AIMC Topic: Antimicrobial Cationic Peptides

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

Bioorganic & medicinal chemistry Jul 8, 2017
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...
Machine Learning Anti-Infective Agents Animals Humans Drug Design Peptides Antimicrobial Cationic Peptides Computer-Aided Design Models, Molecular
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Unveiling antimicrobial peptide-generating human proteases using PROTEASIX.

Journal of proteomics Feb 27, 2017
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...
Knowledge Bases Protein Precursors Peptide Hydrolases Substrate Specificity Computational Biology Proteome Antimicrobial Cationic Peptides Humans Peptides
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Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou's general PseAAC.

Scientific reports Feb 13, 2017
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...
Databases, Protein Antimicrobial Cationic Peptides Area Under Curve Antiviral Agents Support Vector Machine Chemical Phenomena Antifungal Agents ROC Curve
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Resistance gene identification from Larimichthys crocea with machine learning techniques.

Scientific reports Dec 6, 2016
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. ...
Machine Learning Immunity, Innate Fish Diseases Animals Interferons Antimicrobial Cationic Peptides Histocompatibility Antigens Immunoglobulins Datasets as Topic Fish Proteins Perciformes Disease Resistance Cation Transport Proteins Genome Gene Expression Regulation
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Mapping membrane activity in undiscovered peptide sequence space using machine learning.

Proceedings of the National Academy of Sciences of the United States of America Nov 14, 2016
There are some ∼1,100 known antimicrobial peptides (AMPs), which permeabilize microbial membranes but have diverse sequences. Here, we develop a support vector machine (SVM)-based classifier to investigate ⍺-helical AMPs and the interrelated nature o...
X-Ray Diffraction Antimicrobial Cationic Peptides Amino Acid Sequence Cell Membrane Models, Theoretical Support Vector Machine Anti-Infective Agents Peptides Microbial Sensitivity Tests Machine Learning Anti-Bacterial Agents
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Hybrid Network Model for "Deep Learning" of Chemical Data: Application to Antimicrobial Peptides.

Molecular informatics Mar 10, 2016
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...
Antimicrobial Cationic Peptides Machine Learning Principal Component Analysis Staphylococcus aureus
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Machine learning assisted design of highly active peptides for drug discovery.

PLoS computational biology Apr 7, 2015
The discovery of peptides possessing high biological activity is very challenging due to the enormous diversity for which only a minority have the desired properties. To lower cost and reduce the time to obtain promising peptides, machine learning ap...
Peptides Protein Interaction Mapping Drug Discovery Molecular Sequence Data Structure-Activity Relationship Sequence Analysis, Protein Machine Learning Antimicrobial Cationic Peptides Amino Acid Sequence Pattern Recognition, Automated Bacterial Physiological Phenomena
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iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities.

Briefings in bioinformatics Jul 20, 2023
Antimicrobial peptides (AMPs) are short peptides that play crucial roles in diverse biological processes and have various functional activities against target organisms. Due to the abuse of chemical antibiotics and microbial pathogens' increasing res...
Deep Learning Antimicrobial Cationic Peptides Antimicrobial Peptides Algorithms Anti-Bacterial Agents
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Designing antimicrobial peptides using deep learning and molecular dynamic simulations.

Briefings in bioinformatics Mar 19, 2023
With the emergence of multidrug-resistant bacteria, antimicrobial peptides (AMPs) offer promising options for replacing traditional antibiotics to treat bacterial infections, but discovering and designing AMPs using traditional methods is a time-cons...
Molecular Dynamics Simulation Gram-Negative Bacteria Gram-Positive Bacteria Deep Learning Antimicrobial Cationic Peptides Anti-Bacterial Agents Antimicrobial Peptides
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Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction.

Briefings in bioinformatics Jul 18, 2022
The evolution of drug-resistant pathogenic microbial species is a major global health concern. Naturally occurring, antimicrobial peptides (AMPs) are considered promising candidates to address antibiotic resistance problems. A variety of computationa...
Machine Learning Algorithms Databases, Factual Antimicrobial Cationic Peptides
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