Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Antimicrobial Proteins

Antimicrobial Proteins

Antimicrobial proteins are important components of the immune system. They aid the body in combating pathogens by either killing them directly or hindering their replication processes. Four main types of antimicrobial substances are interferons, the complement system, iron-binding proteins, and antimicrobial proteins.
Interferons
Interferons (IFNs) are proteins produced by lymphocytes, macrophages, and fibroblasts infected with viruses. While IFNs cannot prevent viruses from entering and...

Antibiotic Selection

Antibiotic Selection

Automated Microbial Diagnostics

Automated Microbial Diagnostics

Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Genomic Regions Associated with Drought Tolerance and Other Traits in Lentils (<i>Lens</i> sp.).

Plants (Basel, Switzerland)·2026

Same author

Bioinformatics Insights on the Physicochemical Properties of SCN5A Mutant Proteins Associated with the Brugada Syndrome.

Current medicinal chemistry·2022

Same author

Bioinformatics-based Characterization of the Sequence Variability of Zika Virus Polyprotein and Envelope Protein (E).

Evolutionary bioinformatics online·2022

Same author

Cost-effectiveness analysis of apixaban versus vitamin K antagonists for antithrombotic therapy in patients with atrial fibrillation after acute coronary syndrome or percutaneous coronary intervention in Spain.

PloS one·2021

Same author

The MLO1 powdery mildew susceptibility gene in Lathyrus species: The power of high-density linkage maps in comparative mapping and synteny analysis.

The plant genome·2021

Same author

Standardizing Health Outcomes for Lung Cancer. Adaptation of the International Consortium for Health Outcomes Measurement Set to the Spanish Setting.

Frontiers in oncology·2020

Search research articles

Related Experiment Video

Updated: Mar 19, 2026

Production and Visualization of Bacterial Spheroplasts and Protoplasts to Characterize Antimicrobial Peptide Localization

Production and Visualization of Bacterial Spheroplasts and Protoplasts to Characterize Antimicrobial Peptide Localization

Published on: August 11, 2018

Identification of antimicrobial peptides by using eigenvectors.

Carlos Polanco¹

¹Department of Mathematics, Faculty of Sciences, Universidad Nacional Autónoma de México, México.

Acta Biochimica Polonica

|June 24, 2016

Summary

A new Polarity Vector Method accurately identifies antimicrobial peptides targeting bacteria, fungi, and viruses. This computational approach shows high discrimination (>70%) and was validated against a previous method, achieving up to 98% positive hits.

More Related Videos

Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids

Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids

Published on: May 4, 2018

Identification of Antibacterial Immunity Proteins in Escherichia coli using MALDI-TOF-TOF-MS/MS and Top-Down Proteomic Analysis

Identification of Antibacterial Immunity Proteins in Escherichia coli using MALDI-TOF-TOF-MS/MS and Top-Down Proteomic Analysis

Published on: May 23, 2021

Related Experiment Videos

Last Updated: Mar 19, 2026

Production and Visualization of Bacterial Spheroplasts and Protoplasts to Characterize Antimicrobial Peptide Localization

Production and Visualization of Bacterial Spheroplasts and Protoplasts to Characterize Antimicrobial Peptide Localization

Published on: August 11, 2018

Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids

Antimicrobial Peptides Produced by Selective Pressure Incorporation of Non-canonical Amino Acids

Published on: May 4, 2018

Identification of Antibacterial Immunity Proteins in Escherichia coli using MALDI-TOF-TOF-MS/MS and Top-Down Proteomic Analysis

Identification of Antibacterial Immunity Proteins in Escherichia coli using MALDI-TOF-TOF-MS/MS and Top-Down Proteomic Analysis

Published on: May 23, 2021

Area of Science:

Biochemistry
Computational Biology
Bioinformatics

Background:

Antimicrobial peptides (AMPs) are crucial in treating diseases.
Research into AMPs is expanding due to their broad applicability.
Identifying specific AMPs is essential for targeted therapies.

Purpose of the Study:

Introduce a novel mathematical-computational method, the Polarity Vector Method.
Evaluate the discriminative power of the Polarity Vector Method for AMP identification.
Compare the Polarity Vector Method with the established Polarity Index Method.

Main Methods:

Utilized the Antimicrobial Peptides Database for peptide data.
Developed a supervised learning approach based on eigenvectors from the incident polar matrix.
Performed comparative analysis against the Polarity Index Method.

Main Results:

The Polarity Vector Method achieved a high discrimination level (>70%) in identifying peptides.
The method demonstrated effectiveness across diverse targets: Gram-negative bacteria, Gram-positive bacteria, cancer cells, fungi, insects, mammalian cells, parasites, and viruses.
Both methods achieved up to 98% positive hits in validation tests.

Conclusions:

The Polarity Vector Method is a robust computational tool for AMP identification.
This method offers significant potential for developing targeted antimicrobial and therapeutic agents.
The high accuracy and validation confirm the method's reliability in AMP research.