described.
• Chemometrics/cheminformatics can be useful in designing peptides with biological functions.

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.