ArticleBioinformatics (Oxford, England)2015
Distinct profiling of antimicrobial peptide families.
Article in Bioinformatics (Oxford, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 37 citations in OpenAlex.
- Mapping of the Lipid-Binding Regions of the Antifungal Protein NFAP2 by Exploiting Model Membranes.Journal of chemical information and modeling · 2024Article
- A novel family of defensin-like peptides from Hermetia illucens with antibacterial properties.BMC microbiology · 2024Article
- Short-Chained Linear Scorpion Peptides: A Pool for Novel Antimicrobials.Antibiotics (Basel, Switzerland) · 2024Review
- Chalkiness and premature controlled by energy homeostasis in OsNAC02 Ko-mutant during vegetative endosperm development.BMC plant biology · 2024Article
- Interplay between membrane active host defense peptides and heme modulates their assemblies and in vitro activity.Scientific reports · 2021Article
- Using an Ensemble to Identify and Classify Macroalgae Antimicrobial Peptides.Interdisciplinary sciences, computational life sciences · 2021Article
- Amino Acid Reduction Can Help to Improve the Identification of Antimicrobial Peptides and Their Functional Activities.Frontiers in genetics · 2021Article
- A New Family of Diverse Skin Peptides from the Microhylid Frog GenusMolecules (Basel, Switzerland) · 2020Article
- De Novo Design and In Vitro Testing of Antimicrobial Peptides against Gram-Negative Bacteria.Pharmaceuticals (Basel, Switzerland) · 2019Article
- TELS: A Novel Computational Framework for Identifying Motif Signatures of Transcribed Enhancers.Genomics, proteomics & bioinformatics · 2018Article
- The lipid mediator lysophosphatidic acid induces folding of disordered peptides with basic amphipathic character into rare conformations.Scientific reports · 2018Article
- Sarconesin:Frontiers in microbiology · 2018Article
- Discriminative identification of transcriptional responses of promoters and enhancers after stimulus.Nucleic acids research · 2017Article
- Imbalanced multi-label learning for identifying antimicrobial peptides and their functional types.Bioinformatics (Oxford, England) · 2016Article
- Leveraging family-specific signatures for AMP discovery and high-throughput annotation.Scientific reports · 2016Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationThe increased prevalence of multi-drug resistant (MDR) pathogens heightens the need to design new antimicrobial agents. Antimicrobial peptides (AMPs) exhibit broad-spectrum potent activity against MDR pathogens and kills rapidly, thus giving rise to AMPs being recognized as a potential substitute for conventional antibiotics. Designing new AMPs using current in-silico approaches is, however, challenging due to the absence of suitable models, large number of design parameters, testing cycles, production time and cost. To date, AMPs have merely been categorized into families according to their primary sequences, structures and functions. The ability to computationally determine the properties that discriminate AMP families from each other could help in exploring the key characteristics of these families and facilitate the in-silico design of synthetic AMPs.
resultsHere we studied 14 AMP families and sub-families. We selected a specific description of AMP amino acid sequence and identified compositional and physicochemical properties of amino acids that accurately distinguish each AMP family from all other AMPs with an average sensitivity, specificity and precision of 92.88%, 99.86% and 95.96%, respectively. Many of our identified discriminative properties have been shown to be compositional or functional characteristics of the corresponding AMP family in literature. We suggest that these properties could serve as guides for in-silico methods in design of novel synthetic AMPs. The methodology we developed is generic and has a potential to be applied for characterization of any protein family.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.