Lipid-based inhibitors act directly on GlyT2 - ACS Chemical

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Lipid-based inhibitors act directly on GlyT2 Alexandra Schumann-Gillett, and Megan L O'Mara ACS Chem. Neurosci., Just Accepted Manuscript • DOI: 10.1021/acschemneuro.8b00586 • Publication Date (Web): 05 Dec 2018 Downloaded from http://pubs.acs.org on December 10, 2018

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ACS Chemical Neuroscience

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Lipid-based inhibitors act directly on GlyT2

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Alexandra Schumann-Gillett1 and Megan L. O’Mara1*

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1Research

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2601, Australia

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*[email protected] (corresponding author)

School of Chemistry, The Australian National University, Canberra ACT

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ACS Paragon Plus Environment

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ACS Chemical Neuroscience 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Abstract

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The endogenous lipids N-arachidonylglycine and oleoyl-L-carnitine, are potential

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therapeutic leads in the treatment of chronic pain through their inhibition of the

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glycine transporter GlyT2. However, their mechanism of action is unknown. It has

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been hypothesised that these “bioactive” lipids either inhibit GlyT2 indirectly, by

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significantly perturbing the biophysical properties of the membrane; or directly, by

16

binding directly to the transporter (either from a membrane-exposed or solvent-

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exposed binding site). Here, we used molecular dynamics simulations to study the

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effects of the lipids anandamide, N-arachidonylglycine and oleoyl-L-carnitine on a)

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the biophysical properties of the bilayer, and b) direct binding interactions with

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GlyT2. During the simulations, the biophysical properties of the bilayer itself—for

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example the area per lipid, bilayer thickness and order parameters—were not

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significantly altered by the presence or type of bioactive lipid, regardless of the

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presence of GlyT2. Our work, together with previous computational and experimental

24

data, suggests that these acyl-inhibitors of GlyT2 inhibit the transporter by directly

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binding to it. However, these bioactive lipids bound to various parts of GlyT2 and did

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not prefer a single binding site during 4.5 μs of simulation. We postulate that the

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binding site is located at the solvent-exposed regions of GlyT2. Understanding the

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mechanism of action of these, and related bioactive lipids is essential in effectively

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developing high-affinity GlyT2 inhibitors for the treatment of pain.

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Abbreviations

32 ATB

Automated topology builder

EL4

Extracellular loop 4

GlyT2

Glycine transporter 2

MD

Molecular dynamics

PC

Phosphatidylcholine

PE

Phosphatidylethanolamine

POPC

1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine

SLC6

Solute carrier 6

33 34

Keywords


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Anandamide; GlyT2; lipid inhibitor; molecular dynamics; N-arachidonylglycine;

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oleoyl-L-carnitine; symporter

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Introduction

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Glycine is an inhibitory neurotransmitter that is important in regulating pain sensory

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neurons 1. The glycine transporter, GlyT2, regulates the concentration of glycine in

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the synapse by the transport of glycine from the synaptic cleft into the pre-synaptic

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neuron. GlyT2 activity can be altered by signalling pathways that influence GlyT2

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expression levels, or via the action of inhibitors. For example, GlyT2 expression is

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modulated by glycogen synthase kinase 3 2, neuronal plasma membrane Ca2+-ATPase

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(isoforms 2 and 3) and Na+/Ca2+-exchanger 1 3, and Na+/K+-ATPase 4 . The inhibition

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of GlyT2 has become the target for lipid-based inhibitors to treat chronic pain 5.

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Glycine transport by GlyT2 is reversibly and non-competitively inhibited by N-

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arachidonylglycine (IC50 5.1 μM)

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Transport is inhibited up to 15-fold more by oleoyl-L-carnitine (IC50 340 nM) 9; a

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lipid that is widely distributed throughout the body. In contrast, the structurally

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related lipid and precursor to N-arachidonylglycine, anandamide, has no measurable

54

effects on GlyT2 function 6. Figure 1 shows the chemical structure of anandamide, N-

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arachidonylglycine and oleoyl-L-carnitine. Anandamide and N-arachidonylglycine

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differ only in their head groups, where anandamide has an aminoglycol group and N-

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arachadonylglycine has a glycine group. Oleoyl-L-carnitine has a similar overall

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structure (acyl chain with a polar head group) but both a unique head group

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(carnitine) and acyl chain (monounsaturated, 18-carbon length). N-arachidonylglycine

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reduces pain in rodent models, with minimal side effects 10,11.

6,7;

a lipid present mainly in the spinal cord 8.

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Two main theories have been posed to explain how N-arachidonylglycine and oleoyl-

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L-carnitine

64

biophysical properties of the bilayer, or directly, by binding to a specific binding site

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that is accessible via the membrane or the extracellular solution. For example, as

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acylcarnitines can increase the permeability of the membrane to drugs, it has been

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suggested that they may perturb the lipid order in the bilayer

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influence the transport characteristics of the embedded membrane transporter

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Moreover, endocannabinoids have been associated with lipid raft formation, which

70

could impact the function of neighbouring proteins

71

studies have shown that the addition of fatty acids to model bilayers or liposomes

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alter the biophysical properties of the membrane, such as the phospholipid phase,

inhibit GlyT2. They could act on GlyT2 indirectly, by perturbing the


14–17.

9,12,

which in turn may 13.

Previous experimental

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fluidity and thickness, however the precise nature of these changes depend on the acyl

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tail length and saturation 18.

75 76

While there is a great deal of supporting evidence for a direct and specific binding

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interaction of lipid-based inhibitors with GlyT2, the mechanism of the interaction is

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unclear. Oleoyl-L-carnitine is a relatively potent inhibitor of GlyT2 (IC50 of 340 nM)

79

9,

80

suggestions from experiments are that a) oleoyl-L-carnitine interacts with a

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membrane-exposed site on GlyT2

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interactions with solvent-exposed extracellular loop 4 (EL4). The so-called lipid

83

phase interaction of oleoyl-L-carnitine with GlyT2 has been explored using β-

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cyclodextrin; a cyclic sugar oligosaccharide that removes lipids such as cholesterol

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from cell cultures. In experiments, the binding of oleoyl-L-carnitine to GlyT2 is

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essentially irreversible. However when β-cyclodextrin is added to the preparation,

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oleoyl-L-carnitine binding is reversible. Because β-cyclodextrin removes lipids from

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bilayers, it has been suggested that the oleoyl-L-carnitine binding site on GlyT2 may

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be exposed to the lipid membrane. The cell membrane has also been postulated to

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form a reservoir in which oleoyl-L-carnitine can accumulate 9. Previous investigations

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have shown that anandamide binds to the G protein-coupled cannabinoid receptor

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CB1 via the membrane 19,20, and there is evidence that this binding mechanism is used

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by other highly lipophilic molecules to G-protein coupled receptors and ion channels

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21–23.

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potent GlyT2 inhibitors like oleoyl-L-carnitine to that of common membrane

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phosphatidylcholine (PC) and phosphatidylethanolamine (PE) lipids, it has been

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hypothesised that N-arachidonylglycine, oleoyl-L-carnitine and other inhibitors may

98

inhibit GlyT2 by first inserting into the membrane before associating with GlyT2 5.

that displays intriguing behaviour on the transporter. Two seemingly conflicting 5,9;

and b) oleoyl-L-carnitine inhibits GlyT2 via

Based on these previous studies, and the similarity of the unsaturated C18 tail of

99 100

However, mutagenesis data suggests that the activity of oleoyl-L-carnitine and N-

101

arachidonylglycine on GlyT2 also depends on interactions with specific extracellular

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protein residues, particularly I545, located between extracellular loop 4 (EL4)a and

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EL4b. The I545L mutation significantly reduced oleoyl-L-carnitine and N-

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arachidonylglycine inhibition of GlyT2. It has been proposed that oleoyl-L-carnitine

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and N-arachidonylglycine directly interact with EL4 to inhibit the conformational

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movements required for transport 9. Independent docking studies suggest that


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anandamide and the related lipid, 2-arachidonoyl glycerol, bind to the cannabinoid

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receptor CB1 between the extracellular loops

109

importance in mediating protein/ligand interactions.

24,

further demonstrating their

110 111

Whether lipid-based inhibitors act on GlyT2 indirectly by changing the biophysical

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properties of the membrane in which the transporter is embedded, or directly by

113

binding to a specific location on GlyT2 is still a matter of considerable debate. To this

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end, we performed atomistic molecular dynamics simulations in which our

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experimentally characterised GlyT2 model 25 was embedded in bilayers that contained

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1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) and cholesterol, and

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either anandamide (negligibly active), N-arachidonylglycine (active) or oleoyl-L-

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carnitine (potent), as illustrated in Figure 2. We show how these “bioactive” lipids

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affect the biophysical properties of the bilayer in which they are embedded, with and

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without GlyT2; and we present their membrane-accessible binding interactions with

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GlyT2 embedded in bilayer containing POPC and cholesterol.

122 123

Results and discussion

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With the emergence of a new class of effective acyl GlyT2 inhibitors, there has been

126

speculation as to how these drugs elicit inhibition on GlyT2. Theories include a)

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indirect action on GlyT2 by altering the environment (membrane) in which GlyT2 is

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embedded; b) direct binding to GlyT2 from the membrane; and c) direct binding to

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solvent-exposed areas of GlyT2. Here, we performed 12 μs of atomistic molecular

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dynamics simulations of POPC bilayers enriched with 20 mol % cholesterol, lacking

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and containing membrane embedded GlyT2 and 5 mol % of each of the following

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bioactive lipids: anandamide, N-arachidonylglycine and oleoyl-L-carnitine, to address

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theories a) and b).

134 135

Membrane-embedded anandamide, N-arachidonylglycine and oleoyl-L-carnitine

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have little effect on the biophysical properties of the bilayer

137 138

The bilayer thickness and POPC order parameter were not significantly altered in the

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simulations containing or lacking the bioactive lipids, or GlyT2, as shown in Figure 3

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and Table 1. The thickness of the control POPC/cholesterol bilayer remained


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unchanged in the presence (42.8 ± 0.2 Å) or absence (42.8 ± 0.5 Å) of GlyT2. The

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thickness of POPC bilayers enriched with 20 mol % cholesterol is 43 Å in other

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simulations 26 and in experiments (containing 20 mol % cholesterol and a

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phospholipid similar to POPC, SOPC)

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arachidonylglycine or oleoyl-L-carnitine into the bilayers did not substantially alter

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the bilayer thickness, as shown in Figure 3A and Table 1. Likewise, the addition of

147

GlyT2 or 5 mol % of any one of the bioactive lipids had an almost negligible effect on

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the ordering of the POPC tails, as shown in Figure 3C–D. In the absence of GlyT2,

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there was a slight increase in the order parameter for the bilayers containing 5 %

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bioactive lipid (maximum increase of approximately 0.001 units between N-

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arachidonylglycine and control bilayer lacking GlyT2 for carbon 9 of sn-1 tail). The

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POPC order parameter was not altered by adding 5 mol % bioactive lipid to the

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bilayers containing GlyT2. The order parameters for the control system are similar to

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those obtained previously 28.

27.

Incorporating anandamide, N-

155 156

In the absence of GlyT2, the mean area per POPC of the control POPC/cholesterol

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bilayer was 53.0 ± 0.7 Å2. In comparison, the mean area per POPC decreased in all

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cases when 5 % bioactive lipid was added, to give values between 49.2 ± 0.8 Å2 and

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51.2 ± 0.6 Å2 as shown in Table 1 and Figure 3B. When GlyT2 was present in the

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membrane, the mean area per POPC increased by 3.5 ± 0.9 Å2. The mean area per

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lipid of the control POPC/cholesterol bilayer increased from 53.0 ± 0.7 Å2 to

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55.2 ± 0.9 Å2 when GlyT2 was present. Table 1 shows similar trends in the presence

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of GlyT2 for the bilayers containing 5 mol % anandamide, N-arachidonylglycine and

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oleoyl-L-carnitine. The average experimental area per lipid for SOPC, which has the

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same head group as POPC, in a bilayer containing 20 mol % cholesterol is

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approximately 56 Å2 27.

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It should be noted that the bilayers without GlyT2 contained fewer lipids than the

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bilayers with embedded GlyT2, as shown in Table 2. Previous studies have suggested

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that the increase in the area per POPC molecule that we observed when GlyT2 was

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present could be due to finite size effects 29. To ensure that finite size effects were not

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influencing the mean area per POPC observed in the absence of GlyT2, we simulated

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a larger bilayer that contained POPC, cholesterol and 5 mol % anandamide (without

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GlyT2) that had the same box dimensions as the bilayer containing GlyT2. The mean


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area per POPC for the large anandamide-containing bilayer that lacked GlyT2 was

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51.0 Å ± 0.4 Å (c.f. 50.5 ± 0.6 Å for the smaller bilayer) and its thickness was

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42.9 ± 0.1 Å (c.f. 43.0 ± 0.3 Å for the smaller bilayer). The order parameters for

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POPC in the larger anandamide-containing bilayer are shown in Supporting

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Information Figure S1. There is no difference between the order parameters in the

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smaller bilayer and the larger bilayer. The area per POPC and thickness of the larger

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bilayer are within error for the smaller GlyT2-lacking bilayer (Table 1), therefore

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finite size effects are unlikely to have impacted our results. Simulations of the lipid 2-

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hydroxyoleic acid, which exhibits anti-tumour activity, embedded in a POPC bilayer

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show that incorporating it into a bilayer has little effect on the area per lipid and

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bilayer thickness (on the order of tenths of Å2 or Å) 30. We did not observe any lipid

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raft formation in our simulations. Our data suggest that anandamide, N-

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arachidolylglycine and oleoyl-L-carnitine do not alter the biophysical properties of the

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bilayer. Recent experimental data support this finding, for example membrane

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capacitance measurements show that insertion of endocannabanoids has limited effect

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on the thickness of phospholipid bilayers 31.

191 192 193

Anandamide snorkelled into the bilayer but N-arachidonylglycine and oleoyl-L-

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carnitine remained at the lipid/water interface

195 196

During MD simulations, anandamide “snorkelled” into the centre of the bilayer

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regardless of the presence of GlyT2. This behaviour is reflected in the normalised

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number density for the location of the head group atoms of each bioactive lipid and

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GlyT2, shown in Figure 4A–B. At the start of the simulations, all lipids, including the

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bioactive lipids, were embedded into the bilayer with their head group at the

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lipid/water interface and their tail group elongated approximately parallel to the

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bilayer normal. The head group atoms chosen (the phosphorus atom of POPC, the

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oxygen of cholesterol and the nitrogen of the bioactive lipids) remained at the

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lipid/water interface for all lipids except anandamide. As illustrated in Figure 4C,

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anandamide was able to “snorkel” into the membrane and interact with GlyT2 near

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the membrane-embedded TM helices. In the absence of GlyT2, the normalised

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number density when the anandamide head groups were in the centre of the bilayer

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was 0.2, and when GlyT2 was present it was 0.3. The interactions between


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anandamide and GlyT2 were largely transient and occurred on the scale of tens of

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nanoseconds.

211 212

To quantify the flexibility of the bioactive lipids in each membrane, we measured

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their start-to-end intramolecular distance, shown in Figure 5A. In bilayers lacking

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GlyT2, this distance was 18–21 Å for N-arachidonylglycine and oleoyl-L-carnitine,

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and 14–18 Å for anandamide. The shorter distance for anandamide was due to the

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acyl chain folding over on itself, as observed in previous studies

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conformation facilitated the removal of the anandamide head group from the

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lipid/water interface, allowing it to “snorkel” to the centre of the bilayer. In contrast,

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the head groups of N-arachidonylglycine and oleoyl-L-carnitine remained at the

220

lipid/water interface (Figure 4) and these lipids adopted an elongated confirmation as

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in Figure 5C. The intra-molecular flexibility of anandamide and N-arachidonylglycine

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was largely unaltered when GlyT2 was present or absent in the bilayer, as shown in

223

Figure 5B (with some outliers in the spread of the data due to a larger sample size

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when GlyT2 was present). However, the intra-molecular flexibility of oleoyl-L-

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carnitine increased to 19–23 Å when GlyT2 was present, with the majority of the data

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clustered at approximately 22 Å. Therefore, oleoyl-L-carnitine displayed an extended

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conformation, at least as elongated as that shown in Figure 5C, in the bilayer that

228

contained GlyT2.

32.

This folded

229 230 231

Anandamide, N-arachidonylglycine and oleoyl-L-carnitine do not display a

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conserved binding site on GlyT2

233 234

In light of our above findings that the bioactive lipids studied here do not significantly

235

alter the biophysical properties of the membrane, we hypothesised that these bioactive

236

lipids could act on GlyT2 by directly binding to it from the membrane. To assess the

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structural stability of GlyT2 embedded in our membrane systems, we measured its

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backbone root-mean-square deviation. During the during the first 25 ns of all

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simulations, GlyT2 adjusted to the modified lipid bilayer and adopted a conformation

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that was within 2–4 Å of the starting structure, then plateaued, as shown in

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Supporting Information Figure S2, indicating that the conformation of GlyT2 was

242

stable in all simulations.


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To examine the interactions between the membrane-embedded bioactive lipids and

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GlyT2, we recorded the regions of GlyT2 that the bioactive lipids interacted with

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during the final 400 ns of each simulation replicate. Of the three bioactive lipids,

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anandamide bound to GlyT2 the most frequently (Supporting Information Figure

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S3A), followed by N-arachidonylglycine (Supporting Information Figure S3B), then

249

oleoyl-L-carnitine (Supporting Information Figure S3C). In fact, anandamide bound to

250

GlyT2 almost eight times more frequently than oleoyl-L-carnitine, and N-

251

arachidonylglycine bound to GlyT2 almost three times more than oleoyl-L-carnitine.

252 253

The binding locations in Supporting Information Figure S3 show little conservation

254

between lipid type, but some conservation between replicate simulations. To identify

255

any conserved binding locations on GlyT2, we combined the replicate binding data

256

for each bioactive lipid and averaged it to calculate the binding propensity for each

257

GlyT2 residue. Figure 6 shows the binding propensity data for anandamide (Figure

258

6A), N-arachidonylglycine (Figure 6B) and oleoyl-L-carnitine (Figure 6C), coloured

259

in greyscale and mapped onto the structure of GlyT2. Regions of GlyT2 that bioactive

260

lipids did not associate with are coloured by helix. Supporting Information Figure S3

261

and Figure 6 show that none of the lipids consistently bound to GlyT2 in the solvent-

262

exposed regions (i.e. the light salmon coloured parts of GlyT2 in Figure 6).

263

Furthermore, anandamide and N-arachidonylglycine consistently bound to different

264

regions of GlyT2, with little or no overlap in the binding regions. For example,

265

anandamide displayed widespread adsorption to all TM helices and consistently

266

bound to the extracellular region of TM9 (Figure 6A; right side view), whereas N-

267

arachidonylglycine never bound there. Although N-arachidonylglycine remained in

268

the bilayer, oriented with its head group at the lipid/water interface (c.f. atom density

269

data and Figure 4), it bound to the extracellular portion of TM5 and the intracellular

270

portion of TM1 during all simulations (Figure 6B). Oleoyl-L-carnitine—the most

271

experimentally potent bioactive lipid studied here—did not consistently bind to any

272

specific regions of GlyT2 within the timeframe of the simulations.

273 274

Previous studies have found that anandamide does not perturb the properties of the

275

bilayer 19,31 and interacts specifically with the G protein-coupled cannabinoid receptor

276

CB1 at a membrane-exposed site 19. Intriguingly, although the same number of each


10

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277

of the three bioactive lipids were used in the simulations, and all three bound to the

278

GlyT2 transmembrane domains, the most potent inhibitor, oleoyl-L-carnitine,

279

interacted the least with GlyT2 and did not display a conserved binding site between

280

the three simulation replicates (see Supporting Information Figure S3C and Figure

281

6C). This could simply be due to lipid diffusion or insufficient sampling; however the

282

concentration of bioactive lipid used in each simulation was an order of magnitude

283

larger than the half maximal inhibitory concentration for oleoyl-L-carnitine on GlyT2.

284

Our simulations contained 5 mol % bioactive lipid embedded in the bilayer; a

285

concentration of approximately 3000 nM of inhibitor with respect to the entire

286

solute/solvent system. The experimental IC50, for oleoyl-L-carnitine is 340 nM 5,9. The

287

relatively large concentration could explain why anandamide, which does not inhibit

288

GlyT2 6, adsorbed all over transmembrane domains, and at conserved locations

289

between the replicates, for example at the extracellular portion of TM9 and at residues

290

on TM10, TM11 and TM12. The number of binding interactions between anandamide

291

and GlyT2 could also be attributed to the flexible “snorkelling” behaviour

292

anandamide displayed, where it folded over and moved in the centre of the bilayer as

293

shown in Figure 4C (c.f. Figures 4A–B and 5). Alternatively, the behaviour displayed

294

by anandamide could be considered to be similar to that of POPC, with widespread

295

non-specific associations. Conversely, oleoyl-L-carnitine did not display many non-

296

specific associations, but did not show specific binding behaviour in the timescale of

297

the simulations.

298 299

Compared to anandamide, the GlyT2 inhibitors N-arachidonylglycine and oleoyl-L-

300

carnitine remained in an elongated conformation (see Figure 5) and their head groups

301

continually resided at the lipid/water interface (see Figure 4). Polyunsaturated fatty

302

acids are relatively flexible and can form folded structures, whereas monounsaturated

303

fatty acids adopt elongated structures with a local kink at the site of unsaturation

304

During all simulations, N-arachidonylglycine, which inhibits GlyT2 15-fold less than

305

oleoyl-L-carnitine, bound to the extracellular portion of TM1 and the intracellular

306

portion of TM5 (Figure 6B, greyscale colouring) while oleoyl-L-carnitine bound

307

three-fold less than N-arachidonylglycine and did not bind to a conserved location on

308

GlyT2. While GlyT2 can be modulated by the presence of lipid raft formation 34 and

309

neighbouring proteins 2–4, recent experimental data suggest that the head group of a

310

lipid inhibitor could determine the stability of GlyT2 in the bilayer 5. The consistent


33.

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extracellular interactions between N-arachidonylglycine and the extracellular portions

312

of TM1 and TM5 support the postulation by Carland and co-workers that the head

313

groups of N-arachidonylglycine and oleoyl-L-carnitine could interact with GlyT2 at

314

the extracellular lipid/water interface of the TM domains, and influence the

315

movement of EL4 during transport 9.

316 317

There is strong evidence that acyl inhibitors bind to GlyT2 from solution. EL2 and

318

EL4 are required for N-arachidonylglycine to inhibit GlyT2 7, and EL4 is essential for

319

oleoyl-L-carnitine to inhibit GlyT2 9. Figure 6 shows EL4 (shaded in salmon) is

320

located next to the extracellular region of TM5 (cyan) where N-arachidonylglycine

321

consistently bound. In fact, N-arachidonylglycine bound at the extracellular loops of

322

the transmembrane lysophosphatidic acid receptor 5 (formerly known as GPR92) in a

323

study that combined docking with site-directed mutagenesis 35. Docking studies have

324

also suggested that anandamide and related lipids bind near the extracellular loops of

325

cannabinoid receptors 24,36 and ion channels 37.

326 327

We have shown that, at concentrations one order of magnitude higher than those used

328

experimentally, the incorporation of anandamide, N-arachidonylglycine and oleoyl-L-

329

carnitine into the bilayer does not significantly perturb the biophysical properties of

330

the bilayer. Our results also show that membrane-embedded anandamide, N-

331

arachidonylglycine and oleoyl-L-carnitine do not interact with GlyT2 at a specific

332

location that is accessible from within the membrane within a 500 ns timeframe. We

333

therefore hypothesise that the bioactive lipid binding site of GlyT2 may not be

334

accessible from the hydrophobic core of the membrane. We are currently

335

investigating the binding patterns of other lipid-based inhibitors to GlyT2 to

336

determine whether uptake occurs from solution or from the lipid/water interface. By

337

identifying the mechanism of action of these bioactive lipid inhibitors of GlyT2, we

338

move closer to developing targeted, selective and reversible treatments for chronic

339

pain.

340 341 342

Methods

343

Molecular dynamics simulations

344


12

Page 13 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


345

We simulated bilayers that contained POPC and cholesterol, and added bioactive

346

lipids and GlyT2. The specific compositions of the bilayers, expressed as molar ratios,

347

were approximately: 5 % anandamide with 20 % cholesterol and 75 % POPC, 5 % N-

348

arachidonylglycine with 20 % cholesterol and 75 % POPC, and 5 % oleoyl-L-

349

carnitine with 20 % cholesterol and 75 % POPC. As controls, we simulated a bilayer

350

containing GlyT2, 20 % cholesterol and 80 % POPC, and these bilayers without

351

GlyT2. The number of lipids in each bilayer is given in Table 2. Note that we

352

simulated the bilayers without GlyT2 for 0.5 μs first, and then used the coordinates

353

from the end of a 0.5 μs simulation of each bilayer type to build the bilayers that

354

contained GlyT2. Snapshots of each bilayer, lacking and containing GlyT2, are shown

355

in Figure 2.

356 357 358

Molecular coordinates and topologies

359 360

The coordinates of our experimentally validated homology model of GlyT2 (in the

361

outward-occluded conformation) were taken from Subramanian et al. 25. To determine

362

whether inhibitor interactions were competitive or non-competitive with the glycine

363

substrate, all simulations were performed on apo GlyT2, in the absence of substrate or

364

bound ions. The united atom coordinates and parameters for anandamide, N-

365

arachidonylglycine and oleoyl-L-carnitine were developed using the Automated

366

Topology Builder and Repository (ATB)

367

available for download from the ATB (anandamide MoleculeID: 250693, N-

368

arachidonylglycine MoleculeID: 250689, oleoyl-L-carnitine MoleculeID: 296337).

369

Note that the force constant associated with cis double bonds that the ATB produced

370

was routinely low enough to allow for cis/trans isomerisation around the double bond

371

at room temperature—a process not found under biological conditions. To prevent

372

non-physiological cis/trans isomerisation, the the force constants of all double bonds

373

in the ATB parameters for anandamide, N-arachidonylglycine and oleoyl-L-carnitine

374

were altered from their original value of 5.86 kJ/mol/rad2 to a revised value of 41.80

375

kJ/mol/rad2. To ensure that the cis double bond conformations were maintained, each

376

lipid was simulated for 1 ns in a box of water prior to incorporating it into a bilayer.

377

The POPC parameters were taken from Poger and Mark

378

parameters were taken from the ATB 38–40. As classical MD simulations implement a

38–40.

The coordinates and topologies are


41

and the cholesterol

13


Page 14 of 37

379

fixed protonation state, rather than an assigned pH, all lipids were simulated in the

380

protonation state in which they would most likely be found at physiological pH

381

(pH 7). The pKa of the POPC phosphonium group is 1.86, and the pKa’s of the

382

carboxylic acid groups of N-arachidonylglycine and oleoyl-L-carnitine are 3.98 and

383

4.22, respectively, as calculated using the method implemented in ChemAxon 42.

384

Thus, POPC and oleoyl-L-carnitine were simulated as zwitterions and N-

385

arachidonylglycine was simulated in its deprotonated form, as shown in Figure 1. The

386

number of lipids in each bilayer is included in Table 2.

387 388

System Setup

389 390

The simulations were prepared and performed using version 2016.1 of the

391

GROMACS engine 43,44 with the GROMOS54A7 force field for proteins and lipids 44.

392

An equal number of bioactive lipids were incorporated into the upper and lower

393

leaflets of each respective bilayer system, and initially positioned so that they were

394

evenly distributed throughout the leaflet prior to energy minimisation and

395

equilibration. All bilayers were oriented in the x-y plane of a solvated rectangular box.

396

Water was simulated explicitly using the simple point charge water model 45. Na+ and

397

Cl- were included to neutralise the system, and 0.15 M of these ions was added to

398

mimic physiological conditions. Prior to production simulations, periodic boundary

399

conditions were applied and all systems were energy minimised using a steepest

400

descent algorithm.

401 402

All bilayers (lacking or containing GlyT2) underwent a 5 ns equilibration simulation

403

after the initial energy minimisation, to visually assess the coordinates of each system.

404

For the systems containing GlyT2, a series of five consecutive 1 ns position restrained

405

simulations were performed, where the positions of the heavy protein atoms were

406

restrained by a harmonic potential that was successively lowered. The force constant

407

of this potential was initially 1,000 kJ/mol/nm for the first position restrained

408

simulation, and was progressively decreased to 500 kJ/mol/nm, 100 kJ/mol/nm,

409

50 kJ/mol/nm and finally 10 kJ/mol/nm for the following four position restrained

410

simulations. The coordinates of each system after the initial 5 ns simulations

411

(unrestrained for bilayers without GlyT2; restrained for bilayers with GlyT2) were


14

Page 15 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


412

used as the starting conformation for three independent, 0.5 μs simulations per

413

system.

414 415

Simulation Details

416 417

The simulation conditions were consistent for all simulations, regardless of the

418

presence of GlyT2, and are documented by Carland and co-workers

419

velocities were assigned at the start of each simulation replicate. The simulations were

420

performed in the NPT ensemble, where the temperature was maintained by coupling

421

the bilayer (solute) and the solvent separately to an external temperature bath at

422

300 K. The Bussi-Donadio-Parrinello velocity rescale thermostat

423

with a coupling constant, τT = 0.1 ps. Similarly, the pressure was maintained at 1 bar

424

by weakly coupling the system to an external pressure bath using the Berendsen

425

thermostat. The pressure coupling was semi-isotropic, isotropic in the plane of the

426

bilayer (x-y). The isothermal compressibility was 4.5 × 10-5 bar and the coupling

427

constant was τT = 0.5 ps. The lengths of the covalent solute bonds were constrained

428

using the LINCS algorithm

429

constrained using the SETTLE algorithm

430

bonded interactions were updated every time step. The electrostatic interactions were

431

calculated using particle mesh Ewald summation and the Lennard-Jones interactions

432

were calculated with a 1.0 nm cut-off. Images of the systems were produced using the

433

Visual Molecular Dynamics software 50.

48

47

46.

Unique

was employed,

and the geometry of the water molecules was 49.

Both the electrostatic and the non-

434 435

Analysis

436 437

In each case, the first 100 ns of each simulation was treated as an equilibration period,

438

unless otherwise stated. The final 400 ns of each simulation (i.e. 100 ns–500 ns) were

439

used for data analysis. The output was processed so that 400 ns corresponded to 400

440

frames. All data were calculated for each of these frames unless otherwise stated, and

441

averages were calculated over all frames and replicates.

442 443

Bilayer thickness

444


15


Page 16 of 37

445

We calculated the bilayer thickness using the FATSLiM software 51, and selected the

446

phosphorus atoms on POPC as the reference atoms. The program performs a

447

neighbour search and identifies neighbouring lipids, for each lipid, and iteratively

448

calculates the normal. A single lipid is chosen to serve as a modulator for the

449

reference position when its normal is within 10o of the reference (bilayer) normal.

450

This treatment is important for undulating membranes. An averaged position is

451

calculated based on the lipid’s neighbours and the local normal is used with this

452

averaged position to estimate the inter-leaflet distance. Once an averaged position is

453

calculated for one leaflet, a neighbour search is performed on the other leaflet, where

454

lipids close to the reference position and lipids belonging to the other leaflet are

455

identified. We used a neighbour search cut-off distance of 6 nm. Lipids are selected if

456

the distance vector between the neighbour and the reference position is within 10o of

457

the reference normal. Again, an averaged position is calculated. The bilayer thickness

458

is calculated using the distance vector between the two averaged positions. The mean

459

and standard deviation of the combined replicate trajectories (for 100 ns–500 ns) are

460

reported in Table 1.

461 462

Area per lipid

463 464

The FATSLiM software was used to calculate the area per lipid 51. First, a neighbour

465

search is performed for each lipid, using a 3 nm cut-off radius. The curvature within

466

this cut-off is assumed to be negligible. Neighbour lipids are projected onto the x-y

467

plane with the z-coordinate of the reference atom. These projected lipids are then used

468

to calculate the Voronoi cell. The lipid’s accessible area is approximated based on its

469

Voronoi cell. Importantly, FATSLiM takes membrane proteins into account—any

470

protein atoms that lie within the Voronoi cell are projected onto the same plane as the

471

lipids (x-y in our case), and the centre of geometry for those protein atoms inside the

472

Voronoi cell is calculated and removed from the Voronoi cell. An updated cell is used

473

to calculate the area of the lipid in question. The area per lipid was calculated for all

474

lipids in the system, and is reported for POPC for comparison to existing data. The

475

mean and standard deviation of the combined replicate trajectories, for 100 ns–500 ns,

476

are given in Table 1.

477 478

Deuterium order parameter


16

Page 17 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


479 480

We calculated the deuterium order parameter with the gmx order tool provided in the

481

GROMACS software. Note that this tool mistreats double bonds unless particular care

482

is taken

483

carbon atoms as recommended by Piggot and co-workers

484

previous work

485

according to equation 1:

486

𝑆𝐶𝐷 =

(1)

494 495

Lipid head group location

496 497

We determined the location of the lipid head groups by calculating the number

498

density of specific head group atoms for each lipid in the simulation box, and GlyT2

499

if it was present in the bilayer. After centring the bilayer, we performed the number

500

density calculation on the phosphorus atom of POPC, the oxygen of cholesterol and

501

the nitrogen of the bioactive lipids along the z-axis (perpendicular to the plane of the

502

membrane). We performed this calculation for each frame. Because our bilayers

503

contained a heterogeneous number of constituents, we normalised the data with

504

respect to unity so that we could clearly show the locations of the atoms on a single

505

axis.

506 507

Bioactive lipid conformation

508 509

To characterise the conformations that each bioactive lipid adopted in the bilayers, we

510

calculated the pairwise distance between a defined carbon atom on either end of each

511

bioactive lipid as shown in Figure 5C. We averaged the inter-atom distance data over


17


Page 18 of 37

512

the final 400 ns of each simulation replicate for each bioactive lipid molecule, in each

513

system.

514 515

Root-mean-square deviation

516 517

We calculated the root-mean-square deviation (RMSD) of the backbone of GlyT2 by

518

first fitting the backbone to a reference structure, and then computing the deviation of

519

the backbone from the reference using the method of Maiorov and Crippen

520

reference structure was the first frame of the unrestrained simulation. The mean

521

RMSD and standard deviation (for 100 ns–500 ns) are given in Table 1.

56.

The

522 523

Lipid binding

524 525

To characterise how membrane-incorporated bioactive lipids, and cholesterol, bind to

526

GlyT2, we calculated a) the binding location of each lipid to GlyT2 over time, and b)

527

the binding propensity of each lipid to the structure of GlyT2. For a), we recorded

528

every time that any bioactive lipid was within 4 Å of a protein residue, for each frame

529

in each replicate. For b), we combined the binding data from a), averaged it and

530

calculated its proportion so that we had a single binding propensity value for each

531

GlyT2 residue. We did this for each type of bioactive lipid and used the binding

532

propensity data as beta values to map the data onto the structure of GlyT2.

533 534

ASSOCIATED CONTENT

535

Supporting Information

536

Additional figures are given as Supporting Information, including: order parameters

537

for larger bilayer lacking GlyT2 (Figure S1); the root-mean-square deviation of

538

GlyT2 (Figure S2); and bioactive lipid binding patterns over time (Figure S3).

539 540

AUTHOR INFORMATION

541

Corresponding Author

542

* Dr. Megan O’Mara


18

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543

* E-mail: [email protected]

544

Present Addresses

545

1Research

546

2601, Australia.

547

Author Contributions

548

Conceived and designed the experiments: MLO and AS. Performed the experiments:

549

AS. Analysed the data: AS. Contributed reagents/materials/analysis tools: MLO.

550

Wrote the manuscript: AS and MLO.

551

Funding Sources

552

This work was supported by grants from the National Health and Medical Research

553

Council (APP1082570, APP1144429). AS is a recipient of a Westpac Future Leaders

554

Scholarship.

555

Notes

556

The authors declare no competing financial interest.

School of Chemistry, The Australian National University, Canberra ACT

557 558

ACKNOWLEDGMENT

559

The research was undertaken with the assistance of resources and services from the

560

National Computational Infrastructure (NCI), which is supported by the Australian

561

Government. We thank Prof Robert Vandenberg and Dr Shannon Mostyn for their

562

discussions and feedback.

563


19


564

Page 20 of 37

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Geerke, D. P., Stougie, L., and Klau, G. W. (2013) Charge group partitioning in

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biomolecular simulation. J. Comput. Biol. 20, 188–198.

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(41) Poger, D., and Mark, A. E. (2010) On the validation of molecular dynamics

693

simulations of saturated and cis-monounsaturated phosphatidylcholine lipid bilayers:

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a comparison with experiment. J. Chem. Theory Comput. 6, 325–336.

695

(42) Szegezdi, J., and Csizmadia, F. (2007) A method for calculating the pKa values

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of small and large molecules. ACS Spring Meet.

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(43) Abraham, M. J., Murtola, T., Schulz, R., Páll, S., Smith, J. C., Hess, B., and

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Lindahl, E. (2015) Gromacs: high performance molecular simulations through multi-

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level parallelism from laptops to supercomputers. SoftwareX 1–2, 19–25.


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(44) Schmid, N., Eichenberger, A. P., Choutko, A., Riniker, S., Winger, M., Mark, A.

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E., and Van Gunsteren, W. F. (2011) Definition and testing of the GROMOS force-

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field versions 54A7 and 54B7. Eur. Biophys. J. 40, 843–856.

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(45) Hermans, J., Berendsen, H. J. C., Van Gunsteren, W. F., and Postma, J. P. M.

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(1984) A consistent empirical potential for water–protein interactions. Biopolymers

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23, 1513–1518.

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(46) Carland, J. E., Thomas, M., Mostyn, S. N., Subramanian, N., O’Mara, M. L.,

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Ryan, R. M., and Vandenberg, R. J. (2018) Molecular determinants for substrate

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interactions with the glycine transporter GlyT2. ACS Chem. Neurosci. 9, 603–614.

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(47) Bussi, G., Donadio, D., and Parrinello, M. (2007) Canonical sampling through

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velocity rescaling. J. Chem. Phys. 126, 014101.

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(48) Hess, B., Bekker, H., Berendsen, H. J. C., and Fraaije, J. G. E. M. (1997) LINCS:

712

a linear constraint solver for molecular simulations. J Comput Chem 18, 1463–1472.

713

(49) Miyamoto, S., and Kollman, P. A. (1992) Settle: an analytical version of the

714

SHAKE and RATTLE algorithm for rigid water models. J. Comput. Chem. 13, 952–

715

962.

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(50) Humphrey, W., Dalke, A., and Schulten, K. (1996) VMD: visual molecular

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dynamics. J. Mol. Graph. 14, 33–38.

718

(51) Buchoux, S. (2017) FATSLiM: a fast and robust software to analyze MD

719

simulations of membranes. Bioinformatics 33, 133–134.

720

(52) Pluhackova, K., Kirsch, S. A., Han, J., Sun, L., Jiang, Z., Unruh, T., and

721

Böckmann, R. A. (2016) A critical comparison of biomembrane force fields: structure

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and dynamics of model DMPC, POPC, and POPE bilayers. J. Phys. Chem. B 120,

723

3888–3903.

724

(53) Piggot, T. J., Ángel, P., and Khalid, S. (2017) Correction to molecular dynamics

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simulations of phosphatidylcholine membranes: a comparative force field study. J.

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Chem. Theory Comput. 13, 1862–1865.

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(54) Piggot, T. J., Allison, J. R., Sessions, R. B., and Essex, J. W. (2017) On the

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calculation of acyl chain order parameters from lipid simulations. J. Chem. Theory

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Comput. 13, 5683–5696.

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(55) Schumann-Gillett, A., and O’Mara, M. L. (2018) The effects of oxidised

731

phospholipids and cholesterol on the biophysical properties of POPC bilayers.

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Biochim. Biophys. Acta - Biomembr. DOI: 10.1016/j.bbamem.2018.07.012.

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(56) Maiorov, V. N., and Crippen, G. M. (1995) Size-independent comparison of


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734


protein three-dimensional structures. Proteins 22, 273–283.

735 736


25


737

Page 26 of 37

Tables

738 Property

Area per POPC (Å2)

RMSD (Å)

System

No GlyT2

GlyT2

No GlyT2

GlyT2

GlyT2

POPC + 20 % CLR

42.8 ± 0.5

42.8 ± 0.2

53.0 ± 0.7

55.2 ± 0.9

3.1 ± 0.2

43.0 ± 0.3

42.8 ± 0.2

50.5 ± 0.6

53.8 ± 0.8

2.8 ± 0.4

43.4 ± 0.4

42.9 ± 0.2

49.2 ± 0.8

53.8 ± 0.9

3.2 ± 0.3

43.0 ± 0.3

42.8 ± 0.3

51.2 ± 0.6

55.3 ± 0.8

2.9 ± 0.4

43.1 ± 0.4

42.8 ± 0.2

51.0 ± 0.7

54.5 ± 0.9

3.0 ± 0.3

POPC + 20 % CLR + 5 % ANAN POPC + 20 % CLR + 5 % NAGL POPC + 20 % CLR + 5 % CARN Mean

739 740 741 742

P-P distance (Å)

Table 1. Mean properties of the bilayer and mean root-mean-square deviation (RMSD) of GlyT2 during the simulations (100 ns–500 ns). The data are averaged over the three simulation replicates. The error is the standard deviation. CLR, cholesterol; ANAN, anandamide; NAGL, N-arachidonylglycine; CARN, oleoyl-L-carnitine.

743


26

Page 27 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Number of lipids Bilayer

No GlyT2 BIOA

POPC + 20 % CLR POPC + 20 % CLR + 5 % ANAN POPC + 20 % CLR + 5 % ANAN (large bilayer) POPC + 20 % CLR + 5 % NAGL POPC + 20 % CLR + 5 % CARN

744 745

CLR

POPC

-

32

16

GlyT2 TOTAL

BIOA

CLR

POPC

TOTAL

160

192

-

223

851

1074

64

240

320

55

223

851

1129

64

256

960

1280

-

-

-

-

16

64

240

320

57

218

851

1126

16

64

240

320

57

223

871

1151

Table 2. The total number of lipids in each bilayer. BIOA, bioactive lipid; CLR, cholesterol; ANAN, anandamide; NAGL, N-arachidonylglycine; CARN, oleoyl-L-carnitine.

746 747 748 749 750 751 752

Figure Legends

753 754

Figure 1. The chemical structure of anandamide, N-arachidonylglycine and oleoyl-L-

755

carnitine. The carbon-carbon bonds are coloured pink for anandamide, blue for N-

756

arachidonylglycine and maroon for oleoyl-L-carnitine. The carbon numbers that have

757

cis double bonds are labelled, as well as the number of carbon atoms in each acyl

758

chain.

759 760 761


27


Page 28 of 37

762

Figure 2. The systems studied in this work. The composition of each bilayer is

763

labelled. A–D) The bilayers lacking GlyT2. E–H) the bilayers containing GlyT2.

764

POPC and the bioactive lipids are shown in space-fill representation, with POPC

765

carbon atoms coloured tan and the carbon atoms for anandamide (ANAN), N-

766

arachidonylglycine (NAGL) and oleoyl-L-carnitine (CARN), coloured pink, blue and

767

maroon respectively. Cholesterol is shown as yellow sticks; water is shown as a

768

transparent blue surface; and GlyT2 is represented as cartoon, with its molecular

769

surface shown in transparent grey, its transmembrane helices shown in multiple

770

colours and extracellular loop 4 (EL4) coloured black.

771 772 773 774

Figure 3. Biophysical properties of the bilayers calculated over the last 400 ns of

775

simulations. (A) Interleaflet phosphorus–phosphorus distance for each bilayer, with

776

(solid) and without (transparent) GlyT2. The data are expressed as box plots. (B) Area

777

per POPC lipid for each bilayer, with (solid) and without (transparent) GlyT2. The

778

data are expressed as box plots. (C) and (D) Order parameters for each carbon atom

779

on the POPC acyl chains for the bilayers lacking (C) and containing (D) GlyT2. The

780

plots corresponding to each of the two acyl chains of POPC are labelled. The data are

781

averaged over the simulation time and the three replicates for each system. Note that

782

all data are included in panel B; the data are simply overlapping. The systems were

783

CONT., control bilayer (20 % cholesterol + 80 % POPC); ANAN, anandamide

784

bilayer (5 % anandamide + 20 % cholesterol + 75 % POPC); NAGL, N-

785

arachidonylglycine bilayer (5 % N-arachidonylglycine + 20 % cholesterol + 75 %

786

POPC); and CARN, oleoyl-L-carnitine bilayer (5 % oleoyl-L-carnitine + 20 %

787

cholesterol + 75 % POPC).

788 789 790 791

Figure 4. Locations of the lipids in the bilayers. (A–B) Lipid head group atom

792

number density across the bilayer. The normalised number of atoms at each location

793

across the bilayer is shown, averaged over time (100–500 ns) and the three replicates

794

for each system. Water extends from 0 nm to 5 nm. The atoms chosen to represent the

795

head group of each lipid were: POPC, phosphorus; cholesterol (CLR), oxygen; and


28

Page 29 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


796

bioactive lipid (BIOA), nitrogen. The data for each lipid are labelled and coloured

797

according to the type of bioactive lipid present: CONT., control bilayer (20 %

798

cholesterol + 80 % POPC); ANAN, anandamide bilayer (5 % anandamide + 20 %

799

cholesterol + 75 % POPC); NAGL, N-arachidonylglycine bilayer (5 % N-

800

arachidonylglycine + 20 % cholesterol + 75 % POPC); and CARN, oleoyl-L-carnitine

801

bilayer (5 % oleoyl-L-carnitine + 20 % cholesterol + 75 % POPC). A) Bilayer without

802

GlyT2, with a transparent snapshot from an ANAN bilayer simulation overlaid.

803

Anandamide is shown in pink space fill, POPC is shown as tan space fill and

804

cholesterol is shown as yellow sticks. Water is excluded for clarity. B) Bilayer with

805

GlyT2, with the atom density of GlyT2 shaded grey. C) Anandamide “snorkelled”

806

from the lipid/water interface and moved into the centre of the bilayer (two examples

807

circled in black). GlyT2 is shown in cartoon representation, coloured by helix. A

808

slice-through of the surface of GlyT2 is shown in transparent grey. Anandamide is

809

shown as space-fill in CPK colouring, with magenta carbon atoms. The phosphorus

810

atoms of POPC are shown as purple spheres. POPC, cholesterol, water and ions are

811

hidden for clarity.

812 813 814 815

Figure 5. Average intra-molecular distance for the ends of the bioactive lipids. The

816

data are shown as violin, or “jitter” plots, coloured by lipid for the membranes

817

without (A) and with (B) GlyT2. Averages were taken over 100–500 ns. The number

818

of data points corresponds to the number of lipids, e.g. each anandamide molecule, in

819

each system, for the three replicates. The systems are labelled ANAN, anandamide

820

bilayer (5 % anandamide + 20 % cholesterol + 75 % POPC); NAGL, N-

821

arachidonylglycine bilayer (5 % N-arachidonylglycine + 20 % cholesterol + 75 %

822

POPC); and CARN, oleoyl-L-carnitine bilayer (5 % oleoyl-L-carnitine + 20 %

823

cholesterol + 75 % POPC). The united-atom structures, with the distance vectors and

824

example values for the bioactive lipids are shown in (C). The colours are as in (A) and

825

(B), with the first and last carbon in the distance pairing shown as black spheres.

826 827 828

Figure 6. Binding locations and binding propensity of anandamide (A), N-

829

arachidonylglycine (B) and oleoyl-L-carnitine (C) to GlyT2. GlyT2 is shown in


29


Page 30 of 37

830

cartoon, coloured by transmembrane helix (TM). The binding propensity is shown as

831

a greyscale colour band, with dark bands indicating low binding propensity (greater

832

than 0.001) and white bands indicating 0.1 (i.e. 100 %) binding propensity (i.e. most

833

of the simulation, for all three replicates). Solid rainbow colour on the transmembrane

834

helices and light salmon on the extra- and intracellular regions indicate areas where

835

bioactive lipids never bound, i.e. the binding propensity was 0 %.

836 837 838

Graphical Table of Contents

839

840


30

Page 31 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Graphical Table of Contents 80x42mm (300 x 300 DPI)



Figure 1. The chemical structure of anandamide, N-arachidonylglycine and oleoyl-L-carnitine. The carboncarbon bonds are coloured pink for anandamide, blue for N-arachidonylglycine and maroon for oleoyl-Lcarnitine. The carbon numbers that have cis double bonds are labelled, as well as the number of carbon atoms in each acyl chain. 84x66mm (300 x 300 DPI)


Page 32 of 37

Page 33 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2. The systems studied in this work. The composition of each bilayer is labelled. A–D) The bilayers lacking GlyT2. E–H) the bilayers containing GlyT2. POPC and the bioactive lipids are shown in space-fill representation, with POPC carbon atoms coloured tan and the carbon atoms for anandamide (ANAN), Narachidonylglycine (NAGL) and oleoyl-L-carnitine (CARN), coloured pink, blue and maroon respectively. Cholesterol is shown as yellow sticks; water is shown as a transparent blue surface; and GlyT2 is represented as cartoon, with its molecular surface shown in transparent grey, its transmembrane helices shown in multiple colours and extracellular loop 4 (EL4) coloured black. 84x133mm (300 x 300 DPI)



Figure 3. Biophysical properties of the bilayers calculated over the last 400 ns of simulations. (A) Interleaflet phosphorous–phosphorous distance for each bilayer, with (solid) and without (transparent) GlyT2. The data are expressed as box plots. (B) Area per POPC lipid for each bilayer, with (solid) and without (transparent) GlyT2. The data are expressed as box plots. (C) and (D) Order parameters for each carbon atom on the POPC acyl chains for the bilayers lacking (C) and containing (D) GlyT2. The plots corresponding to each of the two acyl chains of POPC are labelled. The data are averaged over the simulation time and the three replicates for each system. Note that all data are included in panel B; the data are simply overlapping. The systems were CONT., control bilayer (20 % cholesterol + 80 % POPC); ANAN, anandamide bilayer (5 % anandamide + 20 % cholesterol + 75 % POPC); NAGL, N-arachidonylglycine bilayer (5 % Narachidonylglycine + 20 % cholesterol + 75 % POPC); and CARN, oleoyl-L-carnitine bilayer (5 % oleoyl-Lcarnitine + 20 % cholesterol + 75 % POPC).


Page 34 of 37

Page 35 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 4. Locations of the lipids in the bilayers. (A–B) Lipid head group atom number density across the bilayer. The normalised number of atoms at each location across the bilayer is shown, averaged over time (100–500 ns) and the three replicates for each system. Water extends from 0 nm to 5 nm. The atoms chosen to represent the head group of each lipid were: POPC, phosphorus; cholesterol (CLR), oxygen; and bioactive lipid (BIOA), nitrogen. The data for each lipid are labelled and coloured according to the type of bioactive lipid present: CONT., control bilayer (20 % cholesterol + 80 % POPC); ANAN, anandamide bilayer (5 % anandamide + 20 % cholesterol + 75 % POPC); NAGL, N-arachidonylglycine bilayer (5 % Narachidonylglycine + 20 % cholesterol + 75 % POPC); and CARN, oleoyl-L-carnitine bilayer (5 % oleoyl-Lcarnitine + 20 % cholesterol + 75 % POPC). A) Bilayer without GlyT2, with a transparent snapshot from an ANAN bilayer simulation overlaid. Anandamide is shown in pink space fill, POPC is shown as tan space fill and cholesterol is shown as yellow sticks. Water is excluded for clarity. B) Bilayer with GlyT2, with the atom density of GlyT2 shaded grey. C) Anandamide “snorkelled” from the lipid/water interface and moved into the centre of the bilayer (two examples circled in black). GlyT2 is shown in cartoon representation, coloured by helix. A slice-through of the surface of GlyT2 is shown in transparent grey. Anandamide is shown as spacefill in CPK colouring, with magenta carbon atoms. The phosphorus atoms of POPC are shown as purple spheres. POPC, cholesterol, water and ions are hidden for clarity. 2799x2481mm (30 x 30 DPI)



Figure 5. Average intra-molecular distance for the ends of the bioactive lipids. The data are shown as violin, or “jitter” plots, coloured by lipid for the membranes without (A) and with (B) GlyT2. Averages were taken over 100–500 ns. The number of data points corresponds to the number of lipids, e.g. each anandamide molecule, in each system, for the three replicates. The systems are labelled ANAN, anandamide bilayer (5 % anandamide + 20 % cholesterol + 75 % POPC); NAGL, N-arachidonylglycine bilayer (5 % Narachidonylglycine + 20 % cholesterol + 75 % POPC); and CARN, oleoyl-L-carnitine bilayer (5 % oleoyl-Lcarnitine + 20 % cholesterol + 75 % POPC). The united-atom structures, with the distance vectors and example values for the bioactive lipids are shown in (C). The colours are as in (A) and (B), with the first and last carbon in the distance pairing shown as black spheres. 84x88mm (300 x 300 DPI)


Page 36 of 37

Page 37 of 37 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 6. Binding locations and binding propensity of anandamide (A), N-arachidonylglycine (B) and oleoylL-carnitine (C) to GlyT2. GlyT2 is shown in cartoon, coloured by transmembrane helix (TM). The binding propensity is shown as a greyscale colour band, with dark bands indicating low binding propensity (greater than 0.001) and white bands indicating 0.1 (i.e. 100 %) binding propensity (i.e. most of the simulation, for all three replicates). Solid rainbow colour on the transmembrane helices and light salmon on the extra- and intracellular regions indicate areas where bioactive lipids never bound, i.e. the binding propensity was 0 %.


Lipid-based inhibitors act directly on GlyT2 - ACS Chemical

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