Computational studies of protegrin antimicrobial peptides: A review

Dan S. Bolintineanu, Yiannis Kaznessis

    Research output: Contribution to journalReview articlepeer-review

    66 Scopus citations


    Antimicrobial peptides (AMPs) are small, naturally occurring peptides that exhibit strong antibacterial properties generally believed to be a result of selective bacterial membrane disruption. As a result, there has been significant interest in the development of therapeutic antibiotics based on AMPs; however, the poor understanding of the fundamental mechanism of action of these peptides has largely hampered such efforts. We present a summary of computational and theoretical investigations of protegrin, a particularly potent peptide that is both an excellent model for the mechanism of action of AMPs and a promising therapeutic candidate. Experimental investigations have shed light on many of the key steps in the action of protegrin: protegrin monomers are known to dimerize in various lipid environments; protegrin peptides interact strongly with lipid bilayer membranes, particularly anionic lipids; protegrins have been shown to form pores in lipid bilayers, which results in uncontrolled ion transport and may be a key factor in bacterial death. In this work, we present a comprehensive review of the computational and theoretical studies that have complemented and extended the information obtained from experimental work with protegrins, as well as a brief survey of the experimental biophysical studies that are most pertinent to such computational work. We show that a consistent, mechanistic description of the bactericidal mechanism of action of protegrins is emerging, and briefly outline areas where the current understanding is deficient. We hope that the research reviewed herein offers compelling evidence of the benefits of computational investigations of protegrins and other AMPs, as well as providing a useful guide to future work in this area.

    Original languageEnglish (US)
    Pages (from-to)188-201
    Number of pages14
    Issue number1
    StatePublished - Jan 2011

    Bibliographical note

    Funding Information:
    This work was supported by a grant from NIH ( GM 070989 ). Computational support from the Minnesota Supercomputing Institute (MSI) is gratefully acknowledged. This work was also partially supported by National Computational Science Alliance under TG-MCA04N033 and utilized the TeraGrid Cluster.


    • Antimicrobial peptides
    • Molecular dynamics
    • Protegrin


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