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Probing Protein Sequences as Sources for Encrypted Antimicrobial Peptides

Author

Listed:
  • Guilherme D Brand
  • Mariana T Q Magalhães
  • Maria L P Tinoco
  • Francisco J L Aragão
  • Jacques Nicoli
  • Sharon M Kelly
  • Alan Cooper
  • Carlos Bloch Jr

Abstract

Starting from the premise that a wealth of potentially biologically active peptides may lurk within proteins, we describe here a methodology to identify putative antimicrobial peptides encrypted in protein sequences. Candidate peptides were identified using a new screening procedure based on physicochemical criteria to reveal matching peptides within protein databases. Fifteen such peptides, along with a range of natural antimicrobial peptides, were examined using DSC and CD to characterize their interaction with phospholipid membranes. Principal component analysis of DSC data shows that the investigated peptides group according to their effects on the main phase transition of phospholipid vesicles, and that these effects correlate both to antimicrobial activity and to the changes in peptide secondary structure. Consequently, we have been able to identify novel antimicrobial peptides from larger proteins not hitherto associated with such activity, mimicking endogenous and/or exogenous microorganism enzymatic processing of parent proteins to smaller bioactive molecules. A biotechnological application for this methodology is explored. Soybean (Glycine max) plants, transformed to include a putative antimicrobial protein fragment encoded in its own genome were tested for tolerance against Phakopsora pachyrhizi, the causative agent of the Asian soybean rust. This procedure may represent an inventive alternative to the transgenic technology, since the genetic material to be used belongs to the host organism and not to exogenous sources.

Suggested Citation

  • Guilherme D Brand & Mariana T Q Magalhães & Maria L P Tinoco & Francisco J L Aragão & Jacques Nicoli & Sharon M Kelly & Alan Cooper & Carlos Bloch Jr, 2012. "Probing Protein Sequences as Sources for Encrypted Antimicrobial Peptides," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-14, September.
  • Handle: RePEc:plo:pone00:0045848
    DOI: 10.1371/journal.pone.0045848
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    References listed on IDEAS

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    1. Li, Baibing & Martin, Elaine B. & Morris, A. Julian, 2002. "On principal component analysis in L1," Computational Statistics & Data Analysis, Elsevier, vol. 40(3), pages 471-474, September.
    2. Michael Zasloff, 2002. "Antimicrobial peptides of multicellular organisms," Nature, Nature, vol. 415(6870), pages 389-395, January.
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    1. Paulina Szymczak & Marcin Możejko & Tomasz Grzegorzek & Radosław Jurczak & Marta Bauer & Damian Neubauer & Karol Sikora & Michał Michalski & Jacek Sroka & Piotr Setny & Wojciech Kamysz & Ewa Szczurek, 2023. "Discovering highly potent antimicrobial peptides with deep generative model HydrAMP," Nature Communications, Nature, vol. 14(1), pages 1-23, December.

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