Tuning of a Membrane-Perforating Antimicrobial Peptide to Selectively Target Membranes of Different Lipid Composition.

Antimicrobial peptides Bacterial selectivity Drug-resistant bacteria Leucine-rich peptide Pore formation Protein folding

Journal

The Journal of membrane biology
ISSN: 1432-1424
Titre abrégé: J Membr Biol
Pays: United States
ID NLM: 0211301

Informations de publication

Date de publication:
02 2021
Historique:
received: 15 12 2020
accepted: 21 01 2021
pubmed: 11 2 2021
medline: 5 3 2022
entrez: 10 2 2021
Statut: ppublish

Résumé

The use of designed antimicrobial peptides as drugs has been impeded by the absence of simple sequence-structure-function relationships and design rules. The likely cause is that many of these peptides permeabilize membranes via highly disordered, heterogeneous mechanisms, forming aggregates without well-defined tertiary or secondary structure. We suggest that the combination of high-throughput library screening with atomistic computer simulations can successfully address this challenge by tuning a previously developed general pore-forming peptide into a selective pore-former for different lipid types. A library of 2916 peptides was designed based on the LDKA template. The library peptides were synthesized and screened using a high-throughput orthogonal vesicle leakage assay. Dyes of different sizes were entrapped inside vesicles with varying lipid composition to simultaneously screen for both pore size and affinity for negatively charged and neutral lipid membranes. From this screen, nine different LDKA variants that have unique activity were selected, sequenced, synthesized, and characterized. Despite the minor sequence changes, each of these peptides has unique functional properties, forming either small or large pores and being selective for either neutral or anionic lipid bilayers. Long-scale, unbiased atomistic molecular dynamics (MD) simulations directly reveal that rather than rigid, well-defined pores, these peptides can form a large repertoire of functional dynamic and heterogeneous aggregates, strongly affected by single mutations. Predicting the propensity to aggregate and assemble in a given environment from sequence alone holds the key to functional prediction of membrane permeabilization.

Identifiants

pubmed: 33564914
doi: 10.1007/s00232-021-00174-1
pii: 10.1007/s00232-021-00174-1
doi:

Substances chimiques

Antimicrobial Peptides 0
Lipid Bilayers 0
Peptides 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

75-96

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Auteurs

Charles H Chen (CH)

Department of Chemistry, King's College London, London, UK. chenchar@mit.edu.
Department of Engineering and Materials Science, Johns Hopkins University, Baltimore, MD, USA. chenchar@mit.edu.
Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA. chenchar@mit.edu.
MIT Synthetic Biology Center and Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA. chenchar@mit.edu.

Charles G Starr (CG)

Department of Biochemistry and Molecular Biology, Tulane University School of Medicine, New Orleans, LA, USA.

Shantanu Guha (S)

Department of Biochemistry and Molecular Biology, Tulane University School of Medicine, New Orleans, LA, USA.

William C Wimley (WC)

Department of Biochemistry and Molecular Biology, Tulane University School of Medicine, New Orleans, LA, USA.

Martin B Ulmschneider (MB)

Department of Chemistry, King's College London, London, UK. martin.ulmschneider@kcl.ac.uk.
Department of Engineering and Materials Science, Johns Hopkins University, Baltimore, MD, USA. martin.ulmschneider@kcl.ac.uk.
Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD, USA. martin.ulmschneider@kcl.ac.uk.

Jakob P Ulmschneider (JP)

Institute of Natural Sciences, Shanghai Jiao-Tong University, Shanghai, China. jakob@sjtu.edu.cn.

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