Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Selective effect of cell membrane on synaptic neurotransmission


Atomistic molecular dynamics simulations were performed with 13 non-peptidic neurotransmitters (NTs) in three different membrane environments. The results provide compelling evidence that NTs are divided into membrane-binding and membrane-nonbinding molecules. NTs adhere to the postsynaptic membrane surface whenever the ligand-binding sites of their synaptic receptors are buried in the lipid bilayer. In contrast, NTs that have extracellular ligand-binding sites do not have a similar tendency to adhere to the membrane surface. This finding is a seemingly simple yet important addition to the paradigm of neurotransmission, essentially dividing it into membrane-independent and membrane-dependent mechanisms. Moreover, the simulations also indicate that the lipid composition especially in terms of charged lipids can affect the membrane partitioning of NTs. The revised paradigm, highlighting the importance of cell membrane and specific lipids for neurotransmission, should to be of interest to neuroscientists, drug industry and the general public alike.


Neurotransmission regulates a variety of senses and functions such as motivation, memory and muscle contraction. Neurotransmitters (NTs) play a key role in these functions since the signal transmission takes place through the binding of a NT with its specific receptor embedded in the postsynaptic membrane. Understanding the details of NT binding is important given that various diseases emerge if the signaling is impaired.

Currently, NTs are depicted in neurobiology textbooks to travel across the synaptic cleft over a distance of 20–40 nm and to bind to their receptors without interacting with the membrane itself1,2. However, several NT receptors (Figure S1 and Table S1 in the Supplementary Information (SI)) contain ligand-binding sites that are membrane-buried (Table 1), suggesting possible relevance of the cell membrane in the NT binding.

Table 1 The neurotransmitter-membrane association.

Until a few decades ago, membranes were considered as passive participants in cellular processes. Recently, however, lipids and membranes have been shown to be in a central position in numerous cellular functions such as signaling and protein sorting3. The conformation and dynamics as well as the function of various membrane-embedded proteins has been shown to be dependent on the lipid composition surrounding membrane proteins4,5,6. Specific lipids can modulate the stability and function of membrane-embedded proteins by diffusing into specific binding sites on their surfaces7,8. For example, cardiolipins have been suggested to facilitate proton transfers during cytochrome bc1 complex operation9,10,11,12,13 by binding to locations close to the enzyme’s active sites in the mitochondrial membrane9,10,11.

The effect of lipids and cell membranes is not limited to proteins and peptides but the dynamics of ligands and other small molecules is affected, too. For instance, antipsychotic drugs have been shown via numerous biophysical methods to interact strongly with lipid membranes12. Membrane permeability is a feature known to influence bioavailability of drugs and major experimental and theoretical effort has been invested to estimate ligand permeability across membranes13,14. Furthermore, analgesic drugs such as propofol and even NTs have been suggested to produce anesthetic effects by affecting membrane properties such as bilayer thickness15,16. The biological effect is, therefore, not necessarily a result of direct ligand-receptor interaction, but the proteins’ functions can be altered via ligand-induced changes in its membrane environment17. To this end, a growing number of both experimental and computational studies exploring ligand-membrane interactions are emerging18,19,20.

A substantial body of work indicates that some ligands first bind to the membrane surface and then diffuse laterally into the membrane-buried binding sites of their receptors21. In these cases, the direct 3D diffusion of the ligands from the water phase to the receptor’s binding site is transformed into 3D-2D diffusion, which speeds up the binding process by several orders of magnitude21. Despite this, the potentially significant effect that the lipid composition exerts on ligand-receptor entry kinetics in the synapse has been largely ignored in previous studies. For example with ionotropic glutamate receptors (Table S1), valuable pharmacological data can be acquired by concentrating only on their extracellular ligand-binding domains22,23,24,25,26,27. However, when studying for instance acetylcholine entry into the M3 muscarinic acetylcholine receptor, the lipid composition is a factor that should not be overlooked28. Although the positively charged NT is not expected to partition to the cell membrane based on its hydrophilic profile, it is yet able to bind effectively into the membrane-buried binding sites of muscarinic receptors as well as into the extracellular binding sites of acetylcholinesterase and nicotinic acetylcholine receptors28.

Several experimental and computational studies have indicated that the lipid composition in membranes has a role in NT dynamics. The lipid composition has been shown by molecular dynamics (MD) simulations and calorimetry29,30 to affect the NT-membrane dynamics with dopamine. The same result has been shown also for glutamate, acetylcholine, γ-aminobutyric acid (GABA) and glycine using MD simulations, calorimetry and dialysis equilibrium experiments31,32. With serotonin, melatonin and peptidic NT encephalin, attachment to neutral membranes has been also documented by means of neutron scattering33, MD simulations34,35,36 and nuclear magnetic resonance measurements36. In general, the presence of anionic lipids and the zwitterionic state of NTs enhances membrane attachment. Further, determining the role of membrane environment for NT binding in the synapses is clearly relevant given that lipids occupy roughly half of the cellular membrane surface area, while the other half is taken up by various proteins37.

In this work we performed atomistic MD simulations for three lipid bilayer models with 13 non-peptidic NTs and the dopamine precursor L-dopa. The pre-equilibrated lipid membrane models (64 lipids/leaflet; see SI) reproduce experimentally determined local bilayer properties such as the order parameter, membrane thickness and average area per lipid (e.g, ref. 38,); accordingly, the models are suitable for studying NT-membrane interactions that take place at the water-membrane interface.

The first “extracellular” membrane model represents the extracellular leaflet of a synaptic membrane, being composed of dioleoylphosphatidylcholine, sphingomyelin and cholesterol (DOPC/SM/CHOL)37. The second “intracellular” model represents a more polar intracellular leaflet and contains dilinoleicphosphatidylcholine, dilinoleicphosphatidylethanolamine and dilinoleicphosphatidylserine (DLPC/DLPE/DLPS)37. Since the exact contents of postsynaptic membranes are not known, the lipid compositions of these two models follow the lipid contents of typical animal cell membranes. Finally, the third “control” model, containing only DLPC lipids, was used as a less polar control membrane. Altogether, 42 NT-membrane systems were simulated for 200–400 ns each; furthermore, the membrane binding energetics were determined for four individual NTs using the umbrella sampling method.

Based on the MD simulation results the current view of neurotransmission, which does not account for the role of lipids1,2, was revised and a holistic theory highlighting the selective effect of cell membrane on synaptic neurotransmission was formulated. In short, the simulations provide strong evidence that neurotransmission follows either the membrane-independent or the membrane-dependent mechanism and the one chosen by nature depends on the position of the receptor’s ligand-binding site.


As expected, the NTs did not permeate the lipid bilayers; instead they displayed varying degrees of reversible membrane attachment. Catecholamines such as dopamine and norepinephrine, as well as serotonin, melatonin and adenosine, all attached strongly to the lipid bilayers in the NT-membrane simulations (Fig. 1; Table 1). The hydrophobic ring systems were found to be essential for the favorable alignment on the membrane surface. In comparison, small NTs containing charged moieties, such as GABA or glutamate (Fig. 2; Table 1), did not attach to the membranes. Hydrogen bonding was prominent when NTs attached to the models of the intracellular and extracellular leaflets. With the less polar control membrane, hydrophobic/steric attraction was required for close contact. The specific NT-membrane interactions are discussed thoroughly in the SI (Figures S3–S11 and Tables S2–S4).

Figure 1
figure 1

Density profiles for neurotransmitters with membrane buried binding sites.

The density curves indicate that adenosine, epinephrine, melatonin and dopamine attached reversibly to the extracellular leaflet surface and the positively charged acetylcholine and histamine attached to the polar intracellular leaflet. In the bottom right corner, extracellular (red) and intracellular (blue) membrane sides and the ligand-binding site (green circle) are indicated with lines for the structure of the muscarinic acetylcholine receptor (Table S1).

Figure 2
figure 2

Density profiles for neurotransmitters with extracellular binding sites.

The density curves indicate that aspartate, glutamate, serine, glycine, GABA and acetylcholine do not attach to the extracellular leaflet. For serotonin, there exist receptors with membrane-buried binding sites and extracellular binding sites (Table 1), but the NT attached to all membranes. Also shown (on the right, bottom) are the extracellular binding sites of the GluA2 glutamate receptor and the 5HT-3 serotonin receptor (Table S1).

The simulations indicate that NTs can be divided into membrane-binding (Fig. 1) and membrane-nonbinding groups (Fig. 2). The MD simulations (Table 1), free energy computations (Fig. 3; Table S5) and log P (the octanol/water partition coefficient) values of the NTs (Fig. 4; Table S3) support this view. Although octanol clearly cannot depict all of the physical properties and the diversity of an actual lipid bilayer, the log P values corroborate the simulation results (Table S3). What is more, this categorization of NTs corresponds to the positioning of the ligand-binding sites of their receptors in relation to the postsynaptic membrane (Tables 1 and S1). As a rule of thumb, if a NT attached to a membrane, then its ligand-binding site is membrane-buried. In contrast, whenever the ligand-binding site is extracellular, then the NT did not attach to the membrane (Table 1).

Figure 3
figure 3

Profiles of free energy obtained from umbrella sampling calculations.

The profiles indicate that norepinephrine, dopamine and serotonin adhere to the membrane surfaces, while glutamate does not. Both the 2D structures of NTs and the 3D receptor structures are shown in the figures. For comparison, the NT-membrane reversible attachment is observed in the end of the extracellular leaflet simulations, too.

Figure 4
figure 4

Lipophilicity classifies neurotransmitters into membrane-nonbinding and membrane-binding categories.

Based on the divergent behavior observed in the simulations, neurotransmission can be split into two different mechanisms (Fig. 5). The classical membrane-independent mechanism (Fig. 5a), shown in neurobiology textbooks, dictates that NTs, whose receptors’ ligand-binding sites are extracellular, travel across the synaptic cleft without adhering to the membrane. Thus, these NTs enter their binding site directly from the bulk water. The membrane-dependent mechanism (Fig. 5b) proposed in this work dictates that NTs, whose binding sites are located in the transmembrane part of the receptor, reversibly attach first to the membrane and then diffuse along the membrane surface to the membrane-buried binding site.

Figure 5
figure 5

Neurotransmission models.

(a) Classical membrane-independent mechanism: (1) neurotransmitter release; (2) random diffusion; and (3) binding into the extracellular ligand-binding sites of the receptors. (b) Membrane-dependent mechanism: (1) neurotransmitter release; (2) aggregation to the membrane; and (3) lateral diffusion followed by binding into the membrane-buried ligand-binding sites.


Although the lipid types residing in synapses are known, the exact lipid compositions of specific synapses or, more importantly, their extracellular and intracellular leaflets are yet to be characterized39,40,41,42. Keeping this in mind, let us consider the perspectives emerging from the simulation data for specific lipid types’ role in the context of NT binding into proteins embedded at the postsynaptic membrane.

The ligand-binding sites of G protein-coupled receptors are typically membrane-buried (Table 1) and their representative NTs follow the membrane-dependent mechanism (Fig. 5b). Adenosine, epinephrine, norepinephrine, dopamine, serotonin and melatonin were found to attach reversibly predominantly to the extracellular and intracellular leaflets in the MD simulations (Table 1), stressing the preference for lipid binding. The positively charged histamines attached preferentially to the DLPS-containing intracellular leaflet instead of the extracellular membrane surface (Table 1; Figures S8,S9), which suggests that negatively charged lipids could be more abundant in synapses housing histamine receptors. For serotonin, there exist several 5-HT receptors with membrane-buried binding sites but also 5-HT3 ion channel receptors with extracellular ligand-binding sites (Figs 1,2, S6 and S7; Table 1). As serotonin was found to adhere to all three membrane models, assuring sufficient amount of NT binding into the extracellular binding sites of 5-HT3 receptors might require for example relatively high serotonin levels.

The ligand-gated ion channels such as ionotropic glutamate receptors have extracellular ligand-binding sites. Accordingly, their representative NTs follow the membrane-independent mechanism (Fig. 5a). GABA, glycine, serine, glutamate and aspartate prefer the bulk water to the extracellular leaflet (Table 1). Interestingly, in the cases of serine and acetylcholine, the polar intracellular leaflet was preferred to the bulk water (Figures S8,S9). The fact that acetylcholine attaches to the intracellular surface and not to the extracellular leaflet, provides an explanation for how muscarinic acetylcholine receptors can have membrane-buried ligand-binding sites while nicotinic acetylcholine receptors have extracellular binding sites (Table 1). Namely, those synapses or membrane regions populated by muscarinic receptors could yet again have more negatively charged lipids attracting the positively charged acetylcholine molecules than those populated by nicotinic receptors. Altogether, the results suggest that specific lipids and charged types in particular, may modulate the association of NTs to their host membranes and hence the binding to their receptors.

The above described results suggest that specific lipid types and the lipid composition in general could have an important role in synaptic neurotransmission. While the concentrations of negatively charged glycolipids are usually small in typical animal cells, their levels are known to be higher in neurons39,40. Thus, these anionic lipids at the extracellular leaflet of the postsynaptic membrane could facilitate the membrane attachment of positively charged histamine or acetylcholine molecules. While the effect of glycolipids was not addressed in this work, the simulations indicate that charged lipids (here DLPS) do affect the partitioning of NTs (Table 1).

Tightly regulated lipid composition differences between synapses could ensure that acetylcholine can bind into both membrane-buried and extracellular ligand-binding sites (Table 1; Figures S8,S9). In fact, the lipid composition may also be an important factor in neurological diseases and/or their diagnostics. Post mortem studies have indicated changes in the lipid composition with schizophrenia, Parkinson’s disease and Alzheimer’s disease patients43,44,45,46. The membrane reversible attachment of a NT could be either enhanced or weakened, if the membrane became less or more charged due to changes in lipid composition. Although the absolute NT levels would not necessarily be affected by these changes, an imbalance in NT-membrane interactions could contribute to disease states such as depression.

Synaptic receptors are not the only membrane-embedded proteins that interact with NTs at the postsynaptic membrane. The timely removal of NTs from the synaptic cleft is vital and, for example, if glutamate transport is obstructed, neurotoxic effects follow47. In this regard, the NT-membrane simulations shed new light also on NT transport across the postsynaptic membrane following neurotransmission.

It may seem contradictory, but all NTs eventually bind into the membrane-buried ligand-binding sites of their transporters (Figure S12a,b). The Na+ gradient across the membrane powers the Na+/NT co-transport. In addition, the positive ion(s) at the ligand-binding sites form ionic bonds with NTs that have carboxylate groups (shown for leucine in Figure S12b)48. With monoamines such as serotonin, which partition readily to the membrane (Table 1), an aspartate side chain acts as an intrinsic ligand which neutralizes the positive charge48. In the glutamate transporter the Na+ binding takes place prior to the NT entry49. Thus, the positively charged ions inside the membrane-buried ligand-binding sites of NT transporters could act as sinks that attract negatively charged NTs such as glutamate and aspartate.

This sink hypothesis is not valid for neutral ligands, but all non-peptidic NTs were somewhat attracted to the polar intracellular membrane in the simulations, serine even preferred it over the bulk water (Figures S10,S11; Table 1). Conceivably, the NT transporters could be surrounded by high concentrations of anionic lipids such as glycolipids. Indeed, lipid composition differences have been suggested to affect, for example, glutamate uptake50. Notably, the removal of acetylcholine from the synaptic cleft is different as the positively charged NT binds into the extracellular ligand-binding site of acetylcholinesterase (Figure S12c) and the reaction products are transported separately into the cytoplasm.

In a broader context, the simulations suggest a strong interplay between lipids, membrane proteins and NTs and coevolution at the postsynaptic membrane. The NTs not only have to pass the on/off test of the membrane and match the properties of their receptors’ active sites in the synapse, but the membrane effect likely applies to the intracellular NT dynamics as well. However, it is important to recognize that drugs or natural compounds such as toxins do not necessarily follow the same logic as the NTs regarding the membrane partitioning. For example, potent acetylcholinesterase inhibitors can be very lipophilic despite the fact that the enzyme’s active site is extracellular (Table S6). This discrepancy highlights the extraordinary importance of fast and coordinated NT kinetics for neurotransmission. Despite this, avoiding ligand-membrane mismatches during drug development should reduce off-target effects and increase efficacy with a multitude of target proteins.

In conclusion, the atomistic MD simulations suggest that non-peptidic NTs are divided into membrane-binding and membrane-nonbinding categories that in turn correspond to the positioning of their receptor’s ligand-binding sites in relation to the postsynaptic membrane (Table 1). Hence, neurotransmission follows either the membrane-dependent or the membrane-independent mechanism (Fig. 5). Despite the apparent simplicity of this finding, it represents a fundamentally different outlook on neurotransmission with far-reaching ramifications. The selective effect of the membrane ensures a more coordinated response to NT release than random diffusion could accomplish alone. By controlling the lipid composition and paying attention to the extracellular leaflet in particular in different synapses in the nervous system, NTs such as acetylcholine could bind efficiently into membrane proteins with both extracellular and membrane-buried ligand-binding sites. Moreover, anionic lipids promote the membrane partitioning of all studied non-peptidic NTs in the simulations (Table 1) and, thus, the presence of negatively charged lipids in the synapse could be a requirement for efficient removal of NTs from the synaptic cleft.


The atomistic molecular dynamics (MD) simulations were performed with GROMACS 4.551 using the OPLS-AA force field38,52,53. The MD simulation protocol was presented in a previous study38. Free energy curves were calculated using umbrella sampling54 together with the Weighted Histogram Analysis Method55. VMD1.9.1 was used to draw the 3D structures of receptors56. Altogether, 42 NT-membrane systems were simulated, each for 200–300 ns (total simulation time being ~12 μs). The computational methods are explained in detail in SI.

Additional Information

How to cite this article: Postila, P. A. et al. Selective effect of cell membrane on synaptic neurotransmission. Sci. Rep. 6, 19345; doi: 10.1038/srep19345 (2016).


  • Binder, M. D., Hirokawa, N. & Windhorst, U. Encyclopedia of Neuroscience. (SpringerVerlag, 2009).

  • Squire, L. R. Fundamental neuroscience, 4th ed. (Elsevier/Academic Press, 2013).

  • Coskun, Ü. & Simons, K. Cell membranes: the lipid perspective. Structure. 19, 1543–1548 (2011).

    CAS  Article  PubMed  Google Scholar 

  • Coskun, Ü., Grzybek, M., Drechsel, D. & Simons, K. Regulation of human EGF receptor by lipids. Proc. Natl. Acad. Sci. USA. 108, 9044–9048 (2011).

    CAS  Article  ADS  PubMed  PubMed Central  Google Scholar 

  • Sandvig, K., Bergan, J., Kavaliauskiene, S. & Skotland, T. Lipid requirements for entry of protein toxins into cells. Prog. Lipid Res. 54, 1–13 (2014).

    CAS  Article  PubMed  Google Scholar 

  • Smith, A. W. Lipid-Protein interactions in biological membranes: a dynamic perspective. Biochim. Biophys. Acta. 1818, 172–177 (2012).

    CAS  Article  PubMed  Google Scholar 

  • Soubias, O. & Gawrisch, K. The role of the lipid matrix for structure and function of the GPCR rhodopsin. Biochim. Biophys. Acta. 1818, 234–240 (2012).

    CAS  Article  PubMed  Google Scholar 

  • Róg, T. & Vattulainen, I. Cholesterol, sphingolipids and glycolipids: what do we know about their role in raft-like membranes? Chem. Phys. Lipids. 184, 82–104 (2014).

    Article  CAS  PubMed  Google Scholar 

  • Paradies, G., Paradies, V., Benedictis, V., de Ruggiero, F. M. & Petrosillo, G. Functional role of cardiolipin in mitochondrial bioenergetics. Biochim. Biophys. Acta. 1837, 408–417 (2014).

    CAS  Article  PubMed  Google Scholar 

  • Hunte, C. Specific protein-lipid interactions in membrane proteins. Biochem. Soc. Transactions. 33, 938–942 (2005).

    CAS  Article  Google Scholar 

  • Pöyry, S., Cramariuc, O., Postila, P. A., Kaszuba, K., Sarewicz, M., Osyczka, A., Vatulainen, I. & Róg, T. Atomistic simulations indicate cardiolipin to have an integral role in the structure of the cytochrome bc1 complex. Biochim. Biophys. Acta. 1827, 769–778 (2013).

    Article  CAS  PubMed  Google Scholar 

  • Alves, I., Staneva, G., Tessier, C., Salgado, G. F. & Nuss, P. The interaction of antipsychotic drugs with lipids and subsequent lipid reorganization investigated using biophysical methods. Biochim. Biophys. Acta. 1808, 2009–2018 (2011).

    CAS  Article  PubMed  Google Scholar 

  • Swift, R. V. & Amaro, R. E. Modeling the pharmacodynamics of passive membrane permeability. J. Comput. Aided Mol. Des. 25, 1007–1017 (2011).

    CAS  Article  ADS  PubMed  PubMed Central  Google Scholar 

  • Swift, R. V. & Amaro, R. E. Back to the future: can physical models of passive membrane permeability help reduce drug candidate attrition and move us beyond QSPR? Chem. Biol. Drug Des. 81, 61–71 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Hansen, A. H., Sørensen, K. T., Mathieu, R., Serer, A., Duelund, L., Khandelia, H., Hansen, P. L. & Simonsen, A. C. Propofol modulates the lipid phase transition and localizes near the headgroup of membranes. Chem. Phys. Lipids. 175–176, 84–91 (2013).

    Article  CAS  PubMed  Google Scholar 

  • Cantor, R. S. Receptor desensitization by neurotransmitters in membranes: are neurotransmitters the endogenous anesthetics? Biochemistry. 42, 11891–11897 (2003).

    CAS  Article  PubMed  Google Scholar 

  • Jerabek, H., Pabst, G., Rappolt, M. & Stockner, T. Membrane-Mediated Effect on ion channels induced by the anesthetic drug ketamine. J. Am. Chem. Soc. 132, 7990–7997 (2010).

    CAS  Article  PubMed  Google Scholar 

  • Kopeć, W., Telenius, J. & Khandelia, H. Molecular dynamics simulations of the interactions of medicinal plant extracts and drugs with lipid bilayer membranes. FEBS J. 280, 2785–2805 (2013).

    Article  CAS  PubMed  Google Scholar 

  • Lucio, M., Lima, J. & Reis, S. Drug-membrane Interactions: Significance for Medicinal Chemistr in Ideas in Chemistry and Molecular Sciences. Where Chemistry Meets Life. (ed. Pignataro, B. ) 1795–1809 (Wiley-VCH Verlag, 2010).

  • Pignatello, R., Musumeci, T., Basile, L., Carbone, C. & Puglisi, G. Biomembrane models and drug-biomembrane interaction studies: involvement in drug design and development. J. Pharm. Bioallied Sci. 3, 4–14 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Vauquelin, G. & Packeu, A. Ligands, their receptors and … plasma membranes. Mol. Cellular Endocrino. 311, 1–10 (2009).

    CAS  Article  Google Scholar 

  • Lash, L. L., Sanders, J. M., Akiyama, N., Shoji, M., Postila, P., Pentikäinen, O. T., Sasaki, M., Sakai, R. & Swanson, G. T. Novel analogs and stereoisomers of the marine toxin neodysiherbaine with specificity for kainate receptors. J. Pharmaco. Exp. Therapeutics. 324, 484–496 (2008).

    CAS  Article  Google Scholar 

  • Frydenvang, K., Lash, L. L., Naur, P., Postila, P. A., Pickering, D. S., Smith, C. M., Gajhede, M., Sasaki, M., Sakai, R., Pentikaïnen, O. T., Swanson, G. T. & Kastrup, J. S. Full Domain closure of the ligand-binding core of the ionotropic glutamate receptor iGluR5 induced by the high affinity agonist dysiherbaine and the functional antagonist 8,9-dideoxyneodysiherbaine. J. Biol. Chem. 284, 14219–14229 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Lash-Van Wyhe, L. L., Postila P. A., Tsubone, K., Sasaki, M., Pentikäinen, O. T., Sakai, R. & Swanson, G. T. Pharmacological activity of C10-substituted analogs of the high-affinity kainate receptor agonist dysiherbaine. Neuropharmacology. 58, 640–649 (2010).

    Article  CAS  PubMed  Google Scholar 

  • Postila, P. A., Swanson, G. T. & Pentikäinen, O. T. Exploring kainate receptor pharmacology using molecular dynamics simulations. Neuropharmacology. 58, 515–527 (2010).

    CAS  Article  PubMed  Google Scholar 

  • Postila, P. A., Ylilauri, M. & Pentikäinen, O. T. Full and partial agonism of ionotropic glutamate receptors indicated by molecular dynamics simulations. J. Chem. Inf. Model. 51, 1037–1047 (2011).

    CAS  Article  PubMed  Google Scholar 

  • Ylilauri, M. & Pentikäinen, O. T. Structural mechanism of N-methyl-D-aspartate receptor type 1 partial agonism. PLoS ONE, 7, e47604 (2012).

    CAS  Article  ADS  PubMed  PubMed Central  Google Scholar 

  • Kruse, A. C., Hu, J., Pan, A. C., Arlow, D. H., Rosenbaum, D. M., Rosemond, E., Green, H. F., Liu, T., Chae, P. S., Dror, R. O., Shaw, D. E., Weis, W. I., Wess, J. & Kobilka, B. K. Structure and dynamics of the M3 muscarinic acetylcholine receptor. Nature. 482, 552–556 (2012).

    CAS  Article  ADS  PubMed  PubMed Central  Google Scholar 

  • Orłowski, A., Grzybek, M., Bunker, A., Pasenkiewicz-Gierula, M., Vattulainen, I., Männistö, P. T. & Róg, T. Strong preferences of dopamine and l-dopa towards lipid head group: importance of lipid composition and implication for neurotransmitter metabolism. J. Neurochem. 122, 681–690 (2012).

    Article  CAS  PubMed  Google Scholar 

  • Jodko-Piorecka, K. & Litwinienko, G. First experimental evidence of dopamine interactions with negatively charged model biomembranes. ACS Chem. Neurosci. 4, 1114–1122 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Wang, C., Ye, F., Velardez, G. F., Valardez, G. F., Peters, G. H. & Westh, P. Affinity of four polar neurotransmitters for lipid bilayer membranes. J. Phys. Chem. B. 115, 196–203 (2011).

    CAS  Article  PubMed  Google Scholar 

  • Peters, G. H., Werge, M., Elf-Lind, M. N., Madsen, J. J., Velardez, G. F. & Westh, P. Interaction of neurotransmitters with a phospholipid bilayer: a molecular dynamics study. Chem. Phys. Lipids. 184, 7–17 (2014).

    CAS  Article  PubMed  Google Scholar 

  • Peters, G. H., Wang, C., Cruys-Bagger, N., Velardez, G. F., Madsen, J. J. & Westh, P. Binding of serotonin to lipid membranes. J. Am. Chem. Soc. 135, 2164–2171 (2013).

    CAS  Article  PubMed  Google Scholar 

  • Drolle, E., Kučerka, N., Hoopes, M. I., Choi, Y., Katsaras, J., Karttunen, M. & Leonenko, Z. Effect of melatonin and cholesterol on the structure of DOPC and DPPC membranes. Biochim. Biophys. Acta. 1828, 2247–2254 (2013).

    CAS  Article  PubMed  Google Scholar 

  • Choi, Y., Attwood, S. J., Hoopes, M. I., Drolle, E., Karttunen, M. & Leonenko, Z. Melatonin directly interacts with cholesterol and alleviates cholesterol effects in dipalmitoylphosphatidylcholine monolayers. Soft Matter 10, 206–213 (2014).

    CAS  Article  ADS  PubMed  Google Scholar 

  • Chandrasekhar, I., van Gunsteren, W. F., Zandomeneghi, G., Williamson, P. T. F. & Meier, B. H. Orientation and conformational preference of leucine-enkephalin at the surface of a hydrated dimyristoylphosphatidylcholine bilayer: NMR and MD simulation. J. Am. Chem. Soc. 128, 159–170 (2006).

    CAS  Article  PubMed  Google Scholar 

  • van Meer, G., Voelker, D. R. & Feigenson, G. W. Membrane lipids: where they are and how they behave. Nat. Rev. Mol. Cell Biol. 9, 112–124 (2008).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Maciejewski, A., Pasenkiewicz-Gierula, M., Cramariuc, O., Vattulainen, I. & Róg, T. Refined OPLS all-atom force field for saturated phosphatidylcholine bilayers at full hydration. J. Phys. Chem. B. 118, 4571–4581 (2014).

    CAS  Article  PubMed  Google Scholar 

  • Stoffel, W. & Bosio, A. Myelin glycolipids and their functions. Cur. Opin. Neurobiol. 7, 654–661 (1997).

    CAS  Article  Google Scholar 

  • Degroote, S., Wolthoorn, J. & van Meer, G. The cell biology of glycosphingolipids. Seminars Cell. Develop. Biol. 15, 375–387 (2004).

    CAS  Article  Google Scholar 

  • Lajtha, A., Tettamanti, G. & Goracci, G. Handbook of Neurochemistry and Molecular Neurobiology. (Springer, 2010).

  • Cotman, C., Blank, M. L., Moehl, A. & Snyder, F. Lipid composition of synaptic plasma membranes isolated from rat brain by zonal centrifugation. Biochemistry. 9, 4606–4612 (1969).

    Article  Google Scholar 

  • Du Bois, T. M., Deng, C. & Huang, X. Membrane phospholipid composition, alterations in neurotransmitter systems and schizophrenia. Prog. Neuropsychopharmacol. Biol. Psychiatry. 29, 878–888 (2005).

    CAS  Article  PubMed  Google Scholar 

  • Fabelo, N., Martín, V., Santpere, G., Marín, R., Torrent, L., Ferrer, I. & Díaz, M. Severe alterations in lipid composition of frontal cortex lipid rafts from Parkinson’s disease and incidental Parkinson’s disease. Mol. Med. 17, 1107–1118 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Martín, V., Fabelo, N., Santpere, G., Puig, B., Marín, R., Ferrer, I. & Díaz, M. Lipid alterations in lipid rafts from Alzheimer’s disease human brain cortex. J. Alzheimers Dis. 19, 489–502 (2010).

    Article  CAS  PubMed  Google Scholar 

  • Tachiki, K. H., Buckman, T. D., Eiduson, S., Kling, A. S. & Hullett, J. Phosphatidylserine inhibition of monoamine oxidase in platelets of schizophrenics. Biol. Psychiatry. 21, 59–68 (1986).

    CAS  Article  PubMed  Google Scholar 

  • Lau, A. & Tymianski, M. Glutamate receptors, neurotoxicity and neurodegeneration. Pflügers Archiv Europ. J. Physio. 460, 525–542 (2010).

    CAS  Article  Google Scholar 

  • Yamashita, A., Singh, S. K., Kawate, T., Jin, Y. & Gouaux, E. Crystal structure of a bacterial homologue of Na+/Cl–dependent neurotransmitter transporters. Nature. 437, 215–223 (2005).

    CAS  Article  ADS  PubMed  Google Scholar 

  • Focke, P. J., Wang, X. & Larsson, H. P. Neurotransmitter transporters: structure meets function. Structure. 21, 694–705 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Danbolt, N. C. Glutamate uptake. Prog. Neurobiol. 65, 1–105 (2001).

    CAS  Article  PubMed  Google Scholar 

  • Hess, B., Kutzner, C., van der Spoel D. & Lindahl, E. GROMACS 4: algorithms for highly efficient, load-balanced and scalable molecular simulation. J. Chem. Theory Comput. 4, 435–447 (2008).

    CAS  Article  PubMed  Google Scholar 

  • Kaminski, G. A., Friesner, R. A., Tirado-Rives, J. & Jorgensen, W. L. Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J. Phys. Chem. B. 105, 6474–6487 (2001).

    CAS  Article  Google Scholar 

  • Kulig, W., Pasenkiewicz-Gierula, M. & Róg, T. Topologies, structures and parameter files for lipid simulations in GROMACS with the OPLS-aa force field: DPPC, POPC, DOPC, PEPC and cholesterol. Data in Brief. 5, 333–336 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  • Torrie, G. M. & Valleau, J. P. Monte Carlo free energy estimates using non-boltzmann sampling: application to the sub-critical Lennard-Jones fluid. Chem. Phys. Letters. 28, 578–581 (1974).

    CAS  Article  ADS  Google Scholar 

  • Hub, J. S., de Groot, B. L. & van der Spoel, D. g_wham — a free weighted histogram analysis implementation including robust error and autocorrelation estimates. J. Chem. Theory. Comput. 6, 3713–3720 (2010).

    CAS  Article  Google Scholar 

  • Humphrey, W., Dalke, A. & Schulten, K. VMD: Visual molecular dynamics. J. Mol. Graph. 14, 33-8, 27–8 (1996).

    Article  Google Scholar 

Download references


The authors wish to thank Robert Swift, Jeffrey Wagner, Hector Martinez-Seara and Adam Orlowski for valuable discussions. Computational resources were provided by CSC – IT Centre for Science (Espoo, Finland). The Academy of Finland (TR, IV and PAP; Center of Excellence in Biomembrane Research), the Paulo Foundation (PAP) and the European Research Council (IV, TR; Advanced Grant project CROWDED-PRO-LIPIDS) are acknowledged for financial support.

Author information

Authors and Affiliations



T.R., I.V. and P.A.P. designed simulations and the analysis program. P.A.P. performed simulations and data analysis. All authors participated in the writing of the article.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Electronic supplementary material

Rights and permissions

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Postila, P., Vattulainen, I. & Róg, T. Selective effect of cell membrane on synaptic neurotransmission. Sci Rep 6, 19345 (2016).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing