Virtual Screening of Cathelicidin-Derived Anticancer Peptides and Validation of Their Production in the Probiotic Limosilactobacillus fermentum KUB-D18 Using Genome-Scale Metabolic Modeling and Experimental Approaches

The development of anticancer peptides (ACPs) has emerged as a promising strategy in targeted cancer therapy due to their high specificity and therapeutic potential. Cathelicidin-derived antimicrobial peptides represent a particularly attractive class of ACPs, yet systematic evaluation of their anticancer activity remains limited. In this study, we conducted virtual screening of eight cathelicidin-derived peptides (AL-38, LL-37, RK-31, KS-30, KR-20, FK-16, FK-13, and KR-12) to assess their potential against colon cancer. Among these, LL-37 and FK-16 were identified as the most promising candidates, with LL-37 exhibiting the strongest inhibitory effects on both non-metastatic (HT-29) and metastatic (SW-620) colon cancer cell lines in vitro. To overcome challenges associated with peptide stability and delivery, we employed the probiotic lactic acid bacterium <i>Limosilactobacillus fermentum</i> KUB-D18 as both a biosynthetic platform and delivery vehicle. A genome-scale metabolic model (GEM), <i>i</i>TM505, was reconstructed to predict the strain's biosynthetic capacity for ACP production. Model simulations identified trehalose, sucrose, maltose, and cellobiose as optimal carbon sources supporting both high peptide yield and biomass accumulation, which was subsequently confirmed experimentally. Notably, <i>L. fermentum</i> expressing LL-37 achieved a growth rate of 2.16 gDW/L, closely matching the model prediction of 1.93 gDW/L (accuracy 89.69%), while the measured LL-37 concentration (26.96 ± 0.08 µM) aligned with predictions at 90.65% accuracy. The strong concordance between in silico predictions and experimental outcomes underscore the utility of GEM-guided metabolic engineering for optimizing peptide biosynthesis. This integrative approach-combining virtual screening, genome-scale modeling, and experimental validation-provides a robust framework for accelerating ACP discovery. Moreover, our findings highlight the potential of probiotic-based systems as effective delivery platforms for anticancer peptides, offering new avenues for the rational design and production of peptide therapeutics.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-10-16
DOI
https://doi.org/10.3390/ijms262010077
Citations
1
Primary Topic
Antimicrobial Peptides and Activities
Type
article
Field-Weighted Citation Impact
1.18

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article

Virtual Screening of Cathelicidin-Derived Anticancer Peptides and Validation of Their Production in the Probiotic Limosilactobacillus fermentum KUB-D18 Using Genome-Scale Metabolic Modeling and Experimental Approaches

Pramote Chumnanpuen, Chomdao Sinthuvanich, Nisit Watthanasakphuban, Vichugorn Wattayagorn et al.
1 citations
International Journal of Molecular Sciences
Antimicrobial Peptides and Activities
1.18
article

Virtual Screening of Cathelicidin-Derived Anticancer Peptides and Validation of Their Production in the Probiotic Limosilactobacillus fermentum KUB-D18 Using Genome-Scale Metabolic Modeling and Experimental Approaches

Pramote Chumnanpuen, Chomdao Sinthuvanich, Nisit Watthanasakphuban, Vichugorn Wattayagorn, Taratorn Mansuwan, Krittapas Angkanawin, Chakkapan Sapkaew
article en
1 citations

Abstract

The development of anticancer peptides (ACPs) has emerged as a promising strategy in targeted cancer therapy due to their high specificity and therapeutic potential. Cathelicidin-derived antimicrobial peptides represent a particularly attractive class of ACPs, yet systematic evaluation of their anticancer activity remains limited. In this study, we conducted virtual screening of eight cathelicidin-derived peptides (AL-38, LL-37, RK-31, KS-30, KR-20, FK-16, FK-13, and KR-12) to assess their potential against colon cancer. Among these, LL-37 and FK-16 were identified as the most promising candidates, with LL-37 exhibiting the strongest inhibitory effects on both non-metastatic (HT-29) and metastatic (SW-620) colon cancer cell lines in vitro. To overcome challenges associated with peptide stability and delivery, we employed the probiotic lactic acid bacterium <i>Limosilactobacillus fermentum</i> KUB-D18 as both a biosynthetic platform and delivery vehicle. A genome-scale metabolic model (GEM), <i>i</i>TM505, was reconstructed to predict the strain's biosynthetic capacity for ACP production. Model simulations identified trehalose, sucrose, maltose, and cellobiose as optimal carbon sources supporting both high peptide yield and biomass accumulation, which was subsequently confirmed experimentally. Notably, <i>L. fermentum</i> expressing LL-37 achieved a growth rate of 2.16 gDW/L, closely matching the model prediction of 1.93 gDW/L (accuracy 89.69%), while the measured LL-37 concentration (26.96 ± 0.08 µM) aligned with predictions at 90.65% accuracy. The strong concordance between in silico predictions and experimental outcomes underscore the utility of GEM-guided metabolic engineering for optimizing peptide biosynthesis. This integrative approach-combining virtual screening, genome-scale modeling, and experimental validation-provides a robust framework for accelerating ACP discovery. Moreover, our findings highlight the potential of probiotic-based systems as effective delivery platforms for anticancer peptides, offering new avenues for the rational design and production of peptide therapeutics.

International Journal of Molecular SciencesVol. 26(20)
Kasetsart University (TH), Bangkok University (TH)
Kasetsart University
Openalex Percentile: Top 17%
Antimicrobial Peptides and Activities
1.18
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