molecular dynamics simulation of dark-adapted rhodopsin in ... · system. two recent molecular...

Molecular Dynamics Simulation of Dark-adaptedRhodopsin in an Explicit Membrane Bilayer: Couplingbetween Local Retinal and Larger ScaleConformational Change

Paul S. Crozier1, Mark J. Stevens1*, Lucy R. Forrest2 andThomas B. Woolf2

1Sandia National LaboratoriesP.O. Box 5800, MS 1411Albuquerque, NM 87185-1411USA

2Department of PhysiologyJohns Hopkins UniversitySchool of Medicine, BaltimoreMD 21205, USA

The light-driven photocycle of rhodopsin begins the photoreceptorcascade that underlies visual response. In a sequence of events, the retinalcovalently attached to the rhodopsin protein undergoes a conforma-tional change that communicates local changes to a global conformationalchange throughout the whole protein. In turn, the large-scale proteinchange then activates G-proteins and signal amplification throughout thecell. The nature of this change, involving a coupling between a localprocess and larger changes throughout the protein, may be important formany membrane proteins. In addition, functional work has shown thatthis coupling occurs with different efficiency in different lipid settings.To begin to understand the nature of the efficiency of this coupling indifferent lipid settings, we present a molecular dynamics study ofrhodopsin in an explicit dioleoyl-phosphatidylcholine bilayer. Our systemwas simulated for 40 ns and provides insights into the very early events ofthe visual cascade, before the full transition and activation have occurred.In particular, we see an event near 10 ns that begins with a change inhydrogen bonding near the retinal and that leads through a series ofcoupled changes to a shift in helical tilt. This type of event, though rareon the molecular dynamics time-scale, could be an important clue to thetypes of coupling that occur between local and large-scale conformationalchange in many membrane proteins.

q 2003 Elsevier Ltd. All rights reserved.

Keywords: rhodopsin; molecular dynamics; membrane protein; simulation*Corresponding author

Introduction

Rhodopsin is the prototypical G-protein coupledreceptor (GPCR) due to the large amount of experi-mental information related to both its structure andits function.1 – 5 It is also the first GPCR with adefined tertiary structure and is thus an excellentcandidate for trying to understand the moleculardetails of function. A full understanding of these

details is difficult, however, due to the large separ-ation in time-scales between the photocycle ofrhodopsin and current computational limits incomputer simulation of bio-molecules. In particu-lar, the full photocycle occurs on the millisecondtime-scale,6 while the state-of-the-art in computersimulation of large proteins is tens of nanoseconds.

Despite the limitations on accessible confor-mations for biomolecules within a computer-simulated system, many important questions can beaddressed through detailed computational modelsthat would not be directly measured experimentally.Thus, a detailed computational model can suggestdetails of function and motion that are difficult toenvision from a static structure and isolated experi-ments. That is, simulation can play a valuable rolein helping to inform intuition about how a structuremoves in its native environment and in suggesting

0022-2836/$ - see front matter q 2003 Elsevier Ltd. All rights reserved.

Present address: L. Forrest, Department ofBiochemistry, University of Columbia, New York, NY10032, USA.

E-mail address of the corresponding author:[email protected]

Abbreviations used: GPCR, G-protein coupledreceptor; DOPC, dioleoylphosphatidylcholine; vdW, vander Waals.

doi:10.1016/j.jmb.2003.08.045 J. Mol. Biol. (2003) 333, 493–514

new classes of experiments that would not have beenattempted in the absence of a detailed simulation.

In addition to the many intriguing features relatedto the rhodopsin photocycle, rhodopsin is also thefirst membrane protein to show a clear sensitivity toits lipid environment. For example, the Browngroup has shown that the M-I to M-II transition ismodulated by the relative mixture of DOPC toDOPE lipids.7–12 In addition, it has been known forsome time that rhodopsin is sensitive to the alkanechain type.13,14 This has led to the realization thatrhodopsin prefers DHA for its environmentalbackground.15 A leading question then, in additionto the details of the photocycle, is how the lipid set-ting can influence the types of functionally importantmotions that the rhodopsin molecule can perform.

There are many excellent reviews on rhodopsinand the connections from rhodopsin to both GPCRsand retinal cell function.1–5 It is not our intent toreview all of the large amount of experimental infor-mation available for this system, as that would thenbe a full separate article in its own right. Rather, weaim in the following paragraphs to provide somefurther context for consideration of the computations.

Rhodopsin background

Bovine rhodopsin has served as a model systemfor the understanding of transduction for manyyears.16 In particular, studies in bovine rods haveled to a general understanding of G-protein coupledsystems, and have led to the first GPCR that wassequenced,16 and to understanding of the connec-tions between particular residues and the rhodopsinfunction.3,17 For example, the role of Glu113 as thecounterion,18 the critical role of certain residues intransduction,19,20 and initial suggestions for spectraltuning21–23 all begin with rhodopsin. An upcomingfrontier is the understanding of the connectionsbetween the structures of the G-protein itself24,25 andthe conformational changes that underlie the photo-cycle and lead to activation and signaling.

Low-resolution structures of rhodopsin

Hydrophobic analysis of the rhodopsin sequenceled to suggestions that the membrane protein hadseven transmembrane helices.26 These initial sug-gestions were confirmed through low-resolutionstructural work27 that also provided the impetusfor improved models of GPCRs.28 The low-resolution structures were also sufficient to confirmthat rhodopsin and bacteriorhodopsin do not sharestructural similarity and that homology models forGPCRs based on bacteriorhodopsin were not correct.

X-ray structure

Membrane proteins have proven difficult tocrystallize for high-resolution structural infor-mation. Thus, each new structure brings a wave ofexcitement and generates a host of new questions.The rhodopsin structure showed the expected

seven transmembrane domains that had beenpredicted both computationally and from low-resolution data.29 – 33 In addition, the structureshowed a beta-strand cap in the extracellular loopfrom helices 3 to 4. This cap structure may alsoplay a role in other family A GPCRs andsuggests that the properties of the binding sitemay not be determined entirely by the trans-membrane domains. The structure showed theexistence of an eighth amphipathic helix that alsohas two palmitoylation sites associated with it.29

While the structure is important for showing theconformation associated with the dark state andfor determining the protein environment of theretinal, it does not, by itself, show how the largeconformational changes occur that lead toactivation of G-proteins. This structure further-more provides the basis for consideration ofhomology models of other GPCRs, for considerationof packing arrangements of helices in membraneproteins and even for considerations of the foldingof alpha-helical membrane proteins.34–36

UV-FTIR spectroscopy; photocycle

The rhodopsin photocycle has been described onthe basis of spectral measurements.37 – 41 With therecent crystal structure it is possible to start relat-ing the structure to the measurements, but thisrequires a quantum-mechanical framework for thecomputation. This relates back to early work onthe relation between the energetics of the activatinglight and the coupling to protein and retinalconformations.42,43 In particular, there has beenmuch discussion of the role of electrostatics and ofmodulation by the protein environment of theretinal conformational energetics. Clearly, a fullunderstanding of the coupling between confor-mation at the retinal level and the protein environ-mental changes due to the light activation iscentral to relating structure to function in thissystem. Two recent molecular dynamicscalculations start to try to connect the cis–transisomerization of the retinal with the proteinchanges.44,45 In one simulation, starting from thedark-adapted state in a membrane setting, steeredmolecular dynamics is used to force thetransition.45 In a second simulation paper, a mem-brane mimic was used for the environment andrestraints were applied to evaluate the cis–transchanges in the first stages of the photocycle.44 Inaddition, the reaction path for the transition hasbeen considered from a theoretical viewpoint andsuggests that a hula-twist conformational changeoccurs during the photocycle.46–48 Confirmation ofthe reaction mechanism has been aided by consider-ation of designed chemical mimics of retinal thatalter the photocycle in controlled ways.49–53

Electron paramagnetic resonance; large-scale motions

The details of how light induces a conformational

494 Molecular Dynamics of Rhodopsin in a Membrane

change leading to G-protein activation are notrevealed by the X-ray structure or the UV-FTIR spec-tral methods. Some insights into the types of motionsthat occur with activation have been achievedthrough the use of cysteine-linked spin labelmethods.54,55 With this approach an engineeredcysteine is reacted with a spin-label and either dis-tances between labels or relative accessibility of a sol-vent-based probe is determined.54,55 The results havesuggested that the photocycle involves changes intilt and some rotation in helices III and VI.55–57 Thissuggests that some part of the activation of rhodop-sin involves coupling between a sensor of the localchange in rhodopsin and the generation of largerigid-body like movements in the helices that leadsto activation of G-proteins.54,55 These results havealso been examined and extended by looking atcysteine–cysteine interactions between engineeredsites in rhodopsin.58

Solid-state and high-resolution NMR

Rhodopsin has been used as a testing ground formeasurements of distance in SS-NMR withrotational resonance and other methods.59 – 70 Theresults have provided structural constraints on dis-tances in the rhodopsin molecule and have inferredproperties of the photocycle. In particular, theNMR methods have suggested the possibility thatthe beta ionone retinal ring may be in a trans ratherthan the cis state observed in the X-ray structure.70

Recent, continuing analysis of this situation hassuggested that there is room for either confor-mation, while the exact conformation of the dark-adapted state for the ring is thus unclear. Inaddition, NMR methods have been used to inferrelative motion of different regions of rhodopsinand to suggest aspects of the lipid dependence ofthe system.

Site-directed mutagenesis

Nearly every residue in the rhodopsinstructure has been examined with site-directedmutagenesis19,71 – 73 and new ideas have beengenerated by the X-ray structure.74 A variety ofexperimental methods have been used to assessthe behavior of the altered system, focusing mainlyon changes in the full photocycle. These results areintriguing for suggesting the possible roles ofindividual amino acids in the function of theprotein. With the presence of the X-ray structure itbecomes possible to try and relate this history ofmutagenesis to the solved structure and severalrecent reviews can be consulted for current effortsin this direction.1,3 – 8

Results

We simulated bovine rhodopsin in the dark-adapted state. For the simulation, the lipid bilayer,salt, and water were represented in atomic detail,

along with the rhodopsin protein and palmitoyl-ated side-chains. Figure 1 shows the outlines ofthe simulation system. More details are providedin Methods. In the following we concentrate onthe analysis and possible implications for rhodop-sin function in the 40 ns simulation.

Our results naturally break down into severalsub-categories. For easier analysis and reading, wepresent results in the order: (1) average structureresults (validation of the simulation conditions);(2) conditions around the retinal-binding site; (3)large-scale motions (and coupling throughout thesystem); and (4) lipid and water interactions.

Average structural results

RMS

A measure of the relative stability of a moleculardynamics simulation is the sampling near to thestarting point. Since the starting point is a relaxedstructure based on the X-ray data, this providesboth a measure of the amount of motion seen inthe trajectory and the relative deviation from the

Figure 1. Overview of the simulation system used. Thewater (7441 TIP3) is schematically shown in blue. Thelipid (99 DOPC, two palmitate) is shown in tan.This illustrates where the bilayer sits relative to theprotein. The protein is illustrated in cartoon form withthe helices labeled. Note that the cytoplasmic side is onthe top and that helix VIII is the amphipathic helix. Thebasic residues are colored in the cartoon as blue, theacidic residues are shown in red, the polar residues ingreen and the non-polar residues in white. The actualsimulation was all-atom and all-hydrogen and consistedof 41,623 atoms in total.

Molecular Dynamics of Rhodopsin in a Membrane 495

experimental starting point. Since simulationscannot, yet, reach long time-scales, a general ruleof thumb is that large deviations from the startingpoint indicate a poorly defined simulation andthat analysis of such a simulation would beinappropriate. On the other hand, a well-definedsimulation should, at a minimum, have an RMSdeviation relative to the starting point that isreasonable. At the same time, the ideal simulationwill also have sampled well from the startingpoint and can comment on the types of motionsexpected from the static initial point. In Figure 2,we present the average RMS over the 40 ns simu-lation relative to the simulation starting point. Ascan be seen clearly, the loops have much moremotion than the helices and the average positionof the helices stays relatively near to the X-raystarting point. This is especially true in the earlystages of the simulation where we did not observeany large changes in the helix orientation or pack-ing. As presented in more detail in this section,later in the simulation, we observe a change inhelix tilt and helix kinking that is indicative of alarger scale conformational change. This first figureshows that our simulation is stable and well-defined by current molecular dynamics standards.

Other trends are obvious as well in Figure 2. Forexample, the largest motions are seen in the C-IIIand C-terminal regions. This indicates a largeamount of relative motion is found in these regionsrelative to the more restricted motion observed inthe helices and the other loop regions. As broughtout more in the discussion, this is consistent withexperimental information obtained from site-directed spin labeling (SDSL) and NMR.

B-factors

The recent X-ray structure provides an initial

insight into relative motion throughout therhodopsin protein through Debye–WallerB-factors. These assume an isotropic motionalmodel and may thus be biased for certainsituations (e.g. if there is more motion in the effec-tive bilayer plane than normal to that plane, thenthis type of motional model would not be the bestfor comparison of dynamics). Nonetheless, thiscomparison is useful, since it provides a roughguide to the types of motion that might be presentin the crystal cell used for X-ray analysis and thetypes of motion that we compute in the lipidbilayer setting. As can be seen in Figure 2, theanalysis suggests that there is considerablesimilarity, in that the loops and termini are moreflexible than the interior helical packing regions.

Retinal binding site

One central mystery for rhodopsin function isthe coupling between local changes in the retinaldue to light activation and the eventual G-proteinamplification mechanisms controlled by G-proteinbinding changes in the cytoplasmic regions of theGPCR rhodopsin. Even though our simulationtime is well short of the full cycle, the moleculardynamics calculations give some insights into thenature of this coupling through analysis of thetypes of fluctuations seen in the binding site andthe amplification and coupling of those changesthroughout the full protein molecule. For this typeof analysis, we first concentrate on the nature ofthe average interaction energies, and then com-ment on the time dynamics of coupling for retinalchanges with the local protein environment.

Dihedral changes

The action of rhodopsin involves the transitionof the retinal in the 11-cis state to the all-transstate. We calculated the dihedral angle for each ofthe dihedrals in the retinal. Figure 3 shows thedihedral angle as a function of time for several ofthe retinal dihedrals. The dihedral for the 11-cis(C11–C12) is flat, indicating no transition. This isto be expected even for a 40 ns simulation. Thetime-scale for the transition without the photonadsorption is well beyond the simulation time.However, some of the other dihedrals show tran-sitions. These transitions demonstrate that theretinal molecule is not locked within the rhodopsinsuch that it cannot move. Furthermore, as thesedihedral transitions affect the retinal structure,they affect the interactions between the retinal andthe rhodopsin residues. These interactions conse-quently have many dynamic transitions. We willhighlight some of these transitions particularlyinvolving hydrogen bonds in Discussion.

Figure 3 shows that frequent transitions occurfor dihedrals about the Cd–Cg and Ce–N16 bondsof Lys296. These dihedral transitions move therelatively highly charged N16, C15 and theirhydrogen atoms. These atoms are involved in the

Figure 2. RMS of heavy atoms from the X-ray structureduring the simulation. Note the larger RMS values forthe loops and lower RMS for the helices.


strong interactions with Glu113 in particular (seeFigure 5). In addition, the residues Ser186 andThr94 interact with these atoms, but their energetictransitions (see Figure 6) are more related to theirown dihedral dynamics. The dihedral about C10–C11 is very noisy, but does not exhibit many com-plete transitions. For comparison, the dihedralsnot shown in Figure 3 do not exhibit transitionsand are like the C11–C12 dihedral. There areseveral short-lived transitions in the dihedralabout C8–C9 in the retinal chain. There arenumerous transitions particularly for t . 20 ns forthe dihedral about C6–C7, which rotates the retinalring. The position of the retinal ring is conse-quently frequently varying for t . 20 ns. We seethat retinal structure is very dynamic, implyingthat the interaction state of retinal is also verydynamic. We thus examined the interactionenergies between the retinal and nearby rhodopsinresidues as a function of time (see below).

The dihedral transitions that occur in nearbyside-chains of the protein near the retinal moietyare also illustrated in Figure 3. In particular, notethat several transitions occur during the course ofthe 40 ns trajectory. We find that the transitionsnear 10 ns reflect changes throughout the proteinand possible coupling between the local changeswithin the binding cavity and the larger scale con-formational transitions that could be linked to theM-II state and G-protein signaling mechanisms.For example, Ser186 has three main transitionsduring the trajectory including one near 10 ns.Glu122 has a series of very rapid transitions separ-ated by a few, short periods of relatively constantdihedral value. Thr94 sees a single large transitionnear 10 ns and a few rapid fluctuations around30 ns. Lastly, for illustration of those protein side-chains near where the retinal undergoes confor-mational changes during the trajectory, Glu181had four transition periods during the trajectory.This Figure illustrates the importance of having along trajectory, since these relatively rare transitionevents may occur only once (e.g. Thr94) during thetrajectory.

Volumetric packing

During the simulation each atom has available toit a range of motions that are primarily restrictedby the behavior of the neighboring atoms. Thus,retinal in the binding pocket of rhodopsin iscapable of a set of motions that are determined bythe interplay between the intrinsic degrees of free-dom of the retinal and the environmental restraintsprovided by the protein itself. Since the cavity islargely protein dominated, there is little role forwater and the range of environmental restraintsexpected from the protein is quite different fromwhat would be expected for retinal in a purewater environment. By computing the range ofaccessible volumes (Voronoi analysis, seeMethods), we compute a set of available spacesthat each atom of the retinal is capable of reachingin the simulation. Thus, a larger volume meansdirectly that more motion is possible for that atomtype. While this analysis averages the ensembleset of motions into a set of equivalent volumes, itdoes give an idea of where the largest amount ofthermal motion is available to the retinal atoms. Inother words, it is hard to directly infer from thesize of the cavity the range of forces that lead tothat cavity volume, but the range of cavityvolumes, across the retinal molecule, give an ideaof the range of environmental restraints providedby the protein.

Figure 4 presents a time-averaged picture ofavailable volume for each heavy-atom group ofthe retinal. The available volume for each atom iscalculated using a Voronoi method and averagedover time.75 Note that the x-axis moves from thering atoms (C1 to C6) through the chain atoms (C7to C16), the methyl groups along the retinal (C17to C20) and into the main-chain connections (N16

Figure 3. Dihedral angle as a function of time for bothretinal and nearby side-chains of the protein.


to N). In this manner of analysis, the largest freethermal volume is attained by the five methylgroups. The C18 methyl group has the largest fluc-tuations in the dynamics of the five groups. Theselarge values for the methyl groups are not surpris-ing, since the bond connecting them to the retinalcan have relatively strong rates of transition andthus the free volume for each reflects the rotationsallowed for the full methyl group. In contrast withthe large value seen for the methyl groups, the C1atom of the ring is nearly an order of magnitudesmaller in thermal volume. This implies that thisparticular heavy atom is much more restricted inrelative motion. Again, this can be rationalized,since the C1 atom connects both to the ring atoms(C2 and C6) and to two methyl groups (C17 andC16). Thus, the largest and smallest thermalvolumes make sense.

Figure 4 also shows that the ring methylenegroups (C2, C3, and C4) have greater thermalvolume available to them than doubly bondedchain carbon atoms with one hydrogen. Thismakes sense as well, since the smaller thermalvolumes for chain heavy atoms are for those car-bon atoms with methyl groups covalently linked(C9 and C13 to C19 and C20 respectively). Thus,the thermal volumes calculated as averages fromthe simulation make chemical sense with the sizeof the groups appended to the carbon drivingmuch of the available free volume.

Time-averaged interaction energies

The time-averaged interaction energy Eave ofretinal with the surrounding environment givesinsight into the relative importance of different

residue:retinal interactions for functional isomeri-zation. In particular, several experimentalgroups1,66,76 have suggested that particular residues(e.g. the Schiff base counter-ion Glu113) are moreimportant than others in the photocycle. Inaddition, some residues have been suggested tocontribute to the coupling between local con-formational change and G-protein signalingmechanisms. In this regard, NMR work60 – 62 andthe X-ray structure29 – 31,77 have highlighted residues(e.g. Trp265) that may act as switches in the light-driven conformational change and the connectionof protein conformational change to G-proteinsignaling. While the interaction energies do notdirectly comment on the possible role of individualamino acids in the switch mechanism, they doprovide some guidance as to which amino acidresidues are most tightly coupled, energetically, tothe retinal. Thus, a priori, it is expected that astronger energetic coupling will imply that changesin retinal conformation (e.g. driven by a lightevent) will lead to changes in the amino acid side-chain position and conformation. In turn, this maylead to the changes in large-scale protein confor-mation. As will be presented in the discussionbelow, energetic transitions due to structuralrearrangements are found in our 40 ns simulation.The structural stability of rhodopsin, particularlyin relation to retinal, involves many strong inter-actions that act cooperatively. Thus, this analysissuggests that a single switch mechanism is overlysimplified relative to the complex cooperativedynamics that are observed in the simulation.

Interaction energies between retinal and the sur-rounding residues were computed individuallyfor each surrounding residue interacting with eachof three segments of the retinal moiety: the Lys296residue (bonded to the retinal), the retinal linearchain, and the retinal ring. This enables us to com-ment on which amino acid residues are interactingwith the given regions of the retinal moiety.Figure 5 shows these interaction energies for eachpart with the nearby residues. Note that wepresent only those interaction energy terms thatare either strongly favorable (less than 21 kcal/mol) or strongly unfavorable (more than 1 kcal/mol). The strong interaction energies are typicallydue to Coulomb interactions (some of which arehydrogen bonds). From the crystal structure,29,30

there are some expected strong interactions. Forexample, the terminal N16 of Lys296 is chargedand close to the Schiff base counter-ion in Glu113.In addition there is a strong interaction withGlu181. There is another glutamic acid (Glu122)close to the retinal ring. Besides these potentialstrongly charged interaction sites, there are manypossibilities for hydrogen bonds.

With this breakdown we note that only oneresidue, Glu181, has strong interactions with allthree components of the retinal. In this case, it hasstrong favorable interactions with the chain andthe ring, and an unfavorable interaction withLys296. There is one amino acid, near to the ring,

Figure 4. Volumetric analysis of the packing in theretinal binding pocket. This reflects a time averageusing Voronoi analysis of the average space available toeach chemical group in the cavity.


Gly188, which has no strong interactions with theretinal. Given its small size, this amino acid maystill play an important role in allowing particularinteractions and conformational changes, but it isprobably not playing a strong coupling role to theretinal, due to the lack of observed interactionenergies.

In a more quantitative analysis, we note fromFigure 5 that Glu113 has the most negative averageenergy of 251 kcal/mol for interaction with theretinal chain and has a 232.6 kcal/mol interactionenergy with the main chain of Lys296. In addition,Glu181 shows the second strongest interactionenergy with 231 kcal/mol to the retinal chain.Surrounding residues interact with Lys296 mostlyvia its N16 atom, and with the retinal chain mostly

via its C15 atom. Both atoms have relatively largepartial charges. Besides the Glu residues, threeresidues close to Lys296 interact strongly with it.Thr297 has an average interaction energy of214.8 kcal/mol; Ala295 has Eave ¼ 214:3 kcal/mol and Phe293 has Eave ¼ 27:4 kcal/mol. Mostof the time average interaction energies for otherresidues are in the range 23 to þ3 kcal/mol. Twoother residues have significant attractive Eave withLys296 outside this range. They are Phe91 at25.11 kcal/mol and Glu181 at 24.60 kcal/mol.Residues that interact strongly with the retinalchain are the following. Cys187 has a high averageenergy of 27.5 kcal/mol. Ala292 has an averageenergy of 26.3 kcal/mol and Tyr268 has anaverage energy of 23.3 kcal/mol. In the positive

Figure 5. Energy of interaction is plotted as a time average. This Figure presents the energetic coupling as a timeaverage between retinal chemical moieties and the surrounding amino acid residues. The retinal ring (squares) isdefined as carbon atoms 1, 2, 3, 4, 5, 6, 17, and 18, as well as the associated hydrogen atoms. The retinal chain(triangles) is defined as carbon atoms 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, and 20 and the associated hydrogen atoms. Thebase (circles) consists of the Lys296 atoms to which the retinal is attached: N16, Ce, Cd, Cg, Cb, Ca, other backboneatoms (C, N, O) and associated hydrogen atoms. For clarity, only interactions with values greater than 1 kcal/mol orless than 21 kcal/mol are shown. Error bars represent standard deviations.


energy range, only Ser186 with an average energyof þ7.5 kcal/mol is outside the most occupiedrange of interactions with the retinal chain. Thestrongest interactions with the retinal ring aremuch weaker than for Lys296 or the retinal tail.Doubly protonated His211 has the most negativeaverage energy of 27.6 kcal/mol and Phe212 issecond with 23.0 kcal/mol. There are strongrepulsive interactions with the retinal ring, in bothcases with Glu residues. The strongest is Glu122with an average energy of þ9.1 kcal/mol, and forGlu181 Eave equals þ4.3 kcal/mol.

Time-dependent interaction energies

Changes in interaction energy can provide anidea of how local conformational changes arecoupled into larger changes throughout thesystem. In particular, by looking at the localchanges in interaction energy within the retinal-binding pocket, we start to see where changeswithin this binding pocket might be coupled intolarger changes in the helix motions and helix kinkangle. While it is difficult to separate cause andeffect in a large cooperatively coupled system,looking for events that are correlated in time doesgive some indication of what change might berelated to what other change in the system.

An example of a local interaction energy tran-sition is seen in Figure 6. Part (a) shows the inter-action energy between Ser186 and Lys296.A transition with a large energy difference equalto 24.7 kcal/mol occurs at t ¼ 9:9 ns. Initially, thehydroxyl of Ser186 is far from Ce and N16 ofLys296. The transition at t ¼ 9:9 ns is due to adihedral rotation in Ser186 (see Figure 3) thatespecially brings the Og close to the oppositelycharged Ce. The Figure shows that there wereother times in the simulation in which the tran-sition partially occurred (or reversed). Moreover,these transitions are mirrored in the interactions ofSer186 with the retinal chain (Figure 6(b)).

At the same time as the transition at t ¼ 9:9 nsbetween Ser186 and both Lys296 and the retinalchain, Thr94 has a large transition in its interactionwith the retinal chain (Figure 6(c)). Graphicalexamination of trajectories shows for earlier times,the hydroxyl groups in Thr94 and Ser186 form ahydrogen bond. The energy change indicates thestructural rearrangement in which acceptor oxygenchanges from the oxygen in Ser186 to the oxygen inThr94. This brings the Thr94 hydroxyl close to thecharged C15 resulting in a large (5.1 kcal/mol)drop in the interaction energy. At about t ¼ 21 nsthe Ser186-Thr94 H-bond is broken and a largeincrease in the energy of the Ser186 occurs, becauseits hydroxyl moves away from H16 on the retinal.The Thr94 hydroxyl does not change position andits energy remains constant.

The interaction energy for Ala292 with Lys296(Figure 6(d)) also has a sharp transition in thevicinity of t ¼ 10 ns as well as several up/downtransitions of the same magnitude at other times.

The behavior is indicative of a two-state system.The energy distribution does have two peaks withenergies at 23.2 and 28.4 kcal/mol. The source ofthese strong interactions is the backbone oxygenof Ala292 interacting primarily with the retinalhydrogen H15. As pointed out earlier in the discus-sion of the dihedral dynamics of the retinal chain(Figure 3), the retinal H15 is affected by dihedraltransitions within retinal. These transitions changethe separation distance between the Ala292 oxygenand H15, altering the pair’s interaction energy.

The retinal dynamics also strongly influences theinteraction with the Glu181 residue, which has fre-quent large transitions as shown in Figure 6(e).

Figure 6. Time series of selected residues’ interactionswith retinal. Interactions are split among Lys296, retinalchain and retinal ring as defined in Figure 5. The timeseries are for (a) Ser186 interaction with the Lys296;(b) Ser186, (c) Thr94, (d) Ala292 and (e) Glu181 all inter-acting with the retinal chain. For clarity, the data havebeen smoothed using a 50-bin boxcar average, whichremoves the high-frequency fluctuations.


The interaction energy for Glu181 with the retinalchain ranges widely from 240 kcal/mol to225 kcal/mol. The fluctuations are large, in partbecause of the strong electrostatic character of theGlu181 interactions. Small changes in distancebetween Glu181 and retinal yield large energeticvariations. The interactions are thus very sensitiveto retinal’s and its own dihedral dynamics. Thedistribution has a main peak at 231 kcal/molwith a weak shoulder peak at 236 kcal/mol. Oneespecially large transition occurs at t ¼ 14:6 ns andinvolves a drop in energy of 11 kcal/mol. This cor-relates with the beginning of a series of dihedralflips in Glu181 (Figure 3). The dihedral dynamicscorrelates well with a two-peak interaction energy,since the dihedral angle is predominantly 658, butspends a minor, but significant fraction of its timeat an angle of 1688.

We have calculated the cross-correlation func-tions between some of the dihedral angles inFigure 3 and the interaction energy of the sameresidue with retinal in Figure 6. For Thr94 weobtain a correlation coefficient of 20.925, whichshows that almost all of the changes in interactionenergy for Thr94 are due to its dihedral dynamics.For Ser186 the correlation coefficient has a smaller,but still large value of 0.59. This implies that someof the interactions involve structural transform-ations other than the dihedral transitions inSer186. These transformations could be thedihedral transitions in the retinal molecule ornearby side-chains. The correlation coefficient forGlu181 is 20.14, a low value. This is not surprising,given that Glu is a charged residue and thereforehas a larger interaction range including the entireretinal molecule. Not all of the retinal dihedralsare in sync with the Glu181 dihedral. Thus, notsurprisingly, the correlation coefficient is low.These three cases show that when the interactionenergy and the structural dynamics are stronglylocalized the correlation can be very strong. As theinteraction range increases, the number of struc-tural transformations within this range that canoccur increases. The time correlation is then likelyto be small as the events become uncorrelated.

Summary of section

In summary, for this sub-section, we have identi-fied the interactions that exhibit significanttransitions during the simulation. As above for thetime-averaged interaction energies, and thedynamic transition energies, retinal was split foranalysis into three parts: Lys296, the retinal chain(C7–C15) and the retinal ring (see Figure 5). Thereare a large number of transitions evident from thetime series of these interaction energies. We charac-terized the structural changes that occur with theenergetic transitions. We then highlighted signifi-cant interaction sites and the significant transitionsthat occur during the simulation. We find corre-lated dynamics. In particular, there are manyevents that occur near t ¼ 10 ns. These events are

connected to the dynamics of whole helices, whichwe discuss next.

Large-scale motions

There is evidence from SDSL (cited above andmore in discussion below) that rigid body motionof helix VI relative to helix III could be part of thelight-activated photocycle. This type of large-scalerigid body motion is intriguing, at least partlybecause it may be a common dynamic motion forother hepta-helical receptors. Even bacterio-rhodopsin (not a canonical GPCR) has similarrigid body motions. Thus, we wanted to examineour simulation carefully for possible rigid bodymotions and also wanted to understand, ifpossible, whether any of the observed rigid bodymotions could be connected to other changes (e.g.near the retinal-binding site) of rhodopsin.

Figure 7. Helix tilt angle as a function of time. The tiltangle dynamics shows that large-scale conformationalchange is present in the 40 ns simulation.


Changes in helix tilt

Figure 7 shows the tilt angle ut for some of theseven transmembrane helices over the 40 nsproduction run time. The tilt angle calculationinvolves a best-fit cylinder to the helix axis and acalculation of the angle of that cylinder relative tothe bilayer normal for each saved conformation ofthe dynamic trajectory. We have split the helicesinto sections based on kinks and intrinsic bends.The legend gives the residue ranges used in thecalculations. Besides the fast fluctuations of a fewdegrees, the range between the minimum andmaximum tilt angle is about 158 for each helix. Asexpected, this shows that the seven helix trans-membrane protein is not a rigid object, but adynamical one with various dynamical modes.However, it is expected that the movementinduced by the retinal isomerization would be dis-tinct from what is seen here and would be a tran-sition to a different state, with its ownfluctuations, rather than a fluctuation within thisstate.

An examination of the tilt angle data in thevicinity of t ¼ 10 ns shows multiple changes in thetilt angle beyond simple fluctuations. As Figure 7shows, helices I, II, V and VII have relativelysharp changes in their tilt angles at this time.Helices III and VI exhibit small changes in thisperiod as well. As noted in the discussion of thedynamics of residue interaction energies withretinal, there are several significant transitions thatoccur in the vicinity of t ¼ 10 ns. The complexityof the multiple helix and individual residue inter-actions makes deciphering the cause-effect relationintractable. However, the existence of a correlationis strong and clear.

Changes in helix kink

Changes in helix kink reflect a possible func-tional role that they may play in rhodopsin protein,similar to, and perhaps greater than, the importantrole of helix tilt in modulating overall protein con-formation and thus G-protein coupling. Threehelices, II, V and VII, are known to have significantkinks.29,30 Figure 8 shows the kink angles uk as afunction of time for the three helices. The kinkangles fluctuate within the vicinity of the kinkangle found in the X-ray structure. The generalcharacteristics of each helix’s uk are that they varyacross a range of about 208 for the 40 ns timeperiod, and that on the picosecond time-scale, fluc-tuations have about a 108 span. Again we findsome significant events occurring in the t ¼ 8–12 nsrange. The kink angle centered at Pro291 in helix VIIhas a sharp transition at about t ¼ 11:5 ns with areverse transition (less sharp) at t ¼ 26 ns. The kinkangle centered at Pro303 in helix VII has narrowdips in uk at t ¼ 5 and 11.5 ns. The kink angle inhelix V has a minimum at about 11.4 ns. There alsois evidence for correlated kink dynamics neart ¼ 22 ns. The kink angle in helix II rises steadily

to a maximum at t ¼ 22 ns and then decreases rela-tively sharply. This maximum occurs at the sametime the kink angle centered at Pro303 for helixVII starts a slow decrease. The kink angle datashow there is significant large-scale motion on the40 ns simulation time-scale and that the motion iscorrelated.

Changes in helix precession

In addition to asking about changes in helix tiltand helix kink, we can address the amount ofprecession relative to the bilayer normal that eachhelix undergoes during the simulation. If a helixwere rigidly locked into conformation within therhodopsin structure, then the helix would see nochanges in helix tilt, kink or precession. We com-puted fluctuations for the precession angle of eachhelix and again find that there is considerable

Figure 8. Changes in helix kink angle during thetrajectory. The kinks are centered at the followingresidues: H-II (Gly89); H-V (His211); H-VII(a) (Pro291);and H-VII(b) (Pro303). The lines indicate the kink angledetermined from the X-ray structure.


motion. The helices had fluctuations of, on averageten degrees on the picosecond time-scale, and typi-cally covered ranges of 50 degrees over the courseof the 40 ns simulation. The most nearly perpen-dicular helix, helix IV, traversed nearly the entirerange of precession angles.

Hydrogen-bonding networks

We believe that changes in hydrogen-bondingnetworks could be important in the isomerization-driven signaling mechanism. Thus, we providesome insights into the changes of hydrogen bond-ing between helices during the simulation. Clearly,this type of analysis involves a large amount ofdata and some arbitrary assumptions about whatconstitutes a hydrogen-bonding interaction (theCHARMM potential does not use an explicit termfor hydrogen bonding). Thus, while the analysismay produce different results with modifiedassumptions, the relative changes in the hydro-gen-bonding networks should be functionallyrelevant and are thus emphasized.

Analysis of the X-ray structure has led severalgroups1,29,30,78 to suggest that certain interactionsbetween helices are important for maintaining theoverall structure and may contribute to thedynamics. In particular, they have identified threewell-defined networks of hydrogen bonds betweenhelices and an additional fourth possibility. Weanalyzed the three well-defined networks. Net-work I is between helices I to II, II to VII, and I toVII (Table 1). Network II involves helix II to helixIII and helix II to helix IV (Table 2), and networkIII involves helices III, V and VI (Table 3).

We computed time averages and dynamic inter-action energies for these three networks. Figure 9shows that hydrogen bond network II has major

energetic transitions at two points in the trajectory.The first major transition is near 10 ns and reflectsan increase in the attractive interaction energyfrom about 2100 kcal/mol to about 2150 kcal/mol. As we discuss later for Figure 13 this is largelyan effect of a change in interaction between Glu113and Thr94. A second transition and then transitionback again occurs near t ¼ 20 ns. In contrast, thehydrogen bond networks I and III showedrelatively constant time evolutions with no majortransitions like that seen in the second network.

Lipid and water interactions

There has been discussion in the literature of thepossible role of boundary lipids in membraneprotein function. The original definition involveda relatively long time-scale for lipid exchange, andis thus clearly not a reasonable way to determinewhich lipids are boundary lipids for relativelyshort molecular dynamics calculations. Still, weexpect that a boundary lipid can be defined, atleast partially, as a lipid that has much higherenergetic interactions with the protein than withthe other lipids. This definition naturally leads toquestions about the details of the interactionsbetween the lipids and the protein. Can we startto rationalize the finding that rhodopsin function

Table 3. The hydrogen-bonding network III is defined byinteractions between the helices (III,VI), (III,V) and (V,VI)

Site 1 Site 2 Eave SD

Glu247 Arg135 2216.42 10.21Thr251 (side

chain)Arg135 2171.55 4.54

Glu134 Arg135 2157.92 9.62OE1, OE2 of

Glu122HD1, HE1, HD2 ofHis211

2125.89 5.98

OE1, OE2 ofGlu122

HD1, HE1, HZ2 ofTrp126

281.51 8.85

Trp126p His211p 55.23 3.58

Ring interactions are denoted by p.

Table 1. Hydrogen-bonding network as defined by inter-actions


OD1, OD2 ofAsp83

HD21, HD22 of Asn55 291.96 5.98

OD1, OD2 ofAsp83

HG1 of Ser298 287.28 6.02

OD1, OD2 ofAsp83

HB1, HB2, HB3 of Ala299 228.18 3.81

O† of Ala299 HD21, HD22 of Asn55 212.20 1.24OE1 of Gln64 HG21, HG22, HG23 of

Thr320211.99 3.22

OD1 of Asn55 HB1, HB2, HB3 of Ala80 210.65 1.81OD1 of Asn55 HB1, HB2, HB3 of Ala299 24.55 0.77OD1, OD2 of

Asp83HN of Val300 218.96 1.42

Tyr43p Phe293p 42.07 3.13Tyr43p Phe294p 42.54 3.11

Hydrogen-bonding network I involves interactions betweenhelices (I,II), (I,VII), (II,VII) and some (I,VIII). Site 1 and 2denotes the interaction pairs which can be hydrogen bondacceptor/donor pairs, ring:ring cation pi interactions and salt-bridge ion pairs. The default interaction is a hydrogen bond;ring interactions are denoted by p ; backbone interactions by †.The site:site interaction energy average ðEaveÞ and standarddeviation (SD) are given.

Table 2. Hydrogen-bonding network number II isdefined by interactions between the helices (II,III),(III,IV) and (II,IV)


OE1, OE2 ofGlu113

HG1 of Thr94 287.57 27.24

OG of Ser127 HD21, HD22 of Asn78 242.35 9.14OG1 of Thr160 HD21, HD22 of Asn78 239.13 10.29OD1 of Asn78 HE1 of Trp161 232.23 4.61OE1, OE2 of

Glu113HG21, HG22, HG23 ofThr94

220.66 3.04

OE1, OE2 ofGlu113

HB of Thr94 211.01 1.84

O† of Phe159 HD21, HD22 of Asn78 27.02 1.55Trp126p Met163 61.13 3.93

The default interaction is a hydrogen bond; ring interactionsare denoted by p ; backbone interactions by †. The site:site inter-action energy average ðEaveÞ and standard deviation (SD) aregiven.


depends on lipid type? To examine this issue, inFigure 12 we present histograms of lipid inter-action energies.

The role of the water and water/lipid transitionregion in membrane protein function will also beimportant. We expect that the conformations ofthe loop, and N and C-terminal tails will be criticalfor G-protein coupling and will be stronglyinfluenced by their interactions with water. Thusan analysis of the energetic interactions of waterwith various regions of the protein gives someindications of those regions that are more definedby solution (water) interactions than by membrane(lipid) interactions.

Changes in solvent-accessible area

Consideration of the water and lipid-accessiblesurface areas for each helix and loop region pro-vides further insight into the role of the solvent.By comparing in Table 4 the amount of water-exposed area on each helix, we note that somehelices (e.g. helix VII) have little water-exposedsurface area, while others (e.g. helices II and III)have a factor of nearly 10 more water-exposed sur-face area. Similar differences are observed for thelipid-exposed regions. As will be discussed later,we find a transition in solvent-accessible areaduring the calculation. This could be importantfor function, since the G-protein coupling mayinvolve changes in water-accessible regions andbinding of G-protein to rhodopsin will clearly bedictated by relative accessibility.

Solvent interaction energies

Treating each helix as a separate interactionmotif, we computed histograms of the interaction

energy between the helix and all of the water, allthe lipids or the remaining protein. The results aregiven in Table 5. In each case, the netprotein interaction was stronger than that fromthe lipid. Interestingly, the interaction withwater was stronger than that for protein for someconformations of helix IV during the simulation.Otherwise, for the remaining helices, the inter-action from water to helix was less than that forhelix to protein interaction. As we compare therange of helix to water and helix to lipid

Figure 9. Changes in the total energy within thehydrogen bonding network II. Smaller fluctuations wereobserved in the first and third hydrogen bondingnetworks.

Table 4. Accessible surface areas (A2)

Lipid Water

Helix I 1356 ^ 69 44 ^ 22Helix II 439 ^ 44 139 ^ 26Helix III 331 ^ 34 151 ^ 43Helix IV 840 ^ 45 210 ^ 40Helix V 931 ^ 56 43 ^ 19Helix VI 642 ^ 49 132 ^ 45Helix VII 583 ^ 31 19 ^ 13Helix VIII 247 ^ 49 157 ^ 78N-terminal 4 ^ 5 1966 ^ 73C-I loop 17 ^ 8 351 ^ 57E-I loop 107 ^ 30 88 ^ 33C-II loop 108 ^ 39 688 ^ 70E-II loop 60 ^ 26 649 ^ 63C-III loop 113 ^ 35 1473 ^ 136E-III loop 6 ^ 6 318 ^ 54C-terminal 22 ^ 18 1963 ^ 221

Table 5. Interaction energies for each helix with itssurroundings

Energy (kcal/mol)

Self Protein Lipid Water Total

Helix I Average 429 2270 2154 261 255Stdev 17 20 18 17 21Max 493 2219 2105 26 10Min 372 2345 2208 2120 2123

Helix II Average 369 2375 2141 2137 2284Stdev 18 23 25 30 23Max 431 2301 264 255 2200Min 304 2450 2222 2244 2349

Helix III Average 243 2639 252 2196 2644Stdev 18 37 9 30 27Max 307 2506 218 2111 2513Min 158 2726 289 2314 2725

Helix IV Average 456 2211 2154 2252 2161Stdev 19 32 26 42 26Max 523 2110 271 2103 255Min 400 2307 2246 2387 2252

Helix V Average 486 2304 2146 2170 2134Stdev 18 15 23 30 23Max 547 2256 282 272 255Min 423 2368 2227 2257 2206

Helix VI Average 430 2430 2188 2209 2397Stdev 25 50 40 62 31Max 501 2279 265 275 2264Min 332 2545 2270 2434 2492

Helix VII Average 542 2454 274 254 240Stdev 19 14 17 14 19Max 608 2403 234 29 44Min 489 2508 2112 293 2102


interactions, we note that helix I had muchstronger lipid than water interactions, some helices(III,IV) had stronger water than lipid and somehelices (II,V,VI,VII) had nearly equal interactions.Furthermore, the fluctuations in the interactiondistributions varied enormously from one helix toanother, suggesting a dynamic range of contri-butions from the environment. For example, helixVII has a narrow and small contribution from bothlipid and water. Helix III has a narrow range oflipid interactions energies, but a broad range(centered on 2200 kcal/mol) of water interactionenergies.

We can get additional insight into the importantrole of the environment by consideration ofselected individual residue interaction energieswith the environment. We examined residues thatare believed to also have some role in the overallrhodopsin function and not simply those mostwater or lipid-exposed. The amino acid residueswith strongest interaction with water are those inthe N-terminal, cytoplasmic, extracellular or loopregions. For example, the glutamine residues 5, 25,and 33 in the N-terminal region have large electro-static interactions (2165, 2 133, 2 149 kcal/molon average). In addition, we observe a set ofamino acid residues that have strong interactionswith the lipid setting. An example is Trp161 witha strong van der Waals (vdW) interaction of 27.2and Glu201 with an electrostatic interaction of230.3 kcal/mol. The Glu201 is at the lipid–waterinterface as one would expect for a strong electro-static interaction. Lastly, we see particular aminoacid residues with especially strong energeticcoupling to the rest of the protein. An example ofthis is Arg135, with 2270.7 kcal/mol of electro-static interaction energy to the protein.

An example of the connection of accessible areaand energetics to structure is seen in the C-terminalloop dynamics. Visualization of the C-terminalloop trajectory shows part of the loop appears tobind to helix VIII. Residues 336 to 339 begin toalign parallel with helix VIII at t . 14 ns andachieve a steady-state structure by t ¼ 19 ns. Theinteraction energies and the water/lipid-accessibleareas for the C-terminal loop change as thestructural transformation occurs. Figure 10 showsthe energies of the C terminus interacting with thewater, lipid, and protein as a function of time. Thewater energy is the strongest interaction of thethree and is attractive. The protein interactionenergy is net positive, implying a net repulsion.The mean water interaction increases by about200 kcal/mol from start to finish. Figure 11 showsthat the mean water-accessible area decreasessteadily from 2500 A2 to about 1700 A2. Thus,much of the decrease in water interaction energyis due to the depletion of the water around the Cterminus and in particular between the C terminusand helix VIII. This is consistent with the bindingof part of the C terminus to helix VIII, and the con-comitant expelling of intermediate water.

There are more subtle details. Initially, the water

interaction energy is undergoing a cyclic behaviorwith a 6 ns period (see Figure 10). The kink anglein helix VII (about Pro303), which is next to theC-terminal loop, also undergoes a 6 ns periodicmotion in the same time-period (see Figure 8). Theend of the third cycle would be at 18 ns, by whichtime the loop has structurally changed and thewater interaction changes too. Thus, we have thekink angle dynamics of helix VII correlatedwith water interaction energy dynamics of theC-terminal loop, which is restructuring and bind-ing to helix VIII. (Helix VIII connects helix VII andthe C-terminal loop.) As we would expect, thisexample shows that large-scale motion such ashelix motion is correlated with the motion andenergetic dynamics of neighboring large-scalestructures (helices, loops, or tails).

The restructuring of the C-terminal loop is alsoseen in the interaction energies with the lipids andprotein. As the water interaction increases,Figure 10 shows the protein interaction decreasesby about 150 kcal/mol. A more favorable inter-action has been made as the loop binds to helixVIII. The interaction with the protein is net nega-tive at t ¼ 13 ns when the residues 337–339 arebeing pulled toward helix VIII. There is a longsteady decrease in the protein interaction energyfor t . 20 ns. This correlates with increase inwater interaction energy and the decrease in lipidinteraction energy. At about t ¼ 19 ns a transitionappears in the lipid interaction energy. Once theC-terminal loop has formed its new configuration,the lipids appear to reorganize, minimizing theirinteraction energy. The lipid-accessible area

Figure 10. Interaction energy as a function of time forthe C-terminal loop with the water, lipid and solvent.


increases during the run with a large transition att ¼ 20 ns coinciding with the energetic change inFigure 10.

We finally note that the C-III loop also shows sig-nificant motion, as one might expect for such along loop. Initially, the loop is bent back down onthe outside of the protein, but within 6 ns it movesto being bent away from the protein into the cyto-sol. The interaction energies with the water, lipidand protein are not as dramatic as for the C-term-inal loop, but there is a noticeable drop in thewater interaction energy of about 150 kcal/moloccurring in the first 10 ns when the loop ischanging its orientation. The protein interactionenergy has a maximum at about t ¼ 10 ns.Figure 11 shows that the water-accessible areaincreases in the first 6 ns when the loop is extend-ing into the water.

Discussion

The current molecular dynamics calculationsprovide initial insights into the coupling betweenlocal changes in the retinal-binding pocket andlarger conformational changes in the whole pro-tein. These larger changes, in turn, should connectinto the G-proteins that underlie signal amplifica-tion and transduction in this system. Though wedo not explicitly analyze the simulations for com-parison to other GPCRs, some features may wellbe common among the rhodopsin system andother GPCRs.

One key finding from the results should beemphasized at this point. That is, much of therhodopsin literature is filled with site-directedmutations and single pathway schemes thatstrongly imply that a particular amino acid or aparticular defined sequence of events is the under-lying key for light-activation of rhodopsin. Thecurrent simulations suggest that no single amino-acid dominated view is going to capture the coop-erative nature of interactions and transitionswithin the system. In other words, the collectivenature of the motions leads to a stabilization ofthe dark-adapted state and to a focused ability ofthe current system to eventually respond to thelight activation. We do not explicitly simulate thelight-dependent changes and the activation ofthe G-proteins, but the process of fluctuations inthe dark-adapted state are part of the pathwayto the light-adapted state. Eventually, this leadsthrough collective motions in response to a lightactivation, to a functional change.

Further emphasizing this finding of oursimulation exploring collective behavior near thedark-adapted state is that we do not see an 11-cisisomerization within the simulation. This is con-sistent with evolutionary pressure to produce asystem that responds in exquisite detail to thepresence of the light event. That is, we do notexpect that the fluctuations within the dark-adapted state will be strong enough energeticallyto produce a high likelihood of a transition intothe light-adapted state. The fact that we do seelocal transitions that couple into large-scale helixtransitions is demonstrative of the types ofcoupling from a local light adapted change to alarger G-protein signaling that we expect in thefull photocycle.

Certainly there is a great wealth of molecularinformation in the simulations and we cannotpresent, or even analyze, all possible events. Toframe our discussion of the results presentedabove we have elected to pursue four themes inmore detail: (1) the importance of hydrogenbonding and salt-bridge networks; (2) thepossible role of lipids in modulating functionalbehavior; (3) the large changes seen in the cyto-plasmic loops and C-terminal region; and (4) thepossible coupling of local structural changes tolarger scale changes in the protein as seen fromthis simulation.

Figure 11. Changes in solvent-accessible surface areaduring the simulation for the C-terminal domain andthe cytoplasmic loops: C-I, C-II, and C-III.


Importance of interaction networks

We analyzed both the local hydrogen-bondingnetwork surrounding the retinal and the networkof interactions between helices and between helicesand the solvent. At each stage we see some net-works that remain strongly coupled throughoutthe simulation (e.g. hydrogen-bonding network I)and others that dynamically evolve during thetrajectory (e.g. hydrogen-bonding network II). Aswe have already emphasized, the secondhydrogen-bonding network (between helices IIand III, helices III and IV and II and IV) showed amajor transition to a lower energy form (roughly240 kcal/mol moving to 2100 kcal/mol). A majorpart of this transition was a change in the strengthof the hydrogen bond between the oxygen atomsof the Glu113 side-chain (OE1, OE2) and the HG1of the Thr94 side-chain (the hydroxyl hydrogen).This type of change appears to have been initiatedby a change in the local orientation of side-chainsaround the retinal group that then led to the largechange in the hydrogen-bonding network (seeFigure 13). As noted in the discussion of tilt angledynamics, several of the helical sections undergolarge changes in tilt angle at this time. Figure 13shows a blow-up of the increase in the tilt angle ofhelix I from 338 to 458 within a nanosecond oft ¼ 10 ns. These results further emphasize thecooperative nature of fluctuations and thusdynamics in this system (Table 6).

In addition to hydrogen bonds, salt-bridges areimportant to interaction networks. The crystalstructure29,30 suggested a strong salt-bridgebetween residues Glu134 and Arg135, and thiswas also emphasized in review articles.1 We com-puted the interaction energy between this salt-

bridge and the alternative salt-bridge betweenGlu247 and Arg135. This latter salt-bridge hasbeen suggested as part of the transition into theM-II state.1 We find that the Glu247 to Arg135 salt-bridge is much stronger (a factor of roughly 2)than the first bridge. However, both salt-bridgesare present energetically throughout the

Figure 12. Histograms of interaction energies for indi-vidual lipid molecules. Shown are the distributions oflipid self-energies as well as interaction energies betweenindividual lipids and the other lipids, water, protein, andthe total interaction energy. This suggests the importantrole of solvent for the system.

Figure 13. Local changes around the retinal bindingpocket can lead to larger changes via coupled changesin the local binding interactions, changes in the hydro-gen-bonding network and then to changes in helix tilt.This Figure shows changes in three dihedral angles ofside-chains near the retinal, and the change in interactionenergy of the Glu113 interaction with Thr94 (part of thesecond hydrogen-bonding network). The large changein the tilt angle of helix I is one example of a large-scalemotion.


dark-adapted rhodopsin simulation. This suggeststhat the electrostatic coupling in the system isstrongly present throughout the protein and thatchanges in the relative balance of electrostaticsmay be more revealing than arguments of an allor none nature (i.e. suggesting that a salt-bridge isfully present or fully absent).

Possible effects of lipids

Both lipid and water play a role in coupling theprotein motion and the degree of relative strengthsof residue:residue and residue:retinal interactions.We would not expect the same type of dynamicsto be observed in a different type of bilayer or in abilayer mimic. Thus, the solvent (meaning bothwater and lipid) plays an important role in modu-lating the types and strengths of interactions thatare present in the simulation. The surface tensionmay have an important effect on the ability ofrhodopsin to change conformation and forcoupling to occur between G-proteins and therhodopsin protein. This idea of a coupling betweenthe mesoscopic properties of the lipid bilayer andthe transition from dark-adapted to M-II rhodopsinhas been tested by the Brown group.7 – 11,79 Theinitial results from our simulation do not directlycomment on the mixed lipid systems that Brownet al.7 – 9 used, but we do find intriguing the typesof specific interactions as seen in Figure 12. In par-ticular, a mechanism related to surface tensioneffects is specific lipid:protein interactions beingimportant in defining the energetic barriers to tran-sition. This is also consistent with experiments.80,81

As emphasized in Results, we observed a widerange of helix coupling to the lipid environment.Some of these results are presented in Table 5.These varied from the relatively weak coupling ofhelix III to the much stronger, and more broadlydistributed coupling of helix VI. These two helicesare especially intriguing due to suggestions thatrigid body motion of these two helices (and/orhelix IV) could underlie the M-II transition. HelixVI has been especially strongly singled out as acandidate for rigid body motion. Since simulationsshow that the coupling to lipid is so broad, thissuggests that changes in lipid type (and/or surfacetension) could have a broader effect on the M-IItransition due to coupling with helix VI than withany other helix. In other words, the distribution ofhelix:lipid interaction energies is consistent withthe experimental observation of a lipid dependenceto the M-II transition that is coupled through thetypes of energetic fluctuations possible betweenhelix VI and the environment.

It is also interesting to note that helix VII (contain-ing the retinal) has a bifurcated distribution for thehelix:lipid interaction with maxima at about 260and 290 kcal/mol. This suggests a type of meta-stable arrangement to the helix:lipid interactionsthat could also be important for the M-II transition.

In a similar way to the lipid:helix interactionenergies, it is interesting to note that the helix:water interactions show a similar trend; helix VIhas the widest distribution of possible energeticinteractions. In particular, in some time periodshelix VI has the strongest conformational couplingto the water and in other periods it is the thirdweakest helix for coupling to the water. If thedegree of water coupling is varied through lipidtype and or through lipid surface tension, thenthis also could be an important mechanism for theenvironmental regulation of the M-II transition.

Motions in C-terminal and cytoplasmic loops

Site-directed, spin-labelling (SDSL) and NMRhave both suggested that the C-terminal region ishighly mobile on the nanosecond time-scale.72,82,83

Our simulations confirm this suggestion andfurther suggest the C-terminal region couldundergo large changes in conformational environ-ment that could be important for preparing aneffective binding site for the G-protein interaction.This is also consistent with mutagenesis results.76,84,85

A recent review by Klein-Seetharaman6 bringstogether many aspects of SDSL and NMR analysisfor comparison to the X-ray structure. In particular,several SDSL studies have shown large mobility inthe C-terminal domain.56,71 Likewise the cytoplasmicloop between helices V and VI has been studied86

and similar conclusions drawn about the mobility.The involvement of the C-II and C-III loops inG-protein binding was shown by Acharya et al.87

The coupling between rigid body motions of thehelices and the C-terminal and loop regions isanother aspect of the trajectory that we findintriguing. While it is difficult to precisely deter-mine the cause and effect for the large changes inlipid and water-accessible surface areas during thesimulation, it is reasonable to suggest that thechanges in solvent accessibility are driven by thesame rigid body motions of the helices that werefirst initiated by the local changes in the retinalbinding pocket. That is, the changes in accessibilityfirst start to occur at about t ¼ 10 ns. Then as timeprogresses the changes become more dramatic untilabout t ¼ 20 ns. Beyond then the lipid accessibilityremains relatively constant, while the water accessi-bility changes only moderately. This is intriguing,because it suggests that changes in the helix tilt(rigid body motion) could drive changes in the localenvironment of the C-terminal and C-III regions.Since these regions are clearly coupled to G-proteinsignaling, it then is reasonable to suppose that thefluctuations seen in the trajectory that triggered thetransition near 10 ns are similar to the types ofchanges that occur with cis–trans isomerization and

Table 6. Energy (kcal/mol) in hydrogen-bonding networks

Network I Network II Network III

Ave 2134.85 2126.15 2298.18Min 2163.76 2178.14 2337.53Max 2101.36 238.89 2241.20Stdev 9.49 26.99 13.07


the M-II signaling transition that activates G-pro-teins. While the G-protein signaling and activationare clearly not part of the current model, these largechanges in conformation of cytoplasmic domainsthat are initiated by changes in other parts of the pro-tein system are very intriguing.

Coupling local changes to largerconformational changes

The results suggest a set of pathways thattogether couple the local changes in the retinalenvironment with larger conformational changes.This is neither the steric switch suggested byNMR experiments nor the local-and-independent-domains view of protein motion. Instead, what thesimulations appear to suggest is that the confor-mations visited are a reflection of relatively tightcoupling between multiple regions of the protein(not independent units) and of a range of couplinginteractions (i.e. not a single residue that is rigidlymoved by a change in the retinal conformation).Another way of phrasing this is that there is arange of motion types and amplitudes throughoutthe simulation and that coupling occurs boththrough direct residue:residue and residue:solventinteractions as well as through indirect hydrogen-bonding networks such as we see in the secondhydrogen-bonding network.

Relatively recent work with chromophore cross-linking88,89 suggests a model where isomerizationleads to changes in helix IV and helix VI with theretinal coming close to Ala169 in the Meta II state.There are several intriguing implications from thesimulations. First, the least strongly interactinghelix with other parts of the protein is helix IV.The distribution is bimodal with a second lowerpeak from about 2150 kcal/mol of interactionenergy. This may reflect that this helix, the shortestand most nearly vertical, is capable of performingthe type of motion suggested in the model. Second,helix VI has a long-tailed distribution from a stronginteraction energy towards a much weaker inter-action with the rest of the protein. The energyvaries from a distribution peak at 2450 kcal/molto a set of weaker interactions around 2300 kcal/mol. This distribution is the widest of all theseven helices. It suggests that fluctuations in thehelix interaction energy, coupled with the light-driven isomerization change could drive largehelix motions, such as suggested in the citedmodel. Other experimental work60,90 is also con-sistent with the thought of rigid body helixmotions for the transition to the M-II state.

It is interesting to speculate on the possiblestructural changes that might underlie the M-IItransition from our calculations. The results areconsistent with an opening of the cytoplasmicdomain and with rigid body motion of the helices.This is especially true for helix VI, where we seebroad interaction distributions and evidence of adifferent class of mobility relative to the otherhelices. It is possible that the M-II transition

involves changes in the cytoplasmic accessibility,and in the tilt of helix IV, as well as in the tilt ofhelix III, the most tightly coupled of the helices.Recent work from the Yeagle group91 is also con-sistent with these ideas.

A further point of comparison is with the largenumber of other class A GPCRs. It appears thatmany of the most conserved residues in theseprimary sequences have important roles inrhodopsin function. Furthermore, the details ofcoupling to G-proteins through changes in thecytoplasmic loops and C-terminal region seem tobe conserved.92 – 97 It will be interesting to see if theregions from the extracellular loops interactingwith the retinal chromophore will also be involvedwith transitions and binding in other GPCRs.2,98,99

Conclusions

This is an exciting time for those interested inGPCRs and G-protein mediated signaling systems.The recent X-ray structure of bovine rhodopsinand the large amount of primary sequence infor-mation suggests that we may soon be able tounderstand the molecular events that drive signalrecognition and signal amplification at a molecularlevel. The current simulations should be viewed asan initial step towards the fuller connection of mol-ecular structures with molecular function througha detailed understanding of the range of motionsthat are available to the system. While we do notclaim to have understood the full details of light-driven isomerization and the coupling of thatmotion change to eventual signaling and amplifica-tion, the simulations do provide an initial view ofthe types of conformations available to dark-adapted rhodopsin within a lipid bilayer setting.We feel that the calculations elucidate the possibletypes of coupling seen between local and large-scale protein change that may be important for thelight-driven coupling underlying visual function.

Methods

We aimed to examine the effects of the lipid environ-ment on rhodopsin structure and motion and thus built,from the start, a system to include all-hydrogen, all-atom representations of protein, lipid, and water. Forthis, it was important to use a consistent force-field thatbalanced the energies between each of these types ofmolecules. We elected to work with the CHARMM all-hydrogen force-field (version 22 for protein and version27 for lipids, both released in August of 1999)100,101 andused the parameters defined for retinal within theCHARMM force-field.102 Furthermore, we designed asystem that included at least two lipid molecules sur-rounding the protein in the planar xy-directions. Periodicimages were used in the z-dimension to represent amultilayer system such as studied experimentally byNMR methods.62 The total system size (41,623 atoms)consisted of protein, 99 DOPC lipids, 100 mM salt con-centration (14 sodium, 16 chloride), palmitoylated lipidsattached to Cys322 and 323, and 7441 TIP3 water


molecules. All calculations started from the first X-raystructure of rhodopsin (1F88).29 The CHARMM programwas used for the initial construction of the starting pointand for the relaxation of the system to a production-ready stage. A modified version of the LAMMPS103 codeusing the CHARMM force-field was verified to produceexactly the same energies as the CHARMM code for theinitial conformation. Production then occurred at SandiaNational Labs taking full advantage of the parallel com-putation environment provided by the code and themachines. For comparison, a 1 ps simulation takes312 minutes on the Beowulf cluster at Hopkins usingfour processors and takes just 2.1 minutes on the Cplantcomputer at Sandia using 84 processors, or a factor of150 faster.

Starting conformation

At the time the simulations were started (August2000), the only available structure was the 2.8 A 1F88structure of the original Science paper.29 Near the end ofthe simulation time a second structure (1HZX) with simi-lar resolution (2.8 A), but an improved R-factor wasavailable from the Rutgers Protein Data Bank.32 Evenmore recently, a slightly higher resolution (2.6 A) struc-ture became available (1L9H).33 A visual comparison ofthese structures shows that many of the features of theinitial 1F88 structure remain in the other two structures.The changes are more significant with the later (1L9H)structure, where more water molecules are resolved.33

While we cannot evaluate the effect of the structuralchanges in starting point on our calculations, we expectthat many, if not all, of the general trends reported inthis calculation are not strongly dependent on thepossible alternative starting points. In the X-ray structureof rhodopsin (1F88) a few regions were not well defined.In particular, we used the CHARMM code to build in theregions of the third cytoplasmic loop (236–239) and theC-terminal tail (328–333) for the starting point ofthe simulation. In addition, considerable time was spentestimating possible charge states for side-chains in thestructure. All solvent-exposed titratable groups wereselected in their default ionization state. Less immedi-ately clear is the region surrounding the binding site.Through our initial calculations, we believe that His211,near the binding site should be doubly protonated (þ1).This reflects the arrangement of other atoms in the bind-ing site of the 1F88 structure. Similar to a study ofrhodopsin in a bilayer mimetic environment, we findthat Glu181 is most likely charged.44 Our charge assign-ments are at least reasonable, judged by the stability ofthe structure during the simulation.

Building the lipid bilayer around the protein

The X-ray structure does not reveal where the lipidbilayer is best placed, nor does it reveal the details ofinteraction between a lipid bilayer and the protein mol-ecule. We used a method that has been applied in thepast to gramicidin and alpha helical systems withsuccess.104 – 106 Two ingredients are needed for ourmethod to achieve success. The first is a decision as tothe appropriate cell dimensions for the system that wewill simulate. This requires a trade-off between theideals of a very large system that is run for a very longtime and the realities of a limited amount of CPU timethat scales (roughly) with the square of the number ofatoms. We elected to choose a unit cell that has approxi-

mately two layers of lipids surrounding the centralprotein. This is not an infinitely dilute system where thelipid will reach a bulk (lipid) limit, but at more than40,000 atoms total, this reflects the largest system thatwe felt could be built and run with reasonable efficiency.Furthermore, there are arguments that this type ofsystem is that studied experimentally under the concen-trations of protein and lipid usually used.107 A secondassumption is the appropriate algorithm for thedynamics. Ideally, a constant normal pressure and con-stant surface tension approach would be used thatadjusts the cell dimensions throughout the simulation tomatch experimental values. Unfortunately, currentmolecular dynamics practice has not converged onappropriate methods for constant surface tension ordefined the appropriate value for the surface tension insuch a simulation. We thus elected to perform the calcu-lation using a constant cross-sectional area with constantnormal pressure. This means that the effective (time-averaged) surface tension is determined by the choice ofour lateral cell dimensions. Thus, a second ingredient isthe optimal choice of cross-sectional area for lipid andrhodopsin molecules. We elected to use the valuescollected in a recent review of the lipid experimentalarea (for pure lipid systems)108 and to estimate thecross-sectional area of rhodopsin using the CHARMMprogram. This led to a value of 72.2 A2 per DOPCmolecule and lateral cell dimensions of 55 A by 77 A forthe total unit cell. Given this starting point, the approachcontinues with an assumption that the experimentallymeasured thickness of a DOPC bilayer is near to thatadopted for matching to the rhodopsin system. Sinceexperimental work has shown functional activity ofrhodopsin in a pure DOPC system, this initial assump-tion seems reasonable. Then a series of vdW spheres aredefined with a rough size near the polar headgroupdimensions of a DOPC. The spheres are placed withinthe unit cell dimensions of our simulation and arerestricted to a planar motion regime. Dynamics is runwith the rhodopsin protein fixed and the vdW spheresthen adjusting throughout the simulation to pack wellwithin the confines of the rhodopsin protein and theimages. After the vdW spheres have defined startingpoints for lipid headgroups, the lipid bilayer is con-structed with sampling of lipid conformations from apre-defined lipid library containing states representativeof the liquid crystalline state. We randomly select lipidsfrom the library and place them with headgroup at thecenter of a vdW sphere. This creates a starting pointwith chains, on average, containing the appropriateratio of gauche to trans conformations. It also creates asystem with a large number of clashes between thealkane chains. To remove this strain on the system, aseries of minimizations is then run to slowly relax thealkane chains to a better starting point. After this stagethe water is added into the system and the solvent(water and lipid) is then relaxed through a series of mini-mization and dynamics calculations. In addition to theconstruction of water and lipid for the system, weelected to add neutralizing salt and excess salt to providean electrically neutral system that was similar to exper-imental work for a salt concentration of 100 mM. Inaddition, after initial equilibration, we converted oneDOPC molecule into the two fatty acids covalentlylinked to the protein through Cys322 and Cys323.109

Note that a recent molecular dynamics simulation ofrhodopsin used a bilayer mimetic rather than explicitlipid as performed here.44


Relaxation to equilibrium state

Starting from a system with lipid molecules, water,salt, and palmitylated protein, we wanted to slowlyrelax the solvent (lipid and water) to the optimal state,consistent with the X-ray structure of the protein. Clearlythere are a number of ways to do this and we describeour approach for this simulation. First we wanted torelax the protein only slowly, so as to let all other degreesof freedom adjust as much as possible before the proteinstarted to move. Towards this end we started with theprotein fixed and ran dynamics cycles with electrostaticcutoffs (12 A) and constant temperature (Nose–Hoover)to relax the solvent. This was performed for 50 ps ofdynamics. Then we performed a series of relaxationsteps on the system with the protein harmonicallyrestrained to values near to the X-ray starting point. Forthis step we started at 100 kcal/mol A2 and steppeddown in steps of 10 kcal/mol A2 till the value 50 kcal/mol A2 was achieved This allowed for small adjustmentsto the protein position to further optimize the solventstarting point. The system was then shifted to constanttemperature and pressure with Ewald electrostatics (realspace cutoff of 12 A, sixth order with kappa of 0.320).We started with harmonic restraints on the backbone of100 kcal/mol A2, for 20 ps, then 50 kcal/mol A2 for20 ps, 25 kcal/mol A2 for 20 ps, 5 kcal/mol A2 for 10 ps,2.5 kcal/mol A2 for 50 ps, 1.0 kcal/mol A2 for 50 ps,0.5 kcal/mol A2 for 50 ps, and 0.1 kcal/mol A2 for 50 ps.For these calculations, Nose–Hoover heat-bath couplingwas used for constant temperature at 307 K and whenused, the pressure was coupled to 1 atm. An additional250 ps was performed with no restraints on the proteinbefore production ensued.

Production run and analysis

Initial production was performed with CHARMM ona Beowulf cluster. Performance on the 41,623 atomsystem was reasonable, but not outstanding. Final pro-duction was performed at Sandia National Labs usingLAMMPS on a CPlant computer110 and the performancewas roughly two orders of magnitude better. At peakperformance (100 processors), throughput of 1 ns/daywas achieved. Analysis was performed in CHARMMusing the abilities to interrogate trajectories and/or setsof coordinate files.

Surface area and Voronoi analysis

The accessible area is calculated by use of theCHARMM program where a probe radius is assignedfor either a lipid molecule or a water molecule of thoseregions of the protein that are accessible to a particulartype of environmental (solvent) molecule. Voronoi analysisused the C-program routines of Gerstein.75 In this analysisthe hydrogen atoms are ignored and the full effectivevolume due to the heavy atoms is calculated.

Acknowledgements

Sandia is a multiprogram laboratory operated bySandia Corporation, a Lockheed Martin Company,for the United States Department of Energy’sNational Nuclear Security Administration under

contract DE-AC04-94AL85000. The work at JohnsHopkins was supported under a grant from theAmerican Cancer Society (ACS-RSG-01-048-01-GMC to TBW). L.R.F. was a Royal Society-FulbrightFellow.

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Edited by G. von Heijne

(Received 24 February 2003; received in revised form 19 August 2003; accepted 20 August 2003)


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