Comparison of coarse-grained (MARTINI) and atomistic molecular dynamics simulations of $$\alpha $$ α and $$\beta $$ β toxin nanopores in lipid membranes

Desikan, Rajat; Patra, Swarna M.; Sarthak, Kumar; Maiti, Prabal K.; Ayappa, K. G.

doi:10.1007/s12039-017-1316-0

Cited by 19 publications

(22 citation statements)

References 51 publications

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“…Our atomistic simulations show in detail the interactions resulting in cholesterol specificity. Despite the limitations of the coarse-grained models imposed by the fixed protein geometry (24,35), the coarse-grained simulations capture the cholesterol dependence of PLY membrane docking, a defining feature of the CDC family. Nevertheless, it is possible that cholesterol has additional stabilizing functions (36), as required for pore formation of alpha-toxins (37) or for dimerization of GPCRs (38).…”

Section: Discussionmentioning

confidence: 99%

“…Molecular dynamics (MD) simulations offer a promising alternative to resolve pore formation at the molecular scale. Previous MD simulations of αand β-PFTs (20)(21)(22)(23)(24)(25) were limited to either protein monomers or small oligomers. Simple rate models for the assembly and insertion process have been proposed (26,27), but the role of lipids and the process of pore opening have not been studied in detail.…”

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confidence: 99%

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Membrane Perforation by the Pore-Forming Toxin Pneumolysin

Vögele

Bhaskara

Mulvihill

et al. 2020

Biophysical Journal

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Pneumolysin (PLY), a major virulence factor of Streptococcus pneumoniae, perforates cholesterol-rich lipid membranes. PLY protomers oligomerize as rings on the membrane and then undergo a structural transition that triggers the formation of membrane pores. Structures of PLY rings in prepore and pore conformations define the beginning and end of this transition, but the detailed mechanism of pore formation remains unclear. With atomistic and coarse-grained molecular dynamics simulations, we resolve key steps during PLY pore formation. Our simulations confirm critical PLY membrane-binding sites identified previously by mutagenesis. The transmembrane β-hairpins of the PLY pore conformation are stable only for oligomers, forming a curtainlike membrane-spanning β-sheet. Its hydrophilic inner face draws water into the protein-lipid interface, forcing lipids to recede. For PLY rings, this zone of lipid clearance expands into a cylindrical membrane pore. The lipid plug caught inside the PLY ring can escape by lipid efflux via the lower leaflet. If this path is too slow or blocked, the pore opens by membrane buckling, driven by the line tension acting on the detached rim of the lipid plug. Interestingly, PLY rings are just wide enough for the plug to buckle spontaneously in mammalian membranes. In a survey of electron cryo-microscopy (cryo-EM) and atomic force microscopy images, we identify key intermediates along both the efflux and buckling pathways to pore formation, as seen in the simulations.pore-forming toxin | cholesterol-dependent cytolysin | pneumolysin | membrane pore Significance Pneumolysin, a pore-forming toxin of Streptococcus pneumoniae, assembles into rings on cholesterol-containing membranes of host cells. β-hairpins form a barrel-shaped transmembrane β-sheet that perforates the membrane, leading to cell lysis. In atomistic and coarse-grained molecular dynamics simulations, we resolve how pneumolysin docks to cholesterol-rich bilayers and how membrane pores form. Remarkably, pneumolysin rings are just wide enough that pores form even if lipid efflux is blocked, driven by spontaneous buckling of the lipid plug. In a survey of electron microscopy and atomic force microscopy images, we identify key intermediates along both the lipid-efflux and plug-buckling pathways of pore opening.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Membrane Perforation by the Pore-Forming Toxin Pneumolysin

Vögele

Bhaskara

Mulvihill

et al. 2020

Biophysical Journal

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“…Although, both CG and FA simulations show increased aggregation with increase in salt concentration, larger sized clusters are more frequently observed for the FA simulations in comparison to the CG simulations (Figures and Supporting Information Figure S9). The greater extent of aggregation observed in the case of FA:20 simulation could be due to softer potentials used in CG simulations . Thus, the reduced molecular friction in CG systems might affect the peptide–peptide interactions and result in greater backbone flexibility compared to the FA systems .…”

Section: Discussionmentioning

confidence: 99%

“…The greater extent of aggregation observed in the case of FA:20 simulation could be due to softer potentials used in CG simulations . Thus, the reduced molecular friction in CG systems might affect the peptide–peptide interactions and result in greater backbone flexibility compared to the FA systems . This is especially relevant for a relatively short peptide like uperin 3.5 that does not contain any proline or aromatic amino acid residues that might stabilize backbone orientations.…”

Section: Discussionmentioning

confidence: 99%

Mechanistic insight into the early stages of amyloid formation using an anuran peptide

et al. 2019

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Uperin 3.5 is a short antimicrobial peptide consisting of 17 Amino acids (GVGDL5IRKAV10SVIKN15IV‐NH2) and is naturally obtained from the skin secretion of Uperoleia mjobergii. It is unusual, as it does not aggregate in pure water, but self‐aggregates to form amyloid fibrils in saline buffer. Hence, it can be used as a model peptide to understand the role of salt in the early stages of amyloid fibril formation. We use molecular dynamics simulations and direct experimental evidence from circular dichroism measurements to investigate the effect of NaCl concentration on interpeptide interactions during the early stages of uperin 3.5 aggregation in water. Our simulations show that addition of salt leads to screening of the positive charges on the R7, K8, and K14 residues by chloride counter‐ions, which in turn results in an increase in the net attraction between the predominantly hydrophobic AVSVI segments of the polypeptide. With addition of salt, changes in interpeptide interactions are accompanied by significant conformational transitions from largely random coil structures in the absence of salt, to greater fractions of α‐helical conformations at higher NaCl concentrations, resulting in greater peptide aggregation at higher NaCl concentrations. Analysis of circular dichroism spectra also shows a similar correlation between an increase in α‐helical content and enhanced aggregation with addition of salt. Thus, the aggregation of uperin 3.5 peptides in presence of salt, results from the combined effects of electrostatic screening, enhanced interaction between hydrophobic residues, and the accompanying conformational changes that stabilize aggregate formation.

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“…Detailed system set-up and all-atom simulation protocols for both ClyA and AHL pores in DMPC lipid membranes have been previously described (Desikan, Patra, et al, 2017). Briefly, both pores were inserted into pre-equilibrated 18 nm × 18 nm DMPC membranes, solvated with TIP3P water (Jorgensen et al, 1983), Na + and Cl − ions to a physiologically relevant 0.15 M NaCl, and subjected to 500 ns long unrestrained production runs in the NPT ensemble at 310 K (stochastic rescaling thermostat (Bussi et al, 2007)) and 1 bar (semi-isotropic Parrinello Rahman barostat (Parrinello & Rahman, 1981)).…”

Section: Methodsmentioning

confidence: 99%

AnIn silicoAlgorithm for Identifying Amino Acids that Stabilize Oligomeric Membrane-Toxin Pores through Electrostatic Interactions

Desikan

Maiti

Ayappa

2019

Preprint

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Pore forming toxins (PFTs) are a class of proteins which have specifically evolved to form unregulated pores in target plasma membranes, and represent the single largest class of bacterial virulence factors. With increasingly prevalent antibiotic-resistant bacterial strains, next generation therapies are being developed to target bacterial PFTs rather than the pathogens themselves. However, structure-based design of inhibitors that could block pore formation are hampered by a paucity of structural information about pore intermediates. On similar lines, observations of the inter-subunit interfaces in fully-formed pore complexes to identify druggable residues, whose interactions could potentially be blocked to hamper pore formation or destabilize pore assemblies, are often limited because of the presence of a large number of protein-protein interaction sites across pore inter-subunit interfaces. Narrowing down the list of plausible target residues requires a quantitative assessment of their contributions towards pore stability, which cannot be gleaned from a single, static, crystal or cryo-EM pore structure.We overcome this limitation by developing an in silico screening algorithm that employs fully atomistic molecular dynamics simulations coupled with knowledge-based screening to identify residues engaged in persistent and stabilizing electrostatic interactions across inter-subunit interfaces in membrane-inserted PFT pores. Application of this algorithm to prototypical α-PFT (cytolysin A) and β-PFT (α-hemolysin) pores yielded a small predicted subset of highly interacting residues, blocking of which could destabilize pore complexes as shown in previous mutagenesis experiments for some of these predicted residues. The algorithm also yielded a novel set of residues in both cytolysin A and α-hemolysin pores for which no mutagenesis and stability data exists to the best of our knowledge, and therefore could serve as hitherto un-CONTACT Rajat Desikan, recognised potential targets for PFT inhibitors. The algorithm worked equally well for both α and β-PFT pores, and could thus be potentially applicable to all pores with known structures to generate a database of pore-destabilizing mutations, which could then serve as a starting point for experimental validation and structure-based PFT-inhibitor design. ABBREVIATIONSAHL α-hemolysin ClyA Cytolysin A DMPC 1,2-dimyristoyl-sn-glycero-3-phosphocholine PDB Protein data bank PFT(s) Pore-forming toxin(s) MD Molecular dynamics RSA Relative solvent accessibility RMSD Root mean square deviation SASA solvent accessible surface area

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Comparison of coarse-grained (MARTINI) and atomistic molecular dynamics simulations of $$\alpha $$ α and $$\beta $$ β toxin nanopores in lipid membranes

Cited by 19 publications

References 51 publications

Membrane Perforation by the Pore-Forming Toxin Pneumolysin

Membrane Perforation by the Pore-Forming Toxin Pneumolysin

Mechanistic insight into the early stages of amyloid formation using an anuran peptide

AnIn silicoAlgorithm for Identifying Amino Acids that Stabilize Oligomeric Membrane-Toxin Pores through Electrostatic Interactions

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