Improved methods for classification, prediction, and design of antimicrobial peptides

Research output: Chapter in Book/Report/Conference proceedingChapter

19 Citations (Scopus)

Abstract

Peptides with diverse amino acid sequences, structures, and functions are essential players in biological systems. The construction of well-annotated databases not only facilitates effective information management, search, and mining but also lays the foundation for developing and testing new peptide algorithms and machines. The antimicrobial peptide database (APD) is an original construction in terms of both database design and peptide entries. The host defense antimicrobial peptides (AMPs) registered in the APD cover the five kingdoms (bacteria, protists, fungi, plants, and animals) or three domains of life (bacteria, archaea, and eukaryota). This comprehensive database ( http://aps.unmc.edu/AP ) provides useful information on peptide discovery timeline, nomenclature, classification, glossary, calculation tools, and statistics. The APD enables effective search, prediction, and design of peptides with antibacterial, antiviral, antifungal, antiparasitic, insecticidal, spermicidal, anticancer activities, chemotactic, immune modulation, or antioxidative properties. A universal classification scheme is proposed herein to unify innate immunity peptides from a variety of biological sources. As an improvement, the upgraded APD makes predictions based on the database-defined parameter space and provides a list of the sequences most similar to natural AMPs. In addition, the powerful pipeline design of the database search engine laid a solid basis for designing novel antimicrobials to combat resistant superbugs, viruses, fungi, or parasites. This comprehensive AMP database is a useful tool for both research and education.

Original languageEnglish (US)
Title of host publicationComputational Peptidology
PublisherSpringer New York
Pages43-66
Number of pages24
ISBN (Print)9781493922857, 9781493922840
DOIs
StatePublished - Jan 2 2015

Fingerprint

antimicrobial peptides
taxonomy
Peptides
prediction
Databases
peptides
methodology
Fungi
Bacteria
information management
fungi
bacteria
engines
Archaea
Antiparasitic Agents
Search Engine
Information Management
education
Biological systems
Terminology

Keywords

  • Ab initio design
  • Database filtering tech
  • Database screen
  • Peptide design
  • Peptide prediction
  • Universal peptide classification

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Medicine(all)

Cite this

Improved methods for classification, prediction, and design of antimicrobial peptides. / Wang, Guangshun.

Computational Peptidology. Springer New York, 2015. p. 43-66.

Research output: Chapter in Book/Report/Conference proceedingChapter

Wang, Guangshun. / Improved methods for classification, prediction, and design of antimicrobial peptides. Computational Peptidology. Springer New York, 2015. pp. 43-66
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