Aparajita Chakraborty1,2,3, Elisey Kobzev1,3,4, Jonathan Chan2,5, Gayan Heruka de Zoysa6, Vijayalekshmi Sarojini6,7, Thomas J Piggot8,9, Jane R Allison1,2,3,10,11. 1. Maurice Wilkins Centre for Molecular Biodiscovery, University of Auckland, Auckland 1010, New Zealand. 2. School of Biological Sciences, University of Auckland, Auckland 1010, New Zealand. 3. Centre for Theoretical Chemistry and Physics, Massey University Auckland, Auckland 0632, New Zealand. 4. School of Computational and Natural Sciences, Massey University Auckland, Auckland 0632, New Zealand. 5. Department of Biochemistry, University of Oxford, South Parks Rd, Oxford OX1 3QU, United Kingdom. 6. School of Chemical Sciences, University of Auckland, Auckland 1010, New Zealand. 7. MacDiarmid Institute for Advanced Materials and Nanotechnology, Victoria University of Wellington, Wellington 6140, New Zealand. 8. School of Chemistry, University of Southampton, Southampton SO17 1BJ, United Kingdom. 9. Chemical Biological and Radiological Sciences, Defence Science and Technology Laboratory, Porton Down, Salisbury, Wiltshire SP4 0JQ, United Kingdom. 10. Biomolecular Interaction Centre, University of Canterbury, Christchurch 8041, New Zealand. 11. Digital Life Institute, University of Auckland, Auckland 1010, New Zealand.
Abstract
Antimicrobial peptides (AMPs) are a potential solution to the increasing threat of antibiotic resistance, but successful design of active but nontoxic AMPs requires understanding their mechanism of action. Molecular dynamics (MD) simulations can provide atomic-level information regarding how AMPs interact with the cell membrane. Here, we have used MD simulations to study two linear analogs of battacin, a naturally occurring cyclic, lipidated, nonribosomal AMP. Like battacin, these analogs are active against Gram-negative multidrug resistant and Gram-positive bacteria, but they are less toxic than battacin. Our simulations show that this activity depends upon a combination of positively charged and hydrophobic moieties. Favorable interactions with negatively charged membrane lipid head groups drive association with the membrane and insertion of hydrophobic residues, and the N-terminal lipid anchors the peptides to the membrane surface. Both effects are required for stable membrane binding.
Antimicrobial peptides (AMPs) are a potential solution to the increasing threat of antibiotic resistance, but successful design of active but nontoxic AMPs requires understanding their mechanism of action. Molecular dynamics (MD) simulations can provide atomic-level information regarding how AMPs interact with the cell membrane. Here, we have used MD simulations to study two linear analogs of battacin, a naturally occurring cyclic, lipidated, nonribosomal AMP. Like battacin, these analogs are active against Gram-negative multidrug resistant and Gram-positive bacteria, but they are less toxic than battacin. Our simulations show that this activity depends upon a combination of positively charged and hydrophobic moieties. Favorable interactions with negatively charged membrane lipid head groups drive association with the membrane and insertion of hydrophobic residues, and the N-terminal lipid anchors the peptides to the membrane surface. Both effects are required for stable membrane binding.
Modern medicine relies
heavily on antibiotics for treating bacterial
infections. However, increasing bacterial resistance against many
antibiotics has become one of the biggest threats to global health
and food security.[1,2] The problem is expected to become
much more serious in the not-too-distant future with the emergence
of increasing numbers of multidrug and extremely drug resistant (MDR
and XDR) bacterial strains.[3] This is driving
a continuous search for new synthetic and natural antibacterial agents,[4,5] one promising source of which is antimicrobial peptides (AMPs).[6−10] The promise of AMPs remains to be fulfilled, however, with only
a few peptides entering clinical trials.[7,11,12] This may be, in part, because their mechanism of
action is difficult to study experimentally at an atomic level,[13] hindering truly rational design of active but
less toxic analogs.[14] Indeed, as yet, no
universal sequence–activity relationship has been discovered,
although it is becoming apparent that this may require consideration
of dynamic structural ensembles rather than static structures.[15−19]AMPs are one of the largest classes of membrane lytic peptides
produced by invertebrates and vertebrates, including microbes themselves.[20] AMPs are part of the cell-mediated immune response
and are synthesized upon induction by pathogens and also by bacteria
themselves in response to competition for food and resources.[20,21] Eukaryotic AMPs, which are genetically encoded and synthesized on
the ribosome, typically consist of 10–50 amino acids and are
classified according to their secondary structure or lack thereof.[21] Bacterial AMPs may be non-ribosomally synthesized
and thus can also include non-proteinogenic amino acids, decreasing
their susceptibility to proteolytic enzymes and be glycosylated; acylated;
halogenated; or hydroxylated, formylated, or lipidated.[21] Non-ribosomally synthesized AMPs can also be
cyclic, increasing their rigidity. The major features shared by all
AMPs are that they are soluble in aqueous environments and can partition
into lipid environments, such as the cell membrane.[9]The generally cationic nature of AMPs along with
the anionic nature
of bacterial membranes results in preferential targeting of AMPs to
bacterial rather than zwitterionic eukaryotic membranes.[21−24] The interaction of AMPs with cell membranes is then facilitated
by their high hydrophobic amino acid content.[21,24,25] Nonribosomal AMPs can also include features,
such as lipids, which are likely to further favor membrane interaction.
The selectivity of AMPs depends upon differences in membrane composition
between different organisms.AMPs generally cause cell death
through membrane disruption and
eventual cell lysis, although there are some instances of AMPs inhibiting
biofilm production or crossing the cell membrane and inhibiting cellular
functions.[21,26−28] Even amongst
membrane-lytic AMPs, however, there are a variety of mechanisms of
action. For ribosomally synthesized AMPs, in particular those that
are α-helical, three major mechanisms of membrane disruption
have emerged: “barrel-stave”, “toroidal-pore”,
and “carpet”.[20,21,27,28] Less is known about the mechanisms
of action of other types of AMPs, however.[24]Battacin is a cyclic, lipidated nonribosomal AMP first isolated
from Paenibacillus tianmuensis.(29) It is composed of both d- and l-amino acids and the unnatural amino acid α,γ-diaminobutyric
acid (Dab) in both its d- and l- forms, which give
it resistance to proteases and thus make it a potential candidate
for therapeutics. It has been found to be active against Gram-negative
MDR bacteria and Gram-positive bacteria in both in vitro and in vivo.[29] Along with high efficacy against MDR
bacterial strains, however, naturally occurring battacin is nephrotoxic
and neurotoxic[29] and thus is not used clinically.To overcome the toxicity of naturally occurring battacin, we previously
designed and synthesized novel structural analogs.[30] Remarkably and in contrast to other AMPs, such as polymyxin,
two of these linear peptides, octapeptide 17 (hereafter octapeptide)
and its derivative pentapeptide 30 (hereafter pentapeptide) (Figure ), were found experimentally
to be active, in terms of both lysing bacteria and dispersing preformed
biofilms, against both model Gram-negative (Escherichia coli) and Gram-positive
(Staphylococcus aureus) bacteria.[30,31] Unlike many AMPs,[26,32,33] the activity of these battacin
analogs does not rely on the presence of a defined secondary structure
when bound to the membrane,[30,34] suggesting that the
mechanism of action might also differ. It is extremely difficult to
experimentally obtain a detailed atomic level insight into their mechanism
of action, however.
Figure 1
Chemical structures of (a) octapeptide 17 (octapeptide)
and (b)
pentapeptide 30 (pentapeptide). The Dab side chains are shown in their
deprotonated state.
Chemical structures of (a) octapeptide 17 (octapeptide)
and (b)
pentapeptide 30 (pentapeptide). The Dab side chains are shown in their
deprotonated state.Molecular dynamics (MD)
simulations can provide time-dependent
information about the structure of AMPs and the nature and energetics
of their interactions. MD simulation of AMP–lipid interactions
has a long history.[35−38] Limitations such as the use of coarse-grained (CG) models[39−44] and simple membranes, particularly those containing only phosphatidylcholinelipids,[16,41−45] which is not representative of bacterial membranes,
can produce results different to those observed with more realistic
models.[15,16,25,39,40,46,47] It has been suggested that the
different results sometimes observed using the Martini CG force field
may be due to a higher energetic cost of pore formation.[48] Almost all simulation studies, however, have
been of AMPs that form stable α-helical or β-hairpin structures
upon binding to and/or insertion into the membrane.[15−17,25,32,44−47,49−59] In general, these AMPs are more likely to act via a pore-forming
mechanism.[58] Less is known, however, about
the mechanism of action of unstructured AMPs such as the linear battacin
analogs.We have, therefore, carried out MD simulations with
atomistic cell
membrane and peptide models to investigate how each of the two linear
battacin analogs, octapeptide and its truncated derivative pentapeptide,
interact with model Gram-negative (E. coli) and Gram-positive (S. aureus) cell
membranes. We find that for both peptides, and in keeping with both
the general mechanism by which AMPs selectively target bacterial cell
membranes[21,24] and residue-specific experimental results
for octapeptide[30] and polymyxins,[60,61] the positively charged Dab residues are the most important for the
initial interaction with and binding to the membrane surface. The
hydrocarbon tail of the N-terminal lipid plays a major role in membrane
permeation and, along with the hydrophobic residues Leu and d-Phe, anchors the peptide to the membrane surface, again in keeping
with experimental results for these peptides.[30] Reducing the positive charge on the peptide by deprotonating the d-Dab and Dab residues generally reduces hydrogen bond formation
and Coulombic interactions with the membrane lipids, which in turn
reduces the structural stability of the peptides and the insertion
of the hydrophobic moieties into the membrane. Stable initial binding
to the membrane surface, which is promoted by positively charged residues,
is therefore crucial for membrane penetration by the hydrophobic moieties
and thus explains the experimentally observed importance of the central
hydrophobic dipeptide unit Leu-d-Phe, its flanking Dab residues,
and the N-terminal lipid of octapeptide, which are recapitulated in
the pentapeptide.[30]
Results and Discussion
Choice
of Model Cell Membranes
To investigate the mechanism
by which these peptides disrupt the cell membrane of both Gram-positive
and Gram-negative bacteria and to search for any differences in the
mechanism between the two types of bacteria, we simulated a single
copy of each peptide with each of two cell membrane models, a S. aureus membrane and an E. coli inner membrane (IM). These two species were chosen both to represent
pathogenic Gram-positive and Gram-negative bacteria, respectively,
and for comparison with the experimental tests of peptide efficacy,
which used the same species.[30]We
focused on the E. coli IM because it
is both more informative with regard to the mechanism of action of
these peptides and because it is more computationally efficient. Naturally
occurring battacin is known to permeate the outer membrane (OM) of
Gram-negative bacteria; it is its interaction with the IM that leads
to the death of the microorganism.[29] The
interaction with the IM is therefore most relevant to understanding
the mechanism of action.
Mechanism of Interaction with Model Cell
Membranes
For each peptide–membrane system, we first
carried out five
independent simulations of 50 ns to monitor the initial approach to
and interaction with the membrane. Three of each set of five simulations
were chosen at random and extended for a further 450 ns to monitor
the long-term behavior and initiation of penetration. Only the data
pertaining to these extended simulations are presented here.
Interaction
with the S. aureus Membrane
Both peptides approach the S. aureus membrane within 25 ns of simulation in all five 50 ns simulations.
Conformational clustering of the three extended simulations shows
that unlike when they are alone in solution, interaction of the peptides
with the membrane surface results in formation of stable structures
that group into just one or two major clusters (Figure a-–f). Unlike most widely studied
AMPs, however,[26,32,33] these stable structures did not exhibit a defined secondary structure,
in keeping with the circular dichroism analysis of octapeptide.[30]
Figure 2
Time series of cluster formation by (a–c) octapeptide,
(d–f)
NH2-octapeptide, (g–i) pentapeptide, and (j–l)
NH2-pentapeptide during simulation in the presence of the
model S. aureus membrane.
Time series of cluster formation by (a–c) octapeptide,
(d–f)
NH2-octapeptide, (g–i) pentapeptide, and (j–l)
NH2-pentapeptide during simulation in the presence of the
model S. aureus membrane.Both peptides partially embed into the head group region
of the
lipid bilayer (Figure a,c, Supporting Information Figure S1).
For octapeptide, the alkyl tail of the lipidated N-terminal residue
(5-methylhexanoyl-d-Dab) and d-Phe residue (5) and,
to a lesser extent, Dab residues 2 and 6 of octapeptide insert most
into the membrane (Figure a). The insertion of d-Phe is in keeping with the
insertion of hydrophobic side chains observed for the α-helical
AMPs, pleurocidin,[25] pardaxin,[62] and GF-17,[63] and
the insertion of lipid moieties has been observed for polymyxin B1[64] and for other lipidated battacin analogs.[65] For pentapeptide, only residue 5-methylhexanoyl-d-Dab 1 inserts into the membrane in all three replicate simulations,
along with residue Dab 2 in replicate 1 only (Figure b). In general, the insertion is much shallower
for pentapeptide than for octapeptide.
Figure 3
Partial atom densities
with respect to the membrane normal for
the lipids and for each residue of (a) octapeptide, (b) NH2-octapeptide, (c) pentapeptide, and (d) NH2-pentapeptide
as labeled during simulation in the presence of the model S. aureus membrane.
Partial atom densities
with respect to the membrane normal for
the lipids and for each residue of (a) octapeptide, (b) NH2-octapeptide, (c) pentapeptide, and (d) NH2-pentapeptide
as labeled during simulation in the presence of the model S. aureus membrane.The peptides also form hydrogen bonds with the lipid head groups
(Supporting Information Figures S3a–c and S4a–c). For octapeptide, Dab residue 2 forms hydrogen
bonds with membrane lipids in all three simulations, Dab residues
1 and 6 form hydrogen bonds in two of the simulations, and Dab 3,
Leu 4, Dab 7, and Leu 8 form hydrogen bonds in one simulation, with
only residue d-Phe 5 failing to form hydrogen bonds in any
of the three simulations. For pentapeptide, Dab residue 2 forms hydrogen
bonds with the membrane in all three simulations, d-Phe 4
and Dab 5 form hydrogen bonds in two simulations, and Dab 1 and Leu
3 form hydrogen bonds in just one of the simulations.The Dab
residues form the majority of the hydrogen bonds to the
membrane, especially for octapeptide, with both the backbone and side
chain amides participating. Dab residues are known to be important
for the binding of antimicrobial peptides to bacterial cell membranes
due to their cationic nature,[61,64,66−68] and MD simulations of polymyxin B1 with E. coli inner and outer membranes revealed that a
large proportion of the hydrogen bonds between polymyxin B1 and the
membrane lipids involved Dab.[64]To
test the importance of the positively charged Dab side chain
on membrane binding, we performed an additional three independent
500 ns simulations for each peptide in which the Dab residues contained
an NH2 group instead of an NH3+ group.
While NH2 is uncharged, it is still capable of forming
hydrogen bonds, albeit to a lesser extent.The NH2–octapeptide still forms reasonably stable
structures after binding to the membrane, particularly in the second
replicate simulation, where it is predominantly in one cluster (Figure g–i), but
these again did not comprise a defined secondary structure. During
the second replicate simulation, hydrogen bonds are formed to just
one lipid, an LPG, initially involving the side chain amides of Dab
residues 1 and 2, and later between the side chain amides of Dab residues
2 and 3 (Supporting Information Figure S3d–f). In contrast, in the first and third replicate simulations,
which are less structurally stable, only three hydrogen bonds are
formed in total, mostly involving backbone amides. Overall, the NH2-octapeptide forms fewer hydrogen bonds with the membrane
than the NH3+-octapeptide.In all three
simulations of the NH2-pentapeptide, the
stability of the pentapeptide structure was reduced compared to the
NH3+-pentapeptide, even after binding to the
membrane (Figure j–l).
There is no clear correspondence between structural stability and
hydrogen bond formation (Supporting Information Figure S4d–f), however.Overall, these results
suggest that while uncharged Dab residues
are still able to form hydrogen bonds with the membrane lipids, the
stronger interactions between positively charged Dab residues and
membrane lipids stabilize the peptide structure, particularly in the
case of the pentapeptide.The importance of Coulombic interactions
is further highlighted
by the much greater magnitude of the Coulombic interaction potential
energies compared to the van der Waals interaction potential energies
for all systems (Figure ).
Figure 4
(a, c, e, g) Van der Waals and (b, d, f, h) Coulombic interaction
potential energies between (a, b) octapeptide, (c, d) NH2-octapeptide, (e, f) pentapeptide, and (g, h) NH2-pentapeptide
and each of the three lipids in the S. aureus membrane during each of the three replicate MD simulations as labeled.
(a, c, e, g) Van der Waals and (b, d, f, h) Coulombic interaction
potential energies between (a, b) octapeptide, (c, d) NH2-octapeptide, (e, f) pentapeptide, and (g, h) NH2-pentapeptide
and each of the three lipids in the S. aureus membrane during each of the three replicate MD simulations as labeled.The lipid with which each peptide has the most
favorable interactions
differs between simulation replicates. It appears that there may be
a slight preference for the interaction with PG and LPG, which would
be in keeping with emerging evidence that AMP resistance tends to
reduce the levels of PG, and sometimes LPG, in bacterial cell membranes.[69] It is more likely, however, that this apparent
preference simply reflects their much greater concentration (54 and
36%, respectively; Table ). In fact, the amount of favorable interactions with DPG
is perhaps surprising, given that it comprises only 5% of the lipids,
although due to its size (four fatty acid tails), it effectively comprises
10% of the surface area. Overall, it appears that neither peptide
has specific lipid preferences, and substantially, more sampling would
be required to investigate this further.
Table 1
Lipid Composition
of the S. aureus and E. coli IM Model Bilayers; The Two Leaflets of each
Bilayer Had Identical
Lipid Composition
model system
lipid headgroup
lipid tail
%
S. aureus
phosphatidylglycerol (PG)
15C anteiso-branched
57%
lysine-phosphatidylglycerol (LPG)
15C anteiso-branched
38%
diphosphatidylglycerol (DPG/cardiolipin)
15C anteiso-branched
5%
E. coli IM
phosphatidylethanolamine
(PE)
1-palmitoyl, 2-cis-vaccenyl (PV)
75%
phosphatidylglycerol
(PG)
1-palmitoyl, 2-cis-vaccenyl (PV)
20%
diphosphatidylglycerol
(DPG/cardiolipin)
1-palmitoyl, 2-cis-vaccenyl (PV)
5%
To facilitate design of novel antimicrobial peptides
with enhanced
activity, the contribution of each residue to the membrane interaction
was also extracted.For the octapeptide, residues 5-methylhexanoyl-d-Dab 1, d-Phe 5, and Leu 8 have the most favorable
van der Waals interactions
(Figure a), in keeping
with the hydrophobic lipid tail and side chains of these residues.
For pentapeptide, residues 5-methylhexanoyl-d-Dab 1 and d-Phe 4 have the most favorable van der Waals interactions (Figure e). This is again
in keeping with the hydrophobic lipid tail and side chains of residues
1 and 4 and the partial atom densities (Figure a). Insertion of residue 5-methylhexanoyl-d-Dab 1 of both peptides is visible in the partial atom densities
(Figure ), but the d-Phe and Leu side chains do not insert as far due to their
shorter length.The favorable Coulombic interactions are, in
general, of higher
magnitude compared to the van der Waals interactions (Figure b,f). For both peptides, d-Dab and Dab residues provide the majority of the favorable
Coulombic interactions with the membrane lipid head groups, which
agrees with the importance of these residues identified by experimental
alanine scanning.[30] These interaction potential
energies were further decomposed to show that the main contribution
comes from the NH3+ groups of the Dab residues
(data not shown). The importance of the positively charged NH3+ group is confirmed by the substantially reduced
peptide–membrane Coulombic interaction energy in the simulations
of the NH2-peptides (Figure d,h). The importance of Dab residues has also been
highlighted by MD simulations[64] and experimental
studies of polymyxin,[61,66,67,70] and results for other AMPs have shown positively
charged amino acids to be critical.[68,71]Interestingly,
we find that the NH2-pentapeptide and
NH2-octapeptide also have reduced van der Waals interaction
potential energies with the membrane core compared to the NH3+ cases (Figure c,g). This is due to reduced insertion of the hydrophobic
portions of the 5-methylhexanoyl-Dab, d-Phe, and Leu residues
into the membrane core (Figure ). It seems, therefore, that stable membrane binding is required
to facilitate insertion of the hydrophobic portions of the peptides
into the membrane.Together, these results indicate that the
favorable Coulombic interactions
between the d-Dab and Dab residues and the negatively charged
lipid head groups provide membrane binding and thus structural stability
to the peptides, which in turn allow for insertion of the hydrophobic
residues into the membrane and further stabilization of the peptide–membrane
interaction through van der Waals interactions. Such a mechanism has
been suggested for other AMPs[21,24,71] and would be in keeping with results of MD simulations of polymyxin
B1.[64]
Interactions with the E. coli IM
In the case of the E. coli IM, both peptides were again found to approach
and form hydrogen
bonds with the membrane rapidly, within 30–50 ns of simulation
(Supporting Information Figures S5a–c and S6a–c).As when interacting with the S. aureus membrane, both peptides become more structurally
stable once bound to the membrane surface, but to a lesser degree,
especially for the pentapeptide (Figure a–g). Whereas on the S. aureus membrane, both peptides grouped predominantly
into a single cluster; here, ∼60% of the simulation time was
spent in the most populated 5–6 clusters. This lack of a single,
stable, and well-defined secondary structure is in keeping with the
experimental circular dichroism results for octapeptide[30] and contrast to many AMPs.[26,32,33]
Figure 5
Time series of cluster formation by (a–c)
octapeptide, (d–f)
NH2-octapeptide, (g–i) pentapeptide, and (j–l)
NH2–pentapeptide during simulation in the presence
of the model E. coli IM.
Time series of cluster formation by (a–c)
octapeptide, (d–f)
NH2-octapeptide, (g–i) pentapeptide, and (j–l)
NH2–pentapeptide during simulation in the presence
of the model E. coli IM.Interestingly, the lipidated N-terminal residue (5-methylhexanoyl-d-Dab) of the octapeptide did not insert into the membrane in
any of the three replicate simulations; rather, residues Dab 7 and
Leu 8 inserted slightly more than the other residues but not beyond
the lipid head groups (Figure a, Supporting Information Figure S2). Overall, the insertion of the octapeptide was greatly reduced
compared to with the S. aureus membrane.
Figure 6
Partial
atom densities with respect to the membrane normal for
the lipids and for each residue of (a) octapeptide, (b) NH2-octapeptide, (c) pentapeptide, and (d) NH2-pentapeptide
as labeled during simulation in the presence of the model E. coli IM.
Partial
atom densities with respect to the membrane normal for
the lipids and for each residue of (a) octapeptide, (b) NH2-octapeptide, (c) pentapeptide, and (d) NH2-pentapeptide
as labeled during simulation in the presence of the model E. coli IM.In contrast, insertion of the pentapeptide was greater than with
the S. aureus membrane, with the hydrophobic
side chains of residues Leu 3 and d-Phe 4 inserting most
in replicate 1 and the lipid tail of 5-methylhexanoyl-d-Dab
1 inserting most in replicates 2 and 3 (Figure c). The hydrophobic Leu-d-Phe is
common amongst lipopeptides[72] and found
to be critical for antimicrobial activity of octapeptide[30] as well as implicated in the interaction of
polymyxin with bacterial cell membranes.[60] Insertion of hydrophobic amino acid side chains has also been observed
for the α-helical AMPs, pleurocidin,[25] pardaxin,[62] and GF-17,[63] and of lipid moieties for polymyxin B1 and other linearized
battacins.[64,65]As with the S. aureus membrane,
both peptides formed hydrogen bonds with the lipid head groups (Supporting
Information Figures S5a–c and S6a–c). These primarily involved the Dab residues, along with the Phe
and Leu backbone amide and, in one replicate simulation of octapeptide,
the C-terminal amide cap.To test the importance of hydrogen
bond formation between the DabNH3+ moieties and the phospholipid head groups,
we again performed an additional three independent simulations for
each peptide in which the Dab residues contained an NH2 group instead of an NH3+ group.As with
the S. aureus membrane,
this change decreased the structural stability of the octapeptide
(Figure d–f),
but it had less effect on the pentapeptide (Figure j–l). The NH2-octapeptide
inserted less deeply into the membrane than the NH3+-octapeptide (Figure b, Supporting Information Figure S2a,b), but two of the three simulations of NH2-pentapeptide
showed insertion of similar depth to that of NH3+-pentapeptide (Figure d, Supporting Information Figure S2c,d),
in keeping with their similar structural stability.The NH2 peptides formed slightly fewer hydrogen bonds
to the membrane lipids than the NH3+peptides,
with none at all formed in replicate 2 of the octapeptide and only
one in replicate 3 of the pentapeptide (Supporting Information Figures S5d–f and S6d–f). In all
other simulations, however, the Dab residues, including the side chain
amides, still formed the majority of the hydrogen bonds.To
provide a more detailed understanding of the factors determining
cell specificity, we again calculated the interaction potential energy
between each peptide and each residue of each type of lipid, and split
this into its Coulombic and van der Waals contributions (Figure ).
Figure 7
(a, c, e, g) Van der
Waals and (b, d, f, h) Coulombic interaction
potential energies between (a, b) octapeptide, (c, d) NH2-octapeptide, (e, f) pentapeptide, and (g, h) NH2-pentapeptide
and each of the three lipids in the E. coli membrane during each of the three replicate MD simulations as labeled.
(a, c, e, g) Van der
Waals and (b, d, f, h) Coulombic interaction
potential energies between (a, b) octapeptide, (c, d) NH2-octapeptide, (e, f) pentapeptide, and (g, h) NH2-pentapeptide
and each of the three lipids in the E. coli membrane during each of the three replicate MD simulations as labeled.For both peptides, more residues have favorable
Coulombic interaction
energies with phosphatidylethanolamine (PE) lipids, followed by PG
and DPG. This largely reflects the much greater concentration of PE
(70%) compared to the other types of lipids (PG, 15%; DPG, 5%; see Table ), however, suggesting
again that neither pentapeptide nor octapeptide have specific lipid
preferences, especially given that such preferences will be difficult
to elucidate without more substantial sampling.For both peptides,
the Dab residues again make a major contribution
to the favorable Coulombic interactions with the membrane lipid head
groups, along with the NH2 moiety in the terminal Leu residue
(Figure e,g). The
latter was particularly important for pentapeptide, most likely due
to its lower number of Dab residues. These results are again in keeping
with alanine scanning of octapeptide[30] and
computational and experimental studies of other AMPs.[61,64,66−68,70,71]As with the S. aureus membrane,
these interactions stabilize the peptide on the membrane surface and
thus facilitate insertion of the hydrophobic residues of the peptide
into the membrane. The latter is visible as negative van der Waals
energies pertaining to interactions between the 5-methylhexanoyl-d-Dab, the d-Phe side chain, and occasionally, the
Leu side chain with the hydrophobic membrane core (Figure a,c). The insertion of these
moieties into the membrane core is visible in the partial electron
densities (Figure ).For the NH2 peptides, the Coulombic interaction
energies
again almost disappear (Figure e–h), and the van der Waals interaction energies are
reduced (Figure a–d).
For the NH2-octapeptide, residues Leu 4, d-Phe
5, and to a lesser extent, 5-methylhexanoyl-d-Dab 1 and Dab
8 show some favorable van der Waals interaction energies, although
the partial atom densities reveal little insertion (Figure b). For the NH2-pentapeptide,
residues 5-methylhexanoyl-d-Dab 1, Leu 3, and Phe 4 have
favorable van der Waals interactions with PE and PG lipids, in keeping
with the insertion of these residues into the membrane core (Figure d).The reduction
in Coulombic interaction energy and slight reduction
in hydrogen bond formation by the NH2 peptides appears
to reduce the insertion of the hydrophobic portions of the octapeptide
into the membrane core but has less effect on the insertion of the
hydrophobic moieties of the pentapeptide.
Conclusions
The two peptides studied here are unusual in that they have activities
against both Gram-negative and Gram-positive model species,[30] which we sought to understand by analyzing in
detail the contributions that each residue and each type of lipid
make to the peptide–membrane interaction. Our simulations did
not seem to reveal any specific lipid preferences with either model
membrane by either of the peptides, although substantially more replicates
of each system would be required to provide a more definitive answer.With both model membranes and peptides, the alkyl tail of the lipidated
N-terminal residue (5-methylhexanoyl-d-Dab) and the d-Phe and Leu residues insert most into the membrane core, anchoring
the peptide to the membrane. The Dab residues improve membrane binding
through increased hydrogen bond formation with both membranes, which
in turn improves the peptide structural stability. The lack of a well-defined
secondary structure and indeed of a specific membrane-bound structure
is in agreement with experimental circular dichroism data[30] but is in contrast to many other AMPs,[26,32,33] which form specific secondary
structures upon membrane binding that appear to be crucial for membrane
disruption. Hydrogen bond formation, structural stability, and insertion
were generally reduced when the NH3+ side chains
of the d-Dab and Dab residues were changed to NH2. An exception to this was the pentapeptide, for which there was
little change.In general, we found that favorable Coulombic
interactions between
Dab residues and the negatively charged lipid head groups drive membrane
association and are required for stable membrane binding and insertion
of the hydrophobic moieties, which anchor the peptides to the membrane.
This mechanism, while previously unconfirmed for these linear battacin
analogs, is in keeping with the results of studies of how a range
of other, predominantly helical AMPs interact with the cell membrane.[21,24,71] It is also in keeping with the
importance of Dab[30,61,64,66,67,70] and other positively charged amino acids,[68,71] along with hydrophobic amino acids[25,30,62,63] and/or lipid moieties[64,65] for effective membrane disruption by a range of AMPs, including
those studied here. Only individual peptide molecules were studied
here, but our results suggest that pentapeptide and octapeptide are
likely to first associate with the membrane surface, with selectivity
coming largely through electrostatic complementarity but ultimately
disrupt the membrane integrity through insertion of their hydrophobic
components.
Computational Methods
Coordinates
Initial coordinates
for both peptides were
obtained using the Avogadro software package[73] and refined by energy minimization and a 500 ps equilibration as
outlined below. Pre-equilibrated coordinates for lipid bilayers representative
of the S. aureus and E. coli inner membranes (Table ) were taken from refs (64, 74). Peptide molecules were placed at least
1.4 nm (the cutoff distance for calculation of inter-atomic interactions)
from the membrane (Supporting Information Figures S1 and S2), and peptide and membrane coordinates were combined
by simply concatenating the coordinate files.
Parameters
The
natural amino acids in both peptides
were modeled using standard GROMOS 54A7[75] parameters. Parameters for l-Dab were obtained by removing
one CH2 group from the side chain of Lys, and d-Phe and d-Dab were obtained by inverting the stereochemistry
of and reordering the atoms surrounding the Cα atom of the l-Phe and l-Dab parameters. The terminal amine of d-Dab was modeled as NH3+, representative
of its state at pH 7, unless otherwise specified. Partial charges
for the NH2 state were obtained by analogy to the deprotonated
state of lysine. GROMOS-CKP[74,76−78] parameters, which are compatible with the GROMOS 54A7 force field,
were used for the phospholipids, including the 5-methylhexanoyl portion
of 5-methylhexanoyl-d-Dab.
Molecular Dynamics Simulations
All the simulations
were performed using the GROMACS MD software package[79] version 2016.3. All bond lengths were constrained using
the LINCS algorithm[80] allowing for a 2
fs time step, and periodic boundary conditions were applied. The energy
of the complete peptide–membrane system was minimized using
the steepest descent algorithm until the maximum force changed by
less than 1000 kJ·mol–1·nm–1 and then solvated using the SPC water model[81] and minimized again. The total number of water molecules depended
on the box size (Table ). Each system was then neutralized by the addition of Na+ ions (Table ) and
again, the potential energy was minimized. Each system was equilibrated
for 500 ps under isothermal–isobaric (NpT) conditions with
the temperature maintained at physiological temperature, 310 K, using
the Berendsen thermostat[82] with a time
constant of 1 ps, and the pressure was maintained at 1 bar using the
Berendsen barostat[82] with semi-isotropic
pressure coupling, a time constant of 1 ps and an isothermal compressibility
of 4.575 × 10–4 (kJ·mol–1·nm–3)−1. For the production
runs, the temperature was maintained at 310 K using the Nosé–Hoover
thermostat[83,84] with a time constant of 1 ps,
and the pressure of 1 bar was maintained using semi-isotropic pressure
coupling using the Parrinello–Rahman barostat[85] with a time constant of 5 ps and an isothermal compressibility
of 4.575 × 10–4 (kJ·mol–1·nm–3)−1. For both the equilibration
and production runs, long-range electrostatic interactions outside
a cutoff of 1.4 nm were treated using the reaction field[86] algorithm, and van der Waals interactions were
truncated at 1.4 nm.
Table 2
Box Dimensions and
the Total Number
of Water Molecules and Na+ Ions for Each Set of Three Replicate
Simulations
S. aureus
E. coli IM
box dimensions (nm)
box dimensions (nm)
peptide
x
y
z
water
Na+ ions
x
y
z
water
Na+ ions
octapeptide
8.32510
7.20975
11.78254
14,959
51
6.00364
6.30451
10.53374
7882
31
pentapeptide
8.32810
7.21234
11.78078
14,977
53
6.00447
6.30538
10.25824
7501
33
NH2-octapeptide
8.31097
7.19750
11.97127
14,635
56
6.10694
6.41299
9.65750
7914
36
NH2-pentapeptide
8.30443
7.19184
12.10536
14,973
56
5.97560
6.27507
9.44980
5867
36
Each peptide was first simulated alone in solution
for 500 ns.
Each peptide–membrane system, comprising one copy of a given
peptide with one of the two types of membrane, was first simulated
in quintuplicate for 50 ns, and three of these were extended to 500
ns.
Analysis
All analysis was carried out using GROMACS
tools unless otherwise specified. Conformational clustering was carried
out using the GROMOS[87] clustering method.
An RMSD cutoff of 0.25 nm was selected as this value results in more
than 60% of the sampled structures being grouped into clusters. Only
the 20 most populated clusters were analyzed. Partial electron densities
along the z axis (perpendicular to the plane of the
membrane) were calculated with the system vertically centered to the
middle of the lipid bilayer. Intermolecular hydrogen bonds between
the peptide and the membrane were calculated using the Visual Molecular
Dynamics (VMD) software[88] and plotted as
a time series with the help of Python and Tcl scripts. Only hydrogen
bonds that appeared over 10% of the simulation were plotted. The interaction
potential energies are the short-range (within the nonbonded cutoff)
nonbonded potential energies between the specified groups, divided
into the contributions from the Coulombic and van der Waals (Lennard–Jones)
force field terms. While it is the free energy that ultimately determines
the behavior of the system, analyzing the potential energies in this
way provides insight into which groups of atoms are interacting and
the nature of these interactions.
Authors: Nathan Schmid; Andreas P Eichenberger; Alexandra Choutko; Sereina Riniker; Moritz Winger; Alan E Mark; Wilfred F van Gunsteren Journal: Eur Biophys J Date: 2011-04-30 Impact factor: 1.733
Authors: Charles H Chen; Charles G Starr; Evan Troendle; Gregory Wiedman; William C Wimley; Jakob P Ulmschneider; Martin B Ulmschneider Journal: J Am Chem Soc Date: 2019-03-13 Impact factor: 15.419
Authors: Nils A Berglund; Thomas J Piggot; Damien Jefferies; Richard B Sessions; Peter J Bond; Syma Khalid Journal: PLoS Comput Biol Date: 2015-04-17 Impact factor: 4.475