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Interactions of peripheral proteins with model membranes as viewed by molecular dynamics simulations Antreas C. Kalli*1 and Mark S. P. Sansom* *Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, U.K.
Biochemical Society Transactions
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Abstract Many cellular signalling and related events are triggered by the association of peripheral proteins with anionic lipids in the cell membrane (e.g. phosphatidylinositol phosphates or PIPs). This association frequently occurs via lipid-binding modules, e.g. pleckstrin homology (PH), C2 and four-point-one, ezrin, radixin, moesin (FERM) domains, present in peripheral and cytosolic proteins. Multiscale simulation approaches that combine coarse-grained and atomistic MD simulations may now be applied with confidence to investigate the molecular mechanisms of the association of peripheral proteins with model bilayers. Comparisons with experimental data indicate that such simulations can predict specific peripheral protein–lipid interactions. We discuss the application of multiscale MD simulation and related approaches to investigate the association of peripheral proteins which contain PH, C2 or FERM-binding modules with lipid bilayers of differing phospholipid composition, including bilayers containing multiple PIP molecules.
Introduction Transmission of signals across the plasma membrane is central to cellular function [1]. The mechanisms whereby such transmission can be achieved in many cases involve the reversible binding of peripheral membrane proteins to the cell membrane in order to, e.g., modulate the formation of protein–protein or protein–lipid complexes [2]. Localization and binding of peripheral proteins to the cell membrane may be controlled by lipid-binding modules, e.g. pleckstrin homology (PH), C2 and four-point-one, ezrin, radixin, moesin (FERM) domains, that are present in many peripheral proteins. We focus on how computational approaches can be used to elucidate the molecular details of the interactions of such lipid-binding modules with lipid bilayer models of complex cell membranes. Cell membranes are dynamic entities containing diverse lipid types in complex and time-dependent spatial arrangements [3]. Anionic lipids such as phosphatidylinositol phosphates (PIPs), present at a concentration of 5–15 % [4] in the plasma membrane, play a crucial role to the localization of different types of peripheral proteins. PIPs have an inositol headgroup which can be phosphorylated at different positions alongside acyl chains with four double bonds, which may result in a looser packing of PIPs Key words: four-point-one, ezrin, radixin, moesin (FERM), lipid bilayer, molecular dynamics simulation, phosphatase and tensin homologue deleted on chromosome 10 (PTEN), phosphatidylinositol phosphate (PIP), pleckstrin homology (PH). Abbreviations: CG-MD, coarse-grained MD; Ci-VSP, Ciona intestinalis voltage-sensitive phosphatase; FERM, four-point-one, ezrin, radixin, moesin; GRP1, general receptor for phosphoinositides 1; PH, pleckstrin homology; PIP, phosphatidylinositol phosphate; PIP2 , phosphatidylinositol 4,5-bisphosphate; PIP3 , phosphatidylinositol 3,4,5-trisphosphate; PKC, protein kinase C; PLC, phospholipase C; PS, phosphatidylserine; PTEN, phosphatase and tensin homologue deleted on chromosome 10. 1 To whom correspondence should be addressed (email [email protected]).
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within the membrane [5]. It is possible that clustering of PIP molecules may provide a scaffold for localization of peripheral protein to the cell membrane. Such PIP clustering may also be stabilized or enhanced by peripheral proteins [6]. The presence of PIPs and other anionic lipids (e.g. phosphatidylserine, PS) creates an overall negative electrostatic field, which is likely to facilitate the initial association of a peripheral protein with the inner membrane surface [7]. This initial encounter may be followed by formation of more specific interactions (e.g. hydrogen bonds) and a degree of penetration of parts of a peripheral protein into the hydrophobic core of the membrane [8]. The association of a peripheral protein with the membrane depends on both the properties of the peripheral protein and the properties of the membrane. Biophysical [9] and structural [10] techniques provide valuable insights into the underlying interactions of peripheral proteins with lipid bilayers. However, a complete understanding of the dynamic molecular events underlying lipid-binding domains with membranes remains elusive. Molecular simulations may be used to provide a ‘computational microscope’, enabling us to probe the mechanistic details of the binding of a peripheral protein to a membrane [11–14].
Simulation approaches to peripheral membrane proteins In the context of membrane biology, MD simulations have focused mainly on integral membrane proteins, both to understand their conformational dynamics and to assess their interactions with the surrounding lipids [15]. Simulations of the interactions of peripheral proteins with a membrane have in some ways proved more challenging because of the Biochem. Soc. Trans. (2014) 42, 1418–1424; doi:10.1042/BST20140144
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need for extended simulation timescales in order to address the coupled dynamic events underlying such interactions. These include (i) diffusional encounter of a protein with the membrane, (ii) diffusional redistribution of lipids within a bilayer in response to the encounter, (iii) conformational changes within the protein, and (iv) penetration of parts of the protein into the hydrophobic core of the bilayer. In the last few years, atomistic MD simulations have been used to study the interactions of, e.g., BAR [16], C2 [17], FYVE [18], Phox homology (PX) [19] and PH [20,21] domains with lipid bilayers and with membrane-mimetic models [22,23]. Bioinformatics and related approaches have also highlighted the key role of electrostatic interactions in the formation of peripheral protein–membrane complexes [7,24]. These and other simulation studies have provided detailed models of both the specific and non-specific interactions of key recognition domains with membrane lipids. However, many molecular simulation approaches require a degree of prior knowledge of the nature of the membrane-anchoring region of the protein and/or of the orientation and position of the protein relative to the lipid bilayer surface [25]. These limitations may be addressed by using lower-resolution simulation methodologies, e.g. coarse-grained MD (CGMD) simulations [26,27]. In the CG-MD approach, both the protein and the lipids are simplified by grouping together small numbers (typically four or five) of atoms into coarse-grained particles. This simplification enables longer timescales and larger, more complex systems to be addressed [28,29]. However, it introduces a degree of approximation. The use of a multiscale approach, in which initial lower-resolution CG-MD simulations are combined with subsequent atomistic simulations, helps to address such limitations. This may be viewed as a process of zooming in one’s computational microscope as a simulation of protein– membrane interactions proceeds. In the following sections, we discuss some examples of how such multiscale MD simulations have been used to study three important and abundant lipid-binding modules, namely PH, C2 and FERM domains.
PH domains PH domains contain approximately 100 amino acids in an antiparallel β-sheet architecture followed by one or two αhelices. PH domains form a highly structurally conserved family of proteins, but with considerable sequence diversity. The low sequence similarity between different PH domains correlates with differences in their specificity for PIPs [30]. Early atomistic simulation studies showed that the presence of phosphatidylinositol 4,5-bisphosphate (PIP2 ) molecules in a zwitterionic phosphatidylcholine bilayer enhanced the association of the phospholipase C-δ1 (PLCδ1) PH domain with the bilayer [20]. Han et al. [31] used CG-MD simulations to suggest a mechanism for the association of the PLCβ2 PH domain with model bilayers. MD simulations combined with NMR and monolayer penetration experiments on general receptor for phosphoinositides 1 (GRP1) have shown
that specific electrostatic interactions between the GRP1 PH domain and a phosphatidylinositol 3,4,5-trisphosphate (PIP3 ) molecule are combined with non-specific interactions between flexible hydrophobic loop regions of the PH domain and surrounding lipids in the bilayer [21]. Recent multiscale MD simulations have examined the association of PH domains from the kindlin family of proteins with PIP-containing bilayers. These studies revealed that the kindlin PH isoforms associate with the PIP2 and PIP3 molecules in the membrane via a positively charged loop region (A.C. Kalli and M.S.P. Sansom unpublished work) (Figure 1). In silico mutations of positively charged residues on this loop perturb the orientation of the PH domains relative to the lipid bilayer. Interaction of kindlin PH domains with the negatively charged lipid headgroups results in the clustering of PIP molecules in the (inner) leaflet of the bilayer adjacent to the protein. In addition, MD simulations and molecular docking have suggested that disruption of a salt bridge in the kindlin-1 PH-binding pocket may be needed before PIP3 binding [32]. Overall, these simulation studies suggest that PH domains associate with the membrane via a multistep process involving both specific interactions with the PIP molecules and non-specific interactions with the bilayer.
C2 domains and PTEN C2 domains also possess an antiparallel β-sheet architecture, with variable loops connecting the β-sheets [33,34]. C2 domains can associate with the membrane in either a Ca2 + dependent [e.g. the protein kinase C (PKC) C2 domain] or a Ca2 + -independent manner, e.g. the phosphatase and tensin homologue deleted on chromosome 10 (PTEN) C2 domain [35]. Both types of C2 domains have been shown to interact with anionic lipids with different specificities and/or to coordinate interactions with multiple lipid molecules [36–38]. Atomistic simulations of the cytoplasmic phospholipase A2 (cPLA2 ) C2 domain revealed specific interactions of the loop regions of the C2 domain with the lipids [17]. MD simulations of the PKCα C2 domain combined with experimental studies suggested that in the presence of PIP2 molecules the C2 domain was tilted away from the bilayer, in good agreement with EPR spectroscopic data [39]. Computational studies of the PKCα C2 domain also suggested that Ca2 + -dependent PS binding is needed for the formation of the PKCα C2– membrane complex [40]. A biomedically important example of the C2–membrane interaction is seen in the case of PTEN, a cytosolic enzyme which catalyses dephosphorylation of PIP3 to PIP2 [41,42]. Structural modelling of a PIP3 molecule in the PTEN catalytic site combined with multiscale simulations of the PTEN– PIP3 complex [43] demonstrated that PTEN is located on the lipid–water interface with the loop regions of the PTEN C2 domain, interacting with the bilayer. Atomistic simulations using an extended model of PTEN showed that the PTEN C2 domain associates strongly with PS lipids, although also suggesting that regulatory conformational changes of C The
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Figure 1 Association of the PH domains of the kindlin family of proteins with model membranes (A) Snapshots from a simulation of the kindlin-1 PH domain with a POPC/POPS/PIP2 bilayer at 0, 0.8 and 1.5 μs. The lipid headgroups are shown as grey spheres and the lipid tails are in cyan. (B) Mean distance as a function of time between the centres of mass of the kindlin-1 PH domain and the centre of the bilayer for three different membrane models: POPC, black; POPC/POPS, red; and POPC/POPS/PIP2 , green. (C) Model of the kindlin-1 PH domain bound to a PIP2 -containing bilayer derived from multiscale simulations. The PH domain is shown in orange. POPC and POPS lipid molecules are shown in grey. PIP2 molecules are shown in the bond format to highlight their headgroups. POPC, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine; POPS, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine.
the PTEN C-terminal tail in the membrane-bound and membrane-unbound states may occur [44]. Subsequent multiscale MD simulation studies of the PTEN focused on the mechanism of protein–membrane encounter and recognition. Simulations starting with the protein positioned at a distance from PIP-containing bilayers suggested a novel mechanism for the association of the PTEN with the membrane. The initial encounter of the PTEN with C The
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the bilayer was followed by reorientation of the protein relative to the bilayer surface, resulting in more specific PTEN–lipid interactions [11] (Figure 2). After the association of PTEN with the bilayer, the PIP3 molecules were able to enter the PTEN catalytic cleft via lateral diffusion along with a degree of ‘loosening’ followed by ‘tightening’ of the PTEN– bilayer interaction. A similar encounter-plus-reorientation mechanism has also been observed for the related auxilin-1
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Figure 2 Mechanism of the association of the (A) PTEN and (B) talin head domains with a lipid bilayer as identified using multiscale simulations In (A) the PTEN C2 domain is shown in orange and the PD in blue. In (B) the talin head F0 subdomain is purple, F1 is green, F2 is cyan and F3 subdomain is yellow. PD, phosphatase domain.
PTEN-like domain, again via multiscale simulations [12]. In good agreement with other studies of C2 domains, these simulations demonstrated that the C2 loops facilitate the reorientation of the auxilin-1 PTEN-like domain to a productive orientation (Figure 2). Interestingly, simulations also demonstrated that the interaction of the PTEN domain from the Ciona intestinalis voltage-sensitive phosphatase (CiVSP) [45] did not generally require a reorientation step. In this study, it has also been shown that the residues that formed a substantive number of contacts with PIP2 or PIP3 molecules during the simulations are near the IP3 lipid headgroup (i.e. a substrate analogue) present in the crystal structure of the CiVSP domain. Binding of all three of the PTEN, auxilin-1 and Ci-VSP PTEN domains to PIP-containing bilayers results in clustering of PIP molecules around the proteins in the adjacent cytoplasmic leaflet [11,12] (Figure 3). Therefore, by using MD simulations, it was possible to show that PTEN domains associate with the membrane in a complex fashion
and that this results in the clustering of PIP molecules around the protein. This clustering changes the local organization of the lipids in the adjacent membrane leaflet, which in turn may be important for the localization of other related peripheral and/or integral membrane proteins.
FERM domains FERM domains contain three or four modules, and are found in many mammalian peripheral proteins. One of the main functions of the FERM-containing peripheral proteins is to link the plasma membrane, via interactions of the FERM domain with anionic lipids, to cytoskeletal compartments of the cell. Simulations of the talin–membrane–integrin complex provide a paradigm of how simulations may be applied to larger and more complicated peripheral proteins. Talin consists of a FERM head domain (F0, F1, F2 and F3) and a rod-like tail [46]. The F1 subdomain contains C The
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Figure 3 Snapshots of the lipid-bound (A) auxilin-1 PTEN-like domain, (B) PTEN and (C) the Ci-VSP PTEN domain The auxilin-1 C2 domain is shown in magenta, the PTEN C2 domain is shown in orange, and the Ci-VSP C2 domain is shown in green. Density profiles along the membrane normal for the C2 domains, the C2 penetrating loops and the lipid phosphate groups (black) reveal the depth of penetration of the three C2 domains into the membrane.
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a long positively charged insertion. Formation of the talin head domain–membrane–integrin complex is needed for the activation of the integrin receptor [47,48]. Simulations have shown that the positively charged insertion within the F1 subdomain may adopt an extended conformation close to the F0–F1 subdomains and next to the positive surfaces of the F2–F3 subdomains [13,14]. This creates an extended cationic surface which facilitates a productive association of the FERM head with the membrane. Interestingly, after the association of the FERM domain with the membrane, a novel V-shaped conformation, in which the F0–F1 pair is rotated relative to the F2–F3 domain, is adopted (Figure 2). The major conformational change within the talin FERM domain optimizes its electrostatic interactions with the anionic lipids, thus creating an optimal configuration of the talin–membrane complex which may be of mechanistic importance.
Conclusions and future directions Our understanding of how peripheral proteins interact with cell membranes has been significantly improved as in vitro, in vivo and in silico techniques have been developed. However, it remains challenging to resolve mechanistic and energetic details of the association of peripheral proteins with their target membranes. Multiscale simulations can predict molecular mechanisms of the association of different classes of peripheral proteins with model lipid bilayers. Given the number of different classes of such proteins (at least 14 different PIP-binding classes have been identified to date [9]) and the increasing number of structures of individual domains and proteins (e.g. ∼130 structures for PH domains have been determined), it will be important to develop more automated simulation approaches that will allow higher-throughput studies across whole families of peripheral proteins. The widespread application of this approach will enable identification and comparison of patterns and principles of the association of membrane recognition domains with bilayer lipids, defining to what extent such interactions are conserved across a given family of peripheral proteins. To date, many computational studies have focused on interactions of lipid-binding domains with relatively simple models of the lipid bilayer component of cell membranes. However, it is likely that that association and diffusion of peripheral protein at a membrane surface may be regulated by, e.g., membrane curvature [49]. Advances in simulation methodologies alongside model bilayers, which better reflect the compositional [50] and geometrical complexities of mammalian cell membranes, should enable more biologically realistic simulations to address these mechanistic issues.
Funding This work was supported by the Wellcome Trust [grant number 092970] and the Biotechnology and Biological Sciences Research Council [grant number BB/I019855/1].
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Interactions of peripheral proteins with model membranes as viewed by molecular dynamics simulations Antreas C. Kalli*1 and Mark S. P. Sansom* *Department of Biochemistry, University of Oxford, South Parks Road, Oxford OX1 3QU, U.K.
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Abstract Many cellular signalling and related events are triggered by the association of peripheral proteins with anionic lipids in the cell membrane (e.g. phosphatidylinositol phosphates or PIPs). This association frequently occurs via lipid-binding modules, e.g. pleckstrin homology (PH), C2 and four-point-one, ezrin, radixin, moesin (FERM) domains, present in peripheral and cytosolic proteins. Multiscale simulation approaches that combine coarse-grained and atomistic MD simulations may now be applied with confidence to investigate the molecular mechanisms of the association of peripheral proteins with model bilayers. Comparisons with experimental data indicate that such simulations can predict specific peripheral protein–lipid interactions. We discuss the application of multiscale MD simulation and related approaches to investigate the association of peripheral proteins which contain PH, C2 or FERM-binding modules with lipid bilayers of differing phospholipid composition, including bilayers containing multiple PIP molecules.
Introduction Transmission of signals across the plasma membrane is central to cellular function [1]. The mechanisms whereby such transmission can be achieved in many cases involve the reversible binding of peripheral membrane proteins to the cell membrane in order to, e.g., modulate the formation of protein–protein or protein–lipid complexes [2]. Localization and binding of peripheral proteins to the cell membrane may be controlled by lipid-binding modules, e.g. pleckstrin homology (PH), C2 and four-point-one, ezrin, radixin, moesin (FERM) domains, that are present in many peripheral proteins. We focus on how computational approaches can be used to elucidate the molecular details of the interactions of such lipid-binding modules with lipid bilayer models of complex cell membranes. Cell membranes are dynamic entities containing diverse lipid types in complex and time-dependent spatial arrangements [3]. Anionic lipids such as phosphatidylinositol phosphates (PIPs), present at a concentration of 5–15 % [4] in the plasma membrane, play a crucial role to the localization of different types of peripheral proteins. PIPs have an inositol headgroup which can be phosphorylated at different positions alongside acyl chains with four double bonds, which may result in a looser packing of PIPs Key words: four-point-one, ezrin, radixin, moesin (FERM), lipid bilayer, molecular dynamics simulation, phosphatase and tensin homologue deleted on chromosome 10 (PTEN), phosphatidylinositol phosphate (PIP), pleckstrin homology (PH). Abbreviations: CG-MD, coarse-grained MD; Ci-VSP, Ciona intestinalis voltage-sensitive phosphatase; FERM, four-point-one, ezrin, radixin, moesin; GRP1, general receptor for phosphoinositides 1; PH, pleckstrin homology; PIP, phosphatidylinositol phosphate; PIP2 , phosphatidylinositol 4,5-bisphosphate; PIP3 , phosphatidylinositol 3,4,5-trisphosphate; PKC, protein kinase C; PLC, phospholipase C; PS, phosphatidylserine; PTEN, phosphatase and tensin homologue deleted on chromosome 10. 1 To whom correspondence should be addressed (email [email protected]).
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within the membrane [5]. It is possible that clustering of PIP molecules may provide a scaffold for localization of peripheral protein to the cell membrane. Such PIP clustering may also be stabilized or enhanced by peripheral proteins [6]. The presence of PIPs and other anionic lipids (e.g. phosphatidylserine, PS) creates an overall negative electrostatic field, which is likely to facilitate the initial association of a peripheral protein with the inner membrane surface [7]. This initial encounter may be followed by formation of more specific interactions (e.g. hydrogen bonds) and a degree of penetration of parts of a peripheral protein into the hydrophobic core of the membrane [8]. The association of a peripheral protein with the membrane depends on both the properties of the peripheral protein and the properties of the membrane. Biophysical [9] and structural [10] techniques provide valuable insights into the underlying interactions of peripheral proteins with lipid bilayers. However, a complete understanding of the dynamic molecular events underlying lipid-binding domains with membranes remains elusive. Molecular simulations may be used to provide a ‘computational microscope’, enabling us to probe the mechanistic details of the binding of a peripheral protein to a membrane [11–14].
Simulation approaches to peripheral membrane proteins In the context of membrane biology, MD simulations have focused mainly on integral membrane proteins, both to understand their conformational dynamics and to assess their interactions with the surrounding lipids [15]. Simulations of the interactions of peripheral proteins with a membrane have in some ways proved more challenging because of the Biochem. Soc. Trans. (2014) 42, 1418–1424; doi:10.1042/BST20140144
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need for extended simulation timescales in order to address the coupled dynamic events underlying such interactions. These include (i) diffusional encounter of a protein with the membrane, (ii) diffusional redistribution of lipids within a bilayer in response to the encounter, (iii) conformational changes within the protein, and (iv) penetration of parts of the protein into the hydrophobic core of the bilayer. In the last few years, atomistic MD simulations have been used to study the interactions of, e.g., BAR [16], C2 [17], FYVE [18], Phox homology (PX) [19] and PH [20,21] domains with lipid bilayers and with membrane-mimetic models [22,23]. Bioinformatics and related approaches have also highlighted the key role of electrostatic interactions in the formation of peripheral protein–membrane complexes [7,24]. These and other simulation studies have provided detailed models of both the specific and non-specific interactions of key recognition domains with membrane lipids. However, many molecular simulation approaches require a degree of prior knowledge of the nature of the membrane-anchoring region of the protein and/or of the orientation and position of the protein relative to the lipid bilayer surface [25]. These limitations may be addressed by using lower-resolution simulation methodologies, e.g. coarse-grained MD (CGMD) simulations [26,27]. In the CG-MD approach, both the protein and the lipids are simplified by grouping together small numbers (typically four or five) of atoms into coarse-grained particles. This simplification enables longer timescales and larger, more complex systems to be addressed [28,29]. However, it introduces a degree of approximation. The use of a multiscale approach, in which initial lower-resolution CG-MD simulations are combined with subsequent atomistic simulations, helps to address such limitations. This may be viewed as a process of zooming in one’s computational microscope as a simulation of protein– membrane interactions proceeds. In the following sections, we discuss some examples of how such multiscale MD simulations have been used to study three important and abundant lipid-binding modules, namely PH, C2 and FERM domains.
PH domains PH domains contain approximately 100 amino acids in an antiparallel β-sheet architecture followed by one or two αhelices. PH domains form a highly structurally conserved family of proteins, but with considerable sequence diversity. The low sequence similarity between different PH domains correlates with differences in their specificity for PIPs [30]. Early atomistic simulation studies showed that the presence of phosphatidylinositol 4,5-bisphosphate (PIP2 ) molecules in a zwitterionic phosphatidylcholine bilayer enhanced the association of the phospholipase C-δ1 (PLCδ1) PH domain with the bilayer [20]. Han et al. [31] used CG-MD simulations to suggest a mechanism for the association of the PLCβ2 PH domain with model bilayers. MD simulations combined with NMR and monolayer penetration experiments on general receptor for phosphoinositides 1 (GRP1) have shown
that specific electrostatic interactions between the GRP1 PH domain and a phosphatidylinositol 3,4,5-trisphosphate (PIP3 ) molecule are combined with non-specific interactions between flexible hydrophobic loop regions of the PH domain and surrounding lipids in the bilayer [21]. Recent multiscale MD simulations have examined the association of PH domains from the kindlin family of proteins with PIP-containing bilayers. These studies revealed that the kindlin PH isoforms associate with the PIP2 and PIP3 molecules in the membrane via a positively charged loop region (A.C. Kalli and M.S.P. Sansom unpublished work) (Figure 1). In silico mutations of positively charged residues on this loop perturb the orientation of the PH domains relative to the lipid bilayer. Interaction of kindlin PH domains with the negatively charged lipid headgroups results in the clustering of PIP molecules in the (inner) leaflet of the bilayer adjacent to the protein. In addition, MD simulations and molecular docking have suggested that disruption of a salt bridge in the kindlin-1 PH-binding pocket may be needed before PIP3 binding [32]. Overall, these simulation studies suggest that PH domains associate with the membrane via a multistep process involving both specific interactions with the PIP molecules and non-specific interactions with the bilayer.
C2 domains and PTEN C2 domains also possess an antiparallel β-sheet architecture, with variable loops connecting the β-sheets [33,34]. C2 domains can associate with the membrane in either a Ca2 + dependent [e.g. the protein kinase C (PKC) C2 domain] or a Ca2 + -independent manner, e.g. the phosphatase and tensin homologue deleted on chromosome 10 (PTEN) C2 domain [35]. Both types of C2 domains have been shown to interact with anionic lipids with different specificities and/or to coordinate interactions with multiple lipid molecules [36–38]. Atomistic simulations of the cytoplasmic phospholipase A2 (cPLA2 ) C2 domain revealed specific interactions of the loop regions of the C2 domain with the lipids [17]. MD simulations of the PKCα C2 domain combined with experimental studies suggested that in the presence of PIP2 molecules the C2 domain was tilted away from the bilayer, in good agreement with EPR spectroscopic data [39]. Computational studies of the PKCα C2 domain also suggested that Ca2 + -dependent PS binding is needed for the formation of the PKCα C2– membrane complex [40]. A biomedically important example of the C2–membrane interaction is seen in the case of PTEN, a cytosolic enzyme which catalyses dephosphorylation of PIP3 to PIP2 [41,42]. Structural modelling of a PIP3 molecule in the PTEN catalytic site combined with multiscale simulations of the PTEN– PIP3 complex [43] demonstrated that PTEN is located on the lipid–water interface with the loop regions of the PTEN C2 domain, interacting with the bilayer. Atomistic simulations using an extended model of PTEN showed that the PTEN C2 domain associates strongly with PS lipids, although also suggesting that regulatory conformational changes of C The
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Figure 1 Association of the PH domains of the kindlin family of proteins with model membranes (A) Snapshots from a simulation of the kindlin-1 PH domain with a POPC/POPS/PIP2 bilayer at 0, 0.8 and 1.5 μs. The lipid headgroups are shown as grey spheres and the lipid tails are in cyan. (B) Mean distance as a function of time between the centres of mass of the kindlin-1 PH domain and the centre of the bilayer for three different membrane models: POPC, black; POPC/POPS, red; and POPC/POPS/PIP2 , green. (C) Model of the kindlin-1 PH domain bound to a PIP2 -containing bilayer derived from multiscale simulations. The PH domain is shown in orange. POPC and POPS lipid molecules are shown in grey. PIP2 molecules are shown in the bond format to highlight their headgroups. POPC, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine; POPS, 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylserine.
the PTEN C-terminal tail in the membrane-bound and membrane-unbound states may occur [44]. Subsequent multiscale MD simulation studies of the PTEN focused on the mechanism of protein–membrane encounter and recognition. Simulations starting with the protein positioned at a distance from PIP-containing bilayers suggested a novel mechanism for the association of the PTEN with the membrane. The initial encounter of the PTEN with C The
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the bilayer was followed by reorientation of the protein relative to the bilayer surface, resulting in more specific PTEN–lipid interactions [11] (Figure 2). After the association of PTEN with the bilayer, the PIP3 molecules were able to enter the PTEN catalytic cleft via lateral diffusion along with a degree of ‘loosening’ followed by ‘tightening’ of the PTEN– bilayer interaction. A similar encounter-plus-reorientation mechanism has also been observed for the related auxilin-1
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Figure 2 Mechanism of the association of the (A) PTEN and (B) talin head domains with a lipid bilayer as identified using multiscale simulations In (A) the PTEN C2 domain is shown in orange and the PD in blue. In (B) the talin head F0 subdomain is purple, F1 is green, F2 is cyan and F3 subdomain is yellow. PD, phosphatase domain.
PTEN-like domain, again via multiscale simulations [12]. In good agreement with other studies of C2 domains, these simulations demonstrated that the C2 loops facilitate the reorientation of the auxilin-1 PTEN-like domain to a productive orientation (Figure 2). Interestingly, simulations also demonstrated that the interaction of the PTEN domain from the Ciona intestinalis voltage-sensitive phosphatase (CiVSP) [45] did not generally require a reorientation step. In this study, it has also been shown that the residues that formed a substantive number of contacts with PIP2 or PIP3 molecules during the simulations are near the IP3 lipid headgroup (i.e. a substrate analogue) present in the crystal structure of the CiVSP domain. Binding of all three of the PTEN, auxilin-1 and Ci-VSP PTEN domains to PIP-containing bilayers results in clustering of PIP molecules around the proteins in the adjacent cytoplasmic leaflet [11,12] (Figure 3). Therefore, by using MD simulations, it was possible to show that PTEN domains associate with the membrane in a complex fashion
and that this results in the clustering of PIP molecules around the protein. This clustering changes the local organization of the lipids in the adjacent membrane leaflet, which in turn may be important for the localization of other related peripheral and/or integral membrane proteins.
FERM domains FERM domains contain three or four modules, and are found in many mammalian peripheral proteins. One of the main functions of the FERM-containing peripheral proteins is to link the plasma membrane, via interactions of the FERM domain with anionic lipids, to cytoskeletal compartments of the cell. Simulations of the talin–membrane–integrin complex provide a paradigm of how simulations may be applied to larger and more complicated peripheral proteins. Talin consists of a FERM head domain (F0, F1, F2 and F3) and a rod-like tail [46]. The F1 subdomain contains C The
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Figure 3 Snapshots of the lipid-bound (A) auxilin-1 PTEN-like domain, (B) PTEN and (C) the Ci-VSP PTEN domain The auxilin-1 C2 domain is shown in magenta, the PTEN C2 domain is shown in orange, and the Ci-VSP C2 domain is shown in green. Density profiles along the membrane normal for the C2 domains, the C2 penetrating loops and the lipid phosphate groups (black) reveal the depth of penetration of the three C2 domains into the membrane.
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a long positively charged insertion. Formation of the talin head domain–membrane–integrin complex is needed for the activation of the integrin receptor [47,48]. Simulations have shown that the positively charged insertion within the F1 subdomain may adopt an extended conformation close to the F0–F1 subdomains and next to the positive surfaces of the F2–F3 subdomains [13,14]. This creates an extended cationic surface which facilitates a productive association of the FERM head with the membrane. Interestingly, after the association of the FERM domain with the membrane, a novel V-shaped conformation, in which the F0–F1 pair is rotated relative to the F2–F3 domain, is adopted (Figure 2). The major conformational change within the talin FERM domain optimizes its electrostatic interactions with the anionic lipids, thus creating an optimal configuration of the talin–membrane complex which may be of mechanistic importance.
Conclusions and future directions Our understanding of how peripheral proteins interact with cell membranes has been significantly improved as in vitro, in vivo and in silico techniques have been developed. However, it remains challenging to resolve mechanistic and energetic details of the association of peripheral proteins with their target membranes. Multiscale simulations can predict molecular mechanisms of the association of different classes of peripheral proteins with model lipid bilayers. Given the number of different classes of such proteins (at least 14 different PIP-binding classes have been identified to date [9]) and the increasing number of structures of individual domains and proteins (e.g. ∼130 structures for PH domains have been determined), it will be important to develop more automated simulation approaches that will allow higher-throughput studies across whole families of peripheral proteins. The widespread application of this approach will enable identification and comparison of patterns and principles of the association of membrane recognition domains with bilayer lipids, defining to what extent such interactions are conserved across a given family of peripheral proteins. To date, many computational studies have focused on interactions of lipid-binding domains with relatively simple models of the lipid bilayer component of cell membranes. However, it is likely that that association and diffusion of peripheral protein at a membrane surface may be regulated by, e.g., membrane curvature [49]. Advances in simulation methodologies alongside model bilayers, which better reflect the compositional [50] and geometrical complexities of mammalian cell membranes, should enable more biologically realistic simulations to address these mechanistic issues.
Funding This work was supported by the Wellcome Trust [grant number 092970] and the Biotechnology and Biological Sciences Research Council [grant number BB/I019855/1].
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