An in silico Investigation of Anticancer Peptide Candidates in Fermented Food Microbiomes

Year 2023, , 64 - 72, 11.05.2023

Muzaffer Arıkan

https://doi.org/10.26650/experimed.1262138

Abstract

Objective: Cancer is a leading cause of death worldwide, requires development of new effective, specific, and safe strategies that do not carry the disadvantages of traditional cancer treatment approaches. Hence, this study aimed to identify anticancer peptide candidates in fermented food microbiomes through an in silico investigation.
Materials and Methods: One hundred eight shotgun metagenomic sequencing samples from six studies on fermented food microbiomes were downloaded from the NCBI and ENA databases and included in the study. Bioinformatic analyses including quality control of raw data, de novo assembly, prediction of protein sequences, anticancer peptide predictions by an integrated use of four different prediction tools, toxicity predictions and database comparisons were performed.
Results: One hundred forty-two novel anticancer peptide candidates were identified. Liquor, coffee, kefir fermentation samples contained the greatest numbers of anticancer peptide candidates while sugar, dairy, coconut kefir and brine-type fermentations were dominant sources according to the substrate type.
Conclusion: This study indicates the potential of fermented food microbiomes as a useful source for candidate anticancer peptide detection. In vitro and in vivo validations of detected peptides may lead to development of new candidate molecules for cancer therapy in the future.

Keywords

Fermented food, microbiome, bioinformatics, metagenomics, anticancer peptide

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