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In Silico Strategies to Predict Anti-aging Features of Whey Peptides

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Abstract

We have analysed the in silico potential of bioactive peptides from cheese whey, the most relevant by-product from the dairy industry, to bind into the active site of collagenase and elastase. The peptides generated from the hydrolysis of bovine β-lactoglobulin with three proteases (trypsin, chymotrypsin, and subtilisin) were docked onto collagenase and elastase by molecular docking. The interaction models were ranked according to their free binding energy using molecular dynamics simulations, which showed that most complexes presented favourable interactions. Interactions with elastase had significantly lower binding energies than those with collagenase. Regarding the interaction site, it was found that four bioactive peptides were positioned in collagenase’s active site, while six were found in elastase’s active site. Among these, the most we have found one promising collagen-binding peptide produced by chymotrypsin and two for elastase, produced by subtilisin and chymotrypsin. These in silico results can be used as a tool for designing further experiments aiming at testing the in vitro potential of the peptides found in this work.

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Data Availability

Raw data from this study are available at an online repository at https://github.com/gabrielarama/RamaTimmersSouza2022.

Abbreviations

MMP:

Matrix metalloproteinase

ECM:

Extracellular matrix

BAPs:

Bioactive peptides

CW:

Cheese whey

BLG:

β-Lactoglobulin

DHt :

Theoretical degree of hydrolysis

AAs:

Amino acids

MD:

Molecular dynamics

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Acknowledgements

This work was supported by the Brazilian Council for Scientific and Technological Development (CNPq) (Grant no. 308515/2020-0), the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES), and University of Vale do Taquari—Univates. This study was partially funded by CAPES—Finance Code 001.

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Correspondence to Luís Fernando Saraiva Macedo Timmers or Claucia Fernanda Volken de Souza.

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Rama, G.R., Saraiva Macedo Timmers, L.F. & Volken de Souza, C.F. In Silico Strategies to Predict Anti-aging Features of Whey Peptides. Mol Biotechnol (2023). https://doi.org/10.1007/s12033-023-00887-9

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