De novo design of peptides that form transmembrane barrel pores killing antibiotic resistant bacteria

DEB, Rahul, Ivo KABELKA, Jan PŘIBYL a Robert VÁCHA. De novo design of peptides that form transmembrane barrel pores killing antibiotic resistant bacteria. 2022.

Základní údaje

• Originální název: De novo design of peptides that form transmembrane barrel pores killing antibiotic resistant bacteria
• Autoři: DEB, Rahul, Ivo KABELKA, Jan PŘIBYL a Robert VÁCHA.
• Vydání: 2022.

Další údaje

• Typ výsledku: Konferenční abstrakt
• Utajení: není předmětem státního či obchodního tajemství
• WWW: Link to bioRxiv Link to Single-Molecule Protein Sequencing 3 (SMPS3) conference

Anotace

De novo design of peptides that self-assemble to form transmembrane barrel-like nanopores is challenging due to the complexity of several competing interactions involving peptides, lipids, water, and ions. Optimization of peptide nanopores for specific functions is even more challenging because the generalized design principles are still missing. Here, we develop a computational approach using molecular dynamics simulations for the de novo design of α-helical peptides that self-assemble into stable transmembrane barrel pores with a central nano-sized functional channel, i.e., capable of conducting water, ions, and small molecules across the lipid membranes. We formulate the previously missing design guidelines and report 52 sequence patterns for the pore-forming peptides that can be tuned for specific applications using the identified role of each residue. Atomic force microscopy, fluorescent dye leakage, and cryo-EM experiments confirm that the designed peptides form leaky membrane nanopores in vitro. We fine-tune these pore-forming peptides into potent antimicrobial compounds able to kill even antibiotic-resistant ESKAPE bacteria at micromolar concentrations, while exhibiting low toxicity to human cells. The peptides and their assembled nanopore structures can be similarly customized for other medical and biotechnological applications, including single-molecule sensing and sequencing.