Characterization of Selective Antibacterial Peptides by Polarity Index

International Journal of Peptides ◽

10.1155/2012/585027 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

C. Polanco ◽

J. L. Samaniego ◽

T. Buhse ◽

F. G. Mosqueira ◽

A. Negron-Mendoza ◽

...

Keyword(s):

Pathogenic Bacteria ◽

Antibacterial Peptide ◽

Computational Method ◽

Antibacterial Peptides ◽

Double Blind ◽

Blind Test ◽

Bacterial Membranes ◽

Polarity Index ◽

Research Activities ◽

Peptide Database

In the recent decades, antibacterial peptides have occupied a strategic position for pharmaceutical drug applications and became subject of intense research activities since they are used to strengthen the immune system of all living organisms by protecting them from pathogenic bacteria. This work proposes a simple and easy statistical/computational method through a peptide polarity index measure by which an antibacterial peptide subgroup can be efficiently identified, that is, characterized by a high toxicity to bacterial membranes but presents a low toxicity to mammal cells. These peptides also have the feature not to adopt to an alpha-helicoidal structure in aqueous solution. The double-blind test carried out to the whole Antimicrobial Peptide Database (November 2011) showed an accuracy of 90% applying the polarity index method for the identification of such antibacterial peptide groups.

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Non-Lytic Antibacterial Peptides That Translocate Through Bacterial Membranes to Act on Intracellular Targets

International Journal of Molecular Sciences ◽

10.3390/ijms20194877 ◽

2019 ◽

Vol 20 (19) ◽

pp. 4877 ◽

Cited By ~ 11

Author(s):

Marlon H. Cardoso ◽

Beatriz T. Meneguetti ◽

Bruna O. Costa ◽

Danieli F. Buccini ◽

Karen G. N. Oshiro ◽

...

Keyword(s):

Cell Wall ◽

Protein Synthesis ◽

Pathogenic Bacteria ◽

Biological Properties ◽

Antibacterial Peptides ◽

Bacterial Cells ◽

Bacterial Membranes ◽

Intracellular Targets

The advent of multidrug resistance among pathogenic bacteria has attracted great attention worldwide. As a response to this growing challenge, diverse studies have focused on the development of novel anti-infective therapies, including antimicrobial peptides (AMPs). The biological properties of this class of antimicrobials have been thoroughly investigated, and membranolytic activities are the most reported mechanisms by which AMPs kill bacteria. Nevertheless, an increasing number of works have pointed to a different direction, in which AMPs are seen to be capable of displaying non-lytic modes of action by internalizing bacterial cells. In this context, this review focused on the description of the in vitro and in vivo antibacterial and antibiofilm activities of non-lytic AMPs, including indolicidin, buforin II PR-39, bactenecins, apidaecin, and drosocin, also shedding light on how AMPs interact with and further translocate through bacterial membranes to act on intracellular targets, including DNA, RNA, cell wall and protein synthesis.

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Detection of selective antibacterial peptides by the Polarity Profile method.

Acta Biochimica Polonica ◽

10.18388/abp.2013_1969 ◽

2013 ◽

Vol 60 (2) ◽

Cited By ~ 1

Author(s):

Carlos Polanco ◽

Thomas Buhse ◽

José Lino Samaniego ◽

Jorge Alberto Castañón-González

Keyword(s):

Antimicrobial Peptides ◽

Mammalian Cells ◽

False Negative ◽

Antibacterial Peptides ◽

Index Method ◽

Profile Method ◽

Bacterial Membranes ◽

Polarity Index ◽

Polarity Profile ◽

Almost All

Antimicrobial peptides occupy a prominent place in the production of pharmaceuticals, because of their effective contribution to the protection of the immune system against almost all types of pathogens. These peptides are thoroughly studied by computational methods designed to shed light on their main functions. In this paper, we propose a computational approach, named the Polarity Profile method that represents an improvement to the former Polarity Index method. The Polarity Profile method is very effective in detecting the subgroup of antibacterial peptides called selective cationic amphipathic antibacterial peptides (SCAAP) that show high toxicity towards bacterial membranes and exhibit almost zero toxicity towards mammalian cells. Our study was restricted to the peptides listed in the antimicrobial peptides database (APD2) of December 19, 2012. Performance of the Polarity Profile method is demonstrated through a comparison to the former Polarity Index method by using the same sets of peptides. The efficiency of the Polarity Profile method exceeds 85% taking into account the false positive and/or false negative peptides.

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Identification of antimicrobial peptides by using eigenvectors

Acta Biochimica Polonica ◽

10.18388/abp.2015_993 ◽

2016 ◽

Vol 63 (3) ◽

Cited By ~ 1

Author(s):

Carlos Polanco

Keyword(s):

Antimicrobial Peptides ◽

Cancer Cells ◽

Potential Application ◽

Mammalian Cells ◽

Computational Method ◽

Antibacterial Peptides ◽

Index Method ◽

Vector Method ◽

Polarity Index ◽

Wide Range

Antibacterial peptides are subject to broad research due to their potential application and the benefit they can provide for a wide range of diseases. In this work, a mathematical-computational method, called the Polarity Vector Method, is introduced that has a high discriminative level (>70%) to identify peptides associated with Gram (-) bacteria, Gram (+) bacteria, cancer cells, fungi, insects, mammalian cells, parasites, and viruses, taken from the Antimicrobial Peptides Database. This supervised method uses only eigenvectors from the incident polar matrix of the group studied. It was verified with a comparative study with another extensively verified method developed previously by our team, the Polarity Index Method. The number of positive hits of both methods was up to 98% in all the tests conducted.

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Detection of selective cationic amphipatic antibacterial peptides by Hidden Markov models.

Acta Biochimica Polonica ◽

10.18388/abp.2009_2529 ◽

2009 ◽

Vol 56 (1) ◽

Cited By ~ 8

Author(s):

Carlos Polanco ◽

Jose L Samaniego

Keyword(s):

Hidden Markov Models ◽

Pathogenic Bacteria ◽

Markov Models ◽

Hidden Markov ◽

Scoring Function ◽

Chemical Properties ◽

Computational Method ◽

Antibacterial Peptides ◽

Cecropin A ◽

Socially Relevant

Antibacterial peptides are researched mainly for the potential benefit they have in a variety of socially relevant diseases, used by the host to protect itself from different types of pathogenic bacteria. We used the mathematical-computational method known as Hidden Markov models (HMMs) in targeting a subset of antibacterial peptides named Selective Cationic Amphipatic Antibacterial Peptides (SCAAPs). The main difference in the implementation of HMMs was focused on the detection of SCAAP using principally five physical-chemical properties for each candidate SCAAPs, instead of using the statistical information about the amino acids which form a peptide. By this method a cluster of antibacterial peptides was detected and as a result the following were found: 9 SCAAPs, 6 synthetic antibacterial peptides that belong to a subregion of Cecropin A and Magainin 2, and 19 peptides from the Cecropin A family. A scoring function was developed using HMMs as its core, uniquely employing information accessible from the databases.

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Optimum dose setting test by a double blind test of TJN-318 cream for dermatomycosis.

Nishi Nihon Hifuka ◽

10.2336/nishinihonhifu.54.962 ◽

1992 ◽

Vol 54 (5) ◽

pp. 962-976 ◽

Cited By ~ 5

Author(s):

HISASHI TAKAHASHI

Keyword(s):

Optimum Dose ◽

Double Blind ◽

Blind Test

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Breast Cancer Detection from a Urine Sample by Dog Sniffing: A Preliminary Study for the Development of a New Screening Device and a Literature Review

Biology ◽

10.3390/biology10060517 ◽

2021 ◽

Vol 10 (6) ◽

pp. 517

Author(s):

Shoko Kure ◽

Shinya Iida ◽

Marina Yamada ◽

Hiroyuki Takei ◽

Naoyuki Yamashita ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Screening ◽

Cancer Patients ◽

Urine Sample ◽

Urine Samples ◽

Breast Cancer Patients ◽

Double Blind ◽

Blind Test ◽

Preliminary Study ◽

Detect Breast Cancer

Background: Breast cancer is a leading cause of cancer death worldwide. Several studies have demonstrated that dogs can sniff and detect cancer in the breath or urine sample of a patient. This study aims to assess whether the urine sample can be used for breast cancer screening by its fingerprints of volatile organic compounds using a single trained sniffer dog. This is a preliminary study for developing the “electronic nose” for cancer screening. Methods: A nine-year-old female Labrador Retriever was trained to identify cancer from urine samples of breast cancer patients. Urine samples from patients histologically diagnosed with primary breast cancer, those with non-breast malignant diseases, and healthy volunteers were obtained, and a double-blind test was performed. Total of 40 patients with breast cancer, 142 patients with non-breast malignant diseases, and 18 healthy volunteers were enrolled, and their urine samples were collected. Results: In 40 times out of 40 runs of a double-blind test, the trained dog could correctly identify urine samples of breast cancer patients. Sensitivity and specificity of this breast cancer detection method using dog sniffing were both 100%. Conclusions: The trained dog in this study could accurately detect breast cancer from urine samples of breast cancer patients. These results indicate the feasibility of a method to detect breast cancer from urine samples using dog sniffing in the diagnosis of breast cancer. Although the methodological standardization is still an issue to be discussed, the current result warrants further study for developing a new breast cancer screening method based on volatile organic compounds in urine samples.

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Effect of symbiotic supplementation on fecal calprotectin levels and lactic acid bacteria, Bifidobacteria, Escherichia coli and Salmonella DNA in patients with cervical cancer

Nutrición Hospitalaria ◽

10.20960/nh.1762 ◽

2018 ◽

Cited By ~ 1

Author(s):

Genaro Gabriel Ortiz ◽

Luis Humberto De Loera Rodríguez ◽

Paloma Rivero Moragrega ◽

Irma Ernestina Velázquez Brizuela ◽

Juan Francisco Santoscoy Gutiérrez ◽

...

Keyword(s):

Cervical Cancer ◽

Adverse Effects ◽

Pathogenic Bacteria ◽

The United States ◽

Fecal Calprotectin ◽

Control Group ◽

Double Blind ◽

Faecal Calprotectin ◽

Bacterial Dna ◽

Polymerase Chain

Background: Patients with cervical cancer (CC) receiving chemotherapy and radiotherapy have several gastrointestinal adverse effects. Objective: To evaluate the effect of dietary symbiotic supplementation on fecal calprotectin, bacterial DNA levels, and gastrointestinal adverse effects in patients with CC. Methods: Clinical, controlled, randomized, double-blind trial. Patients consumed symbiotics or placebo three times a day for 7 weeks. Fecal calprotectin was assessed by Elisa method. DNA from probiotic and pathogenic bacteria were determined by quantitative real-time polymerase chain reaction. Diarrheal evacuations were evaluated with the Bristol scale and nausea and vomiting were measured using the scale of the National Institute of Cancerology of the United States. Results: Fecal calprotectin concentration was lower in the symbiotic group compared to the control group (p <0.001). The concentrations and total proportions of the probiotic and pathogenic bacteria were similar in both groups. Nausea cases significantly diminished in both groups (p <0.001) at the end of the trial. Furthermore, the symbiotic group had a statistically significant decrease in the frequency and intensity of vomiting when compared to the control group (p <0.001). Conclusions: The symbiotic treatment decreases significantly the fecal calprotectin levels and the frequency and intensity of vomiting in patients with CC. KEYWORDS: faecal calprotectin, cervical cancer, symbiotic, qPCR.

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A Randomised, Controlled Trial: Effect of a Multi-Strain Fermented Milk on the Gut Microbiota Recovery after Helicobacter pylori Therapy

Nutrients ◽

10.3390/nu13093171 ◽

2021 ◽

Vol 13 (9) ◽

pp. 3171

Author(s):

Eric Guillemard ◽

Marion Poirel ◽

Florent Schäfer ◽

Laurent Quinquis ◽

Caroline Rossoni ◽

...

Keyword(s):

Helicobacter Pylori ◽

Gut Microbiota ◽

Beta Diversity ◽

Pathogenic Bacteria ◽

Controlled Trial ◽

Eradication Therapy ◽

Fermented Milk ◽

Control Group ◽

Double Blind ◽

Gi Symptoms

Helicobacter pylori (Hp) eradication therapy alters gut microbiota, provoking gastrointestinal (GI) symptoms that could be improved by probiotics. The study aim was to assess the effect in Hp patients of a Test fermented milk containing yogurt and Lacticaseibacillus (L. paracasei CNCM I-1518 and I-3689, L. rhamnosus CNCM I-3690) strains on antibiotic associated diarrhea (AAD) (primary aim), GI-symptoms, gut microbiota, and metabolites. A randomised, double-blind, controlled trial was performed on 136 adults under 14-day Hp treatment, receiving the Test or Control product for 28 days. AAD and GI-symptoms were reported and feces analysed for relative and quantitative gut microbiome composition, short chain fatty acids (SCFA), and calprotectin concentrations, and viability of ingested strains. No effect of Test product was observed on AAD or GI-symptoms. Hp treatment induced a significant alteration in bacterial and fungal composition, a decrease of bacterial count and alpha-diversity, an increase of Candida and calprotectin, and a decrease of SCFA concentrations. Following Hp treatment, in the Test as compared to Control group, intra-subject beta-diversity distance from baseline was lower (padj = 0.02), some Enterobacteriaceae, including Escherichia-Shigella (padj = 0.0082) and Klebsiella (padj = 0.013), were less abundant, and concentrations of major SCFA (p = 0.035) and valerate (p = 0.045) were higher. Viable Lacticaseibacillus strains were detected during product consumption in feces. Results suggest that, in patients under Hp treatment, the consumption of a multi-strain fermented milk can induce a modest but significant faster recovery of the microbiota composition (beta-diversity) and of SCFA production and limit the increase of potentially pathogenic bacteria.

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