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A large-scale structural classification of antimicrobial peptides.

Hao-Ting LeeChen-Che LeeJe-Ruei YangJim Z C LaiKuan Y Chang
Published in: BioMed research international (2015)
Antimicrobial peptides (AMPs) are potent drug candidates against microbial organisms such as bacteria, fungi, parasites, and viruses. AMPs have abundant sequences and structures, two fundamental resources for bioinformatics researches, but analyses on how they associate with each other are either nonexistent or limited to partial classification and data. We thus present A Database of Anti-Microbial peptides (ADAM), which contains 7,007 unique sequences and 759 structures, to systematically establish comprehensive associations between AMP sequences and structures through structural folds and to provide an easy access to view their relationships. 30 distinct AMP structural fold clusters with more than one structure are detected and about a thousand AMPs are associated with at least one structural fold cluster. According to ADAM, AMP structural folds are limited-AMPs only cover about 3% of the overall protein fold space.
Keyphrases
  • protein kinase
  • machine learning
  • microbial community
  • emergency department
  • electronic health record
  • mass spectrometry
  • adverse drug
  • big data
  • protein protein
  • small molecule
  • artificial intelligence
  • drug induced