Antimicrobial activity and structure of a consensus human β‐defensin and its comparison to a novel putative hBD10

Rodríguez, A.; Pedersen, Marie Østergaard; Villegas, Elba; Rivas-Santiago, Bruno; Villegas‐Moreno, Jessica; Amero, Carlos; Norton, Raymond S.; Corzo, Gerardo

doi:10.1002/prot.25785

Cited by 12 publications

(7 citation statements)

References 76 publications

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“…However, DFEB118 treatment resulted in significant down-regulation of the two critical inflammatory cytokines. The result is also consistent with previous studies on different animal species [14,50].…”

Section: Discussionsupporting

confidence: 94%

Expression and functional characterization of a novel antimicrobial peptide: human beta-defensin118

Xie

Chen

et al. 2020

Preprint

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Background: β-defensin 118 (DEFB118 ) is a novel host defence peptide (HDP) identified in human. To evaluate its potentials for future utilization, the DEFB118 gene was expressed in Escherichia coli ( E. coli ) and the recombinant protein was fully characterized. Methods: The DEFB118 protein was obtained by heterologous expression using E. coli Rosetta (DE3). Antibacterical activity of DEFB118 were determined by using various bacterial strains. IPEC-J cells challenged by E. coli K88 were used to determine its influences on inflammatory responses. Results: The E. coli transformants yielded more than 250 mg/mL D EFB118 protein after 4 h induction by 1.0 mM IPTG. The DEFB118 was estimated by SDS-PAGE to be 30 kDa, and MALDI-TOF analysis verified it is a human β-defensin 118. Importantly, the DEFB118 showed antimicrobial activities against both Gram-negative bacteria ( E. coli K88 and E. coli DH5α) and Gram-positive bacteria ( S. aureus and B. subtilis ), with a minimum inhibitory concentration (MIC) of 4 μg/mL. Hemolytic assays showed that DEFB118 had no detrimental impact on cell viability. Additionally, DEFB118 was found to elevate the viability of IPEC-J2 cells upon E. coli K88 challenge. Moreover, DEFB118 significantly decreased cell apoptosis in the late apoptosis phase and down-regulated the expression of inflammatory cytokines such as the IL-1β and TNF-a in the IPEC-J2 cells exposure to E. coli K88. Conclusions: These results suggested a novel function of the mammalian defensins, and the anti-bacterial and anti-inflammatory properties of DEFB118 may allow it a potential substitute for conventionally used antibiotics or drugs.

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Section: Discussionsupporting

confidence: 94%

Expression and functional characterization of a novel antimicrobial peptide: human beta-defensin118

Xie

Chen

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…However, DFEB118 treatment resulted in significant downregulation of the two critical inflammatory cytokines. The result is also consistent with previous studies on different animal species [ 14 , 50 ].…”

Section: Discussionsupporting

confidence: 93%

Expression and Functional Characterization of a Novel Antimicrobial Peptide: Human Beta-Defensin 118

Lin

Xie

Chen

et al. 2020

BioMed Research International

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Purpose. β-Defensin 118 (DEFB118) is a novel host defense peptide (HDP) identified in humans. To evaluate its potentials for future utilization, the DEFB118 gene was expressed in Escherichia coli (E. coli) and the recombinant protein was fully characterized. Methods. The DEFB118 protein was obtained by heterologous expression using E. coli Rosetta (DE3). Antibacterial activity of DEFB118 was determined by using various bacterial strains. IPEC-J cells challenged by E. coli K88 were used to determine its influences on inflammatory responses. Results. The E. coli transformants yielded more than 250 μg/mL DEFB118 protein after 4 h induction by 1.0 mM IPTG. The DEFB118 was estimated by SDS-PAGE to be 30 kDa, and MALDI-TOF analysis verified that it is a human β-defensin 118. Importantly, the DEFB118 showed antimicrobial activities against both Gram-negative bacteria (E. coli K88 and E. coli DH5α) and Gram-positive bacteria (S. aureus and B. subtilis), with a minimum inhibitory concentration (MIC) of 4 μg/mL. Hemolytic assays showed that DEFB118 had no detrimental impact on cell viability. Additionally, DEFB118 was found to elevate the viability of IPEC-J2 cells upon E. coli K88 challenge. Moreover, DEFB118 significantly decreased cell apoptosis in the late apoptosis phase and downregulated the expression of inflammatory cytokines such as IL-1β and TNF-α in IPEC-J2 cell exposure to E. coli K88. Conclusions. These results suggested a novel function of the mammalian defensins, and the antibacterial and anti-inflammatory properties of DEFB118 may allow it as a potential substitute for conventionally used antibiotics or drugs.

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“…We also study the sequence alignment of the twenty most active peptides within our dataset shows a consensus sequence ("GCRANKGACRAKKCKSHGGRGGKCF" -Figure S4 in the Supplementary material), having a high net charge of +8.25 [36][37][38] and 32% hydrophobic ratio. We remark on the presence of four cysteines (Cys -C) in the peptide sequence, which contributes to the stability of the tertiary structure 39 . The presence of four cysteines is also observed in anti-MRSA peptidic sequences, for example in peptides AP03010, AP03022, and AP03311 in Figure 4 (vide infra).…”

Section: Overview Of Anti-mrsa Peptides Sequence Alignmentsmentioning

confidence: 99%

Towards exploring the activity landscape of peptide datasets using MAP4 fingerprint

López-López

Robles

Plisson³

et al. 2023

Preprint

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Peptides are a re-emerged strategy to fight a plethora of diseases and their utility has been expanded to new areas. Now sequence-based peptide design opens up new possibilities to develop peptidic molecular entities. However, its methodological limitations (e.g., its inefficiency in designing large peptides and that do not allow the analysis of post-traductional modification) limit their applicability domain. In contrast, ligand-based molecular design approaches have demonstrated their extensive applicability domain, although the peptide design-based in this method continues been not exploited. The main limitation has been the complex molecular structure of peptides, which has not been studied using classical fingerprints tuned for small organic compounds. Towards this end, MAP4 is a recently developed universal fingerprint that allows quantifying the sequence/structure diversity of natural products or peptides. As part of the peptide design, there is a current trend to develop predictive models which are founded on the available structure-activity data available. Before developing such models, it is essential to characterize in detail the structure-activity relationship and identify if any activity cliffs: subtle structural modifications that have a large and unexpected effect on the biological activity. In this study, we map the structure-activity landscape of an exemplary dataset with 165 peptides (anti-methicillin-resistant Staphylococcus aureus peptides) using a similarity metric based on MAP4 fingerprint. Specifically, we characterized the activity landscape of this data set, and we identified key amino acids (AAs) and structural motifs that play a key role in the activity of the anti-methicillin-resistant Staphylococcus aureus peptides. To the best of our knowledge, this is the first chemoinformatics approach to systematically explore the activity landscape of peptides emphasizing the quantification of the structural similarity. The approach is general and can be extended to analyze the presence of activity cliffs in any set of peptides. Identifying activity cliffs has practical implications during the development of predictive models.

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Antimicrobial activity and structure of a consensus human β‐defensin and its comparison to a novel putative hBD10

Cited by 12 publications

References 76 publications

Expression and functional characterization of a novel antimicrobial peptide: human beta-defensin118

Expression and functional characterization of a novel antimicrobial peptide: human beta-defensin118

Expression and Functional Characterization of a Novel Antimicrobial Peptide: Human Beta-Defensin 118

Towards exploring the activity landscape of peptide datasets using MAP4 fingerprint

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