Simulations of Membrane-Disrupting Peptides II: AMP Piscidin 1 Favors Surface Defects over Pores

Abstract

Antimicrobial peptides (AMPs) that disrupt bacterial membranes are promising therapeutics against the growing number of antibiotic-resistant bacteria. The mechanism of membrane disruption by the AMP piscidin 1 was examined with multimicrosecond all-atom molecular dynamics simulations and solid-state NMR spectroscopy. The primary simulation was initialized with 20 peptides in four barrel-stave pores in a fully hydrated 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine/1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol bilayer. The four pores relaxed to toroidal by 200 ns, only one porelike structure containing two transmembrane helices remained at 26 ms, and none of the 18 peptides released to the surface reinserted to form pores. The simulation was repeated at 413 K with an applied electric field and all peptides were surface-bound by 200 ns. Trajectories of surface-bound piscidin with and without applied fields at 313 and 413 K and totaling 6 ms show transient distortions of the bilayer/water interface (consistent with 31 P NMR), but no insertion to transmembrane or pore states.15 N chemical shifts confirm a fully surface-bound conformation. Taken together, the simulation and experimental results imply that transient defects rather than stable pores are responsible for membrane disruption by piscidin 1, and likely other AMPs.

Influence of membrane composition on the binding and folding of a membrane lytic peptide from the non-enveloped flock house virus

“…51,52 However, for piscidin 1 a pore structure was not stable as the peptides preferred S-state orientations. 53 Transient membrane defects were observed for piscidin 1, which were characterized by the deep insertion of the C-terminal region of the peptide. 53 Based upon the size and charge similarity of γ 1 to piscidin 1, and that we also observe deep C-terminal insertion (Fig.…”

“…53 Transient membrane defects were observed for piscidin 1, which were characterized by the deep insertion of the C-terminal region of the peptide. 53 Based upon the size and charge similarity of γ 1 to piscidin 1, and that we also observe deep C-terminal insertion (Fig. 6G), we would predict these peptides to share a similar mechanism of action, but further studies will be required to test this prediction.…”

A brief appraisal of computational modeling of antimicrobial peptides’ activity

“…Starting from an aqueous phase, the study was able to simulate, for the first time, the entire event of aggregation and translocation of multiple copies of magainin H2 and subsequent formation of a disordered toroidal pore (see Figure a). Following up this work, there have been numerous computer simulations, majorly focused upon a number of AMPs, namely Melittin (Sengupta, Leontiadou, Mark, & Marrink, ), Alamethicin (Perrin & Pastor, ), and Piscidine (Perrin, Fu, Cotten, & Pastor, ), which have tried to explore the antimicrobial activity of various AMPs at atomistic details. In a recent computer simulation, Ulmschneider ()) has shown computational evidence of direct translocation of highly charged AMP PGLa without the formation of any transmembrane pore.…”

“…The major cause has been that despite improvement in computer hardware, the timescale of membrane disruption and especially pore formation are estimated to be orders of magnitude of longer than the simulation timescale, currently accessed in simulations. Most of the simulation works up till now have thereafter settled by manually modeling artificial pore and exploring the stability of the pore over the simulation timescale (Perrin et al, ; Perrin & Pastor, ), instead of waiting for the pore to form in a spontaneous fashion (see Figure b). Even though the simulation length employed for exploring the stability of pore formation has recently gone up to 10–15 μs (Perrin et al, ; Perrin & Pastor, ), a major issue with these simulations has been that the so‐called pore stability depends strongly upon the simulation length and more importantly on the starting condition.…”

“…A second issue with the current approach has been that the membrane models adopted in the computer simulation approaches are overly simplified (Pandit & Klauda, ), when compared with the diverse composition of biological membranes. The simulations mostly employ single‐component or at the most two‐component (Baul et al, ; Perrin & Pastor, ; Perrin et al, ) lipid bilayers, which are remote mimics of any realistic biological membranes. Finally, the parameters of lipids (so‐called lipid force fields) employed in the molecular dynamics simulations and especially its balance with protein force fields is often considered one of the gray areas of computer simulations in need of substantial improvements.…”