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Antimicrobial Cationic Peptides

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Antibacterial activity and its mechanisms of a recombinant Funme peptide against Cronobacter sakazakii in powdered infant formula.

Food research international (Ottawa, Ont.)
Cronobacter sakazakii (Cs) is a typical foodborne bacterium that infect powdered infant formula (PIF) worldwide. In this study, a recombinant antimicrobial peptide, branded as Funme peptide (FP)was applied to protect PIF from Cs contamination. The re...

Antimicrobial Characteristics of Lactic Acid Bacteria Isolated from Homemade Fermented Foods.

BioMed research international
. Lactic acid bacteria (LAB) were isolated from fermented foods, such as glutinous rice dough, corn noodle, chili sauce, potherb mustard pickles, and stinky tofu, in northeast China. LAB strains with antimicrobial activities were screened, and seven ...

Hybrid Network Model for "Deep Learning" of Chemical Data: Application to Antimicrobial Peptides.

Molecular informatics
We present a "deep" network architecture for chemical data analysis and classification together with a prospective proof-of-concept application. The model features a self-organizing map (SOM) as the input layer of a feedforward neural network. The SO...

Resistance gene identification from Larimichthys crocea with machine learning techniques.

Scientific reports
The research on resistance genes (R-gene) plays a vital role in bioinformatics as it has the capability of coping with adverse changes in the external environment, which can form the corresponding resistance protein by transcription and translation. ...

Unveiling antimicrobial peptide-generating human proteases using PROTEASIX.

Journal of proteomics
UNLABELLED: Extracting information from peptidomics data is a major current challenge, as endogenous peptides can result from the activity of multiple enzymes. Proteolytic enzymes can display overlapping or complementary specificity. The activity spe...

Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou's general PseAAC.

Scientific reports
Antimicrobial peptides (AMPs) are important components of the innate immune system that have been found to be effective against disease causing pathogens. Identification of AMPs through wet-lab experiment is expensive. Therefore, development of effic...

Improving Recognition of Antimicrobial Peptides and Target Selectivity through Machine Learning and Genetic Programming.

IEEE/ACM transactions on computational biology and bioinformatics
Growing bacterial resistance to antibiotics is spurring research on utilizing naturally-occurring antimicrobial peptides (AMPs) as templates for novel drug design. While experimentalists mainly focus on systematic point mutations to measure the effec...

Machine learning-enabled discovery and design of membrane-active peptides.

Bioorganic & medicinal chemistry
Antimicrobial peptides are a class of membrane-active peptides that form a critical component of innate host immunity and possess a diversity of sequence and structure. Machine learning approaches have been profitably employed to efficiently screen s...

Predictive Model of Linear Antimicrobial Peptides Active against Gram-Negative Bacteria.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have been identified as a potential new class of anti-infectives for drug development. There are a lot of computational methods that try to predict AMPs. Most of them can only predict if a peptide will show any antimicro...

Recent Progress in Machine Learning-based Prediction of Peptide Activity for Drug Discovery.

Current topics in medicinal chemistry
Over the past decades, peptide as a therapeutic candidate has received increasing attention in drug discovery, especially for antimicrobial peptides (AMPs), anticancer peptides (ACPs) and antiinflammatory peptides (AIPs). It is considered that the pe...