The structure of bacteriorhodopsin at 3.0 Å resolution based on electron crystallography: implication of the charge distribution1

Article No. jmbi.1998.2529 available online at http://www.idealibrary.com on

J. Mol. Biol. (1999) 286, 861±882

Ê The Structure of Bacteriorhodopsin at 3.0 A Resolution Based on Electron Crystallography: Implication of the Charge Distribution Kaoru Mitsuoka1,2*, Teruhisa Hirai2, Kazuyoshi Murata2 Atsuo Miyazawa3, Akinori Kidera3, Yoshiaki Kimura3 and Yoshinori Fujiyoshi1,2 1

Department of Biophysics Faculty of Science, Kyoto University, Oiwake-cho Kitashirakawa, Sakyo-ku, Kyoto 606-8502, Japan 2

International Institute for Advanced Research, Matsushita Electric Industrial Co., Ltd 3-4 Hikaridai, Seika, Soraku Kyoto, 619-0237, Japan 3

Biomolecular Engineering Research Institute (Protein Engineering Research Institute), Furuedai, Suita Osaka, 565-0874, Japan

Electron crystallography has the potential to visualise the charge status of atoms. This is due to the signi®cantly different scattering factors of neutral and ionised atoms for electrons in the low-resolution range (typically less Ê ). In previous work, we observed two different types of densities than 5 A around acidic residues in the experimental (jFoj) map of bacteriorhodopsin (bR), a light-driven proton pump. We suggested that these might re¯ect different states of the acidic residues; namely, the protonated (neutral) and the deprotonated (negatively charged) state. To evaluate the observed charge more quantitatively, we re®ned the atomic model for bR and eight surrounding lipids using our electron crystallographic data set between 8.0 Ê resolution, where the charge effect is small. The re®ned model and 3.0 A yielded an R-factor of 23.7 % and a free R-factor of 33.0 %. To evaluate the effect of charges on the density map, we calculated a Ê difference (jFoj ÿ jFcj) map including data of a resolution lower than 8.0 A resolution, where the charge effect is signi®cant. We found strong peaks in the difference map mainly in the backbone region of the transmembrane helices. We interpreted these peaks to come from the polarisation of the polar groups in the main chain of the a-helices and we examined this by assuming a partial charge of 0.5 for the peptide carbonyl groups. The resulting R and free R-factors dropped from 0.250 and 0.341 to 0.246 and 0.336, respectively. Furthermore, we also observed some strong peaks around some side-chains, which could be assigned to positively charged atoms. Thus, we could show that Asp36 and Asp102 are likely to interact with cations nearby. In addition, peaks found around the acidic residues Glu74, Glu194 and Glu212 have different features and might represent positive charges on polarised water molecules or hydroxonium ions. # 1999 Academic Press

*Corresponding author

Keywords: bacteriorhodopsin; electron crystallography; membrane protein; lipid; two-dimensional crystal

Present addresses: K. Murata, National Institute for Physiological Sciences, Myodaiji, Okazaki 444-8585 Japan; A. Miyazawa, MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 2QH, UK; A. Kidera, Department of Chemistry, Faculty of Science Kyoto University, Oiwake-cho, Kitashirakawa, Sakyoku, Kyoto 606-8502, Japan. Abbreviations used: bR, bacteriorhodopsin; 2D, twodimensional; 3D, three-dimensional; RMS, root-meansquare; PGP-Me, phosphatidyl glycerophosphate monomethyl ester with dihydrophytol chains. E-mail address of the corresponding author: [email protected] 0022-2836/99/080861±22 $30.00/0

Introduction Bacteriorhodopsin (bR) is a light-driven proton pump that forms purple membranes, two-dimensional (2D) crystalline arrays, in the plasma membrane of Halobacterium salinarium (Oesterhelt & Stoeckenius, 1971). Absorption of light energy isomerises the retinal chromophore from an all-trans to a 13-cis con®guration, and this isomerisation induces a series of further conformational changes in bR. The resulting photocycle intermediates are characterised as the sequence of K590, L550, M412, N560 and O640, and then bR returns to the original # 1999 Academic Press

862 conformation, completing the photocycle (see Lanyi, 1993, 1997). In the transition from the L550 to the M412 intermediate, bR releases a proton into the extracellular space and in the subsequent transition from the M412 to the N560 state, a proton is taken up from the cytoplasm. Thus, absorption of a photon results in transport of a proton from the cytoplasm to the extracellular space. Analysis of a large number of site-speci®c mutants of bR (Khorana, 1988) together with elecÊ resolution tron crystallographic studies at 3.5 A (Henderson et al., 1990; Grigorieff et al., 1996) have provided the structural basis for the proton pumping mechanism. Two aspartic acid residues, Asp85 and Asp96, lie on opposite sides of the Schiff base and act as proton acceptor and donor from and to the Schiff base, respectively, during the photocycle. Furthermore, Glu204 and Arg82 are known to be involved in the proton-releasing mechanism (Lanyi, 1993). Our previous work (Kimura et al., 1997) indicated that Glu194 is involved in the mechanism for proton release, which was recently con®rmed by site-directed mutagenesis (Dioumaev et al., 1998). However, the distances between these residues clearly suggested water molecules to be involved in the proton transfer mechanism, which was further supported by FTIR studies (Maeda et al., 1997). Grigorieff et al. (1996) proposed probable positions for water molecules based on the location of cavities found in their re®ned atomic Ê resolution model. Recently, a model of bR at 2.3 A based on X-ray structural analysis of microcrystals grown in lipidic cubic phases (Landau & Rosenbusch, 1996) indicated at least three water molecules in the proton pathway (Luecke et al., 1998). All these structural analyses assumed that charged residues and water molecules play essential roles in the proton pumping mechanism. However, it is dif®cult in X-ray crystallography to determine the status of the potentially charged residues, because the scattering of X-rays is not signi®cantly affected by charge. On the other hand, electron scattering is very sensitive to charge, especially at low-resolution (Figure 1(a)). The structure factors of a protein molecule are calculated as the sum of scattering factors of the individual atoms in the protein, and the density map of the protein is calculated by the inverse Fourier transform of the structure factors. Therefore, the density map obtained in electron crystallography has the potential to discriminate a charged atom from an uncharged one even at our current resolution of Ê. 3.0 A Previously (Kimura et al., 1997), we presented a Ê resolmodel for the atomic structure of bR at 3.0 A ution. By comparing the experimental maps (from jFoj and observed phases) calculated with and without low-resolution data, we demonstrated that the charge states of acidic side-chains could be visualised. This allowed us to detect the difference between negatively charged and uncharged acidic residues in the ground state of bR. Here, we pre-

Charge Distribution in Bacteriorhodopsin

sent the electron crystallographic re®nement for our atomic model of bR and the quantitative analysis of the resulting maps to determine the charge distribution in bR. In our analysis, we used the difference (jFoj ÿ jFcj) map, which includes data at Ê resolution, to identify positively less than 8.0 A charged atoms. Some residues, which we assigned as protonated in our previous paper, are thought to be interacting with cations whose positive charge could be visualised in this work and therefore to be unprotonated. Moreover, in the Ê jFoj ÿ jFcj map that includes data at less than 8.0 A resolution, polarisation of the peptide carboxyl groups and some positively charged atoms could clearly be depicted. Thus, using our electron crystallographic data set, we could suggest the charge distribution in the bR molecule.

Results Electron crystallographic refinement The program X-PLOR, usually used in X-ray crystallographic re®nement, was also used to re®ne our atomic model for bR based on electron crystalÊ might lographic data. Because a resolution of 3.0 A be insuf®cient for re®nement based solely on amplitude data, we improved the analysis by including phase observations for the re®nement. This was possible because the phases can be determined directly in electron crystallography from image analysis, which is independent of the diffraction measurements. Moreover, we wanted to determine the charge distribution in bR, which can be done only by using the low-resolution data. Therefore, we used the jFcj map, where high-resolution data were well ®t to the jFoj map by the re®nement, for accurate comparison of the two maps in the low-resolution range. Peaks in the difference (jFoj ÿ jFcj) map could then be used to assess the effect of charges. Re®nement of the model led to an R-factor of 23.7 % and a free R-facÊ and 3.0 A Ê tor of 33.0 % for data between 8.0 A Ê were resolution (Table 1). Data lower than 8 A excluded from the re®nement to keep the lowresolution data independent of the re®nement procedure. The resulting 2jFoj ÿ jFcj map showed an excellent ®t with the re®ned model (Figure 2). No density above the 3.5 s level was observed in the jFoj ÿ jFcj map in the region of the transmembrane helices (data not shown), while some peaks could be observed outside the bR molecules in the lipid region. It should be noted that our electron crystallographic data were reprocessed as described in Materials and Methods. We believe that combination of amplitude and phase data improved the re®nement and contributed to the very good map as mentioned above (also see Discussion). However, one reason for the excellent ®t of our model with the density map might be due to the use of the observed phases in the re®nement. Features in a density map are known to be much more sensi-

Charge Distribution in Bacteriorhodopsin

863

Figure 1. Atomic scattering factors for electrons and X-rays. (a) This graph shows the differences of the electron scattering factors between various ionised and neutral atoms along with the electron scattering factors for ionised and neutral oxygen atoms. The difference between the ionised and neutral germanium atoms is almost the same as the difference in the oxygen atoms, although the difference for lithium atoms does not agree well with that for oxygen atoms. (b) This graph of scattering factors versus resolution demonstrates the different scattering behaviour of electrons and X-rays when scattered by carbon or hydrogen atoms. When the scattering factors of carbon atoms for X-rays and electrons are scaled to almost the same value in the low-resolution range, the values of the scattering factors for hydrogen atoms are signi®cantly different, as shown here.

864

Charge Distribution in Bacteriorhodopsin Table 1. Electron crystallographic table A. Crystallographic parameters Space group (layer group) Lattice constants Thickness

P3 (p3) Ê , g ˆ 120 a ˆ b ˆ 62.45 A Ê (assumed in refinement) c ˆ 100 A Ê (used in LATLINE) 70 A

B. Electron diffraction (amplitude information) No. of diffraction patterns Ê) Resolution limit used (A Maximum tilt angle (deg.) No. of observed reflections Friedel R-factor (%)

339 3.0 70.6 110,812 17.6

C. Electron microscopy (phase information) No. of images Ê) Resolution limit used (A Maximum tilt angle (deg.) No. of observed reflections

181 3.0 61.2 25,225

D. Merged data Ê) Resolution (A No. of unique reflections Merging R-factor (%) Phase residual (deg.) Completeness (%)

3.0 6892 (with amplitudes and phases) 31.3 46.8 78.4

E. Refinement No. of degrees of freedom R-factor (%) Free R-factor (%) Phase residual (deg.) Free phase residual (deg.)

6672 (without hydrogen atoms) 23.7 33.0 54.4 63.3

tive to the accuracy of the phases than the accuracy of the amplitudes (Ramachandran & Srinivasan, 1961). In contrast to X-ray crystallography, the phases can be measured directly in electron microscopy, resulting in good phase statistics, Ê . Phase especially in the resolution range up to 4 A Ê yielded poorer data at resolution greater than 4 A statistics, due to the low signal-to-noise ratio of these data and dif®culties in the correction for beam-tilt, which mostly affects the high-resolution data (Henderson et al., 1986). The phase residual of Ê our model in the resolution range between 8.0 A Ê and 4.0 A calculated from phases used for the re®nement was 45.4  , and the phase residual with phases excluded from the re®nement (free phase residual) was 50.1  . Our re®ned model for bR produced a Ramachandran plot showing that no residue was located in a disallowed regions (Figure 3(a)). Concerning the non-glycine and non-proline residues, only one was located in a generously allowed region (Ser158) of the Ramachandran plot. However, just 77.9 % of the residues were located in the most favoured regions and this is a relatively low value (Laskowski et al., 1993). If the binary classi®cation scheme proposed by Kleywegt & Jones (1996) was applied, the percentage of outliers was 15.8 %, a rather high but acceptable value for an atomic Ê resolution. The electron crystallomodel at 3.0 A graphic data might be a bit overinterpreted in our re®ned model. However, the atomic model, which gave calculated amplitudes very similar to the observed intensities in the high-resolution range

was necessary for a quantitative comparison between the jFoj map and the jFcj map for charge visualisation. The temperature factors for the backbone and Ê2 Ê 2 to 40 A the side-chains were in the range of 2 A (Figure 3(b)). In agreement with previous re®nement work (Grigorieff et al., 1996), high temperature factors were found in the AB and EF loop, while temperature factors in the BC loop, where we found an antiparallel b-sheet, seemed to be relatively lower in our re®nement. In addition, the absolute values of the temperature factors were signi®cantly lower in our model than in the previous work. We think that the improvement is due to the higher quality of our data, especially from highly tilted specimens, which were collected by using a special cold stage designed for data collection at liquid helium temperature (Fujiyoshi et al., 1991), and an improved sample preparation technique that uses trehalose and very ¯at carbon support ®lms (Kimura et al., 1997). Trehalose may have served to stabilise the conformation of the loop regions by replacing water molecules around the protein. The very low values of the temperature factors might be explained, at least partially, by underestimation due to the thermal diffuse scattering, which was observed as halos around Bragg peaks in diffraction patterns of highly tilted specimens. The halos were signi®cantly larger for spots with high Z* values and could have a bigger effect on the integrated intensities for these spots. The re®nement revealed higher temperature factors on the cytoplasmic side of bR when compared to

865

Charge Distribution in Bacteriorhodopsin

Ê resolution. The density is conFigure 2. Stereo views of representative parts of the 2jFoj ÿ jFcj map of bR at 3.0 A toured in blue at 1.0 s, where s is the standard deviation from the mean density of the map. The re®ned atomic model is coloured in yellow. Regions of the map are shown corresponding to (a) the bound retinal, (b) the AB loop and (c) the kink in helix G with the extracellular half of helix F.

those on the extracellular side. Furthermore, zones with high temperature factors were found in the transmembrane helices at the approximate height of the retinal moiety, as shown in Figure 4(a).

Secondary structure After electron crystallographic re®nement, we examined the helical regions, the tilt angles of the

866

Charge Distribution in Bacteriorhodopsin

Figure 3. (legend opposite)

867

Charge Distribution in Bacteriorhodopsin Table 2. Orientation of a-helices and their kinks

Helix

Residues

Tilt angle of the RMS distance to helix to z-axis Azimuth to x the model Angle of kink Ê) (deg.) axis (deg.) a-helix (A (deg.)

Residues in a-helix

A1 A2 B1 B2 C1 C2 D E1 E2 F1 F2

8 to Gly16 Gly16 to 30 37 to Pro50 Pro50 to 62 80 to Pro91 Pro91 to 102 105 to 127 131 to Ala143 Ala143 to 156 165 to Pro186 Pro186 to 196

26.2 23.0 9.25 5.81 3.40 13.4 6.63 9.31 21.5 16.8 6.23

ÿ121 ÿ118 ÿ175 164 148 52 0 ÿ35 ÿ21 ÿ73 ÿ62

0.464 0.719 0.656 0.671 0.751 0.559 0.764 0.667 0.632 0.608 0.289

3.4 (1.019) 4.3 (1.131) 14.1 (1.181) 12.7 (1.131) 10.8 (1.221)

10 to 14 16 to 30 39 to 50 50 to 61 81 to 91 91 to 100 105 to 124 134 to 143 143 to 152 167 to 181 185 to 189

G1 G2

201 to Gly215 Gly215 to 225

13.1 9.26

ÿ115 ÿ41

0.627 0.651

13.7 (1.105)

201 to 213 217 to 224

Conformations other than a-helix

193 to 196 in p-helix

The value in parentheses in the ®eld for angle of kink is the RMS distance of the one long helical region including the kink to the model a-helix. The bending of helix C, E, F and G were more signi®cant than those found in helix A and B, the angles of which were less than 5  . The H-bonded turn regions at both ends of the transmembrane helices were included in the residues in transmembrane helices and the normal a-helical regions were shown as residues in a-helix.

helices, and the positions of kinks within the helices in the re®ned model (Table 2). The helical regions were assigned using the program DSSP (Kabsch & Sander, 1983) as described in Materials and Methods. At two points, the starts and ends of the helices were more than two residues different from those in the previous re®nement work by Grigorieff et al. (1996, 2brd in PDB). These differences were found at the start of helix C (from 77 to 80), where we detected an additional antiparallel b-sheet as reported in our previous work (Kimura et al., 1997), and at the start of helix E (from 134 to 131). All the other transmembrane helices were very similar and the averaged root-mean-square (RMS) distance of the Ca atoms between our model Ê in the memand 2brd was found to be 0.97 A brane-spanning helices. The averaged RMS distance of the backbone atoms between the transmembrane helices of our model and the model helices created by the program MOLEMAN2 (see Materials and Methods) Ê , except for helix D. A more was more than 1.0 A careful examination of the helices showed a bending for helices A, E and G in addition to the wellknown proline-induced kinks in helices B, C and F, though the distortion in helix G was already pointed out by Henderson et al. (1990). In every bending region, irregularities of hydrogen bond networks in the secondary structure were found in our re®ned model. However, the densities around the main-chain of the transmembrane helices could be affected by polarisation from hydrogen bond networks (see Discussion). Thus, polarisation and/

or insuf®cient resolution of our re®nement might cause the irregularities in the secondary structure of these regions. We separated the helices into two pieces and ®tted a model helix for each part (Table 2). The bending angles of helices A and B were less than 5  and therefore less signi®cant compared to the other kinks, the angles of which were larger than 10  . The bending of helices E and G seems to be caused rather by kinks around glycine or alanine residues than by global distortions of the helices. There is an oxygen atom in the backbone (143 O) of helix E that does not make a hydrogen bond to a nitrogen atom in the main chain. The position of this oxygen atom is half a turn above the region where the retinal moiety makes close contact to this helix. We think that there is a water molecule close to the oxygen atom, which makes a hydrogen bond to stabilise the kink in this helix. In helix G, on the other hand, we found a hydrogen-bonded turn from Ser214 to Val217. The geometrical ¯exibility of this helix conferred by Gly218 allows the formation of the kink, which seems to be stabilised by an interaction between Asp212 and Lys216. All the bending regions were around the retinal and had slightly higher temperature factors. Thus, we think that these bending regions of the transmembrane helices are utilised to achieve the tight contact between the helices and the retinal chromophore. In the extracellular BC loop, residues 67 to 69 and 76 to 78 form an antiparallel b-sheet, which is stabilised by three hydrogen bonds between the

Figure 3. Quality assessment of the atomic model of bR by electron crystallographic re®nement. (a) A Ramachandran plot for the re®ned protein structure was produced using the program PROCHECK (Laskowski et al., 1993). Of the 190 non-glycine and non-proline amino acids in bR, 148 (77.9 %) were located in the most favoured regions (domains A, B and L) and 41 residues (21.6 %) in additional allowed regions (domains a, b, l and p). Only one residue (Ser158) was found in a generously allowed region (domains a, b, l and p). The triangles represent glycine residues. (b) In this plot of temperature factors for the backbone and the side-chains, the residues assigned to helices and b-sheets are marked by a dark and a light grey background, respectively.

868

Charge Distribution in Bacteriorhodopsin

Figure 4. (legend opposite)

Charge Distribution in Bacteriorhodopsin

backbone atoms of these residues. The two adjacent antiparallel b-strands were connected by a hairpin loop formed by six residues. This result is consistent with the b-strand content of 2 to 11 % in bR determined by Raman spectroscopy (Vogel & GaÈrtner, 1987). Positions of lipids In our experimental map, we could detect eight lipid molecules per asymmetric unit, which we modelled as phosphatidyl glycerophosphate monomethyl ester with dihydrophytol chains (PGP-Me), the major phospholipid found in purple membranes (Kates et al., 1993). When the head groups of the lipids were directly interacting with protein (Figure 5(d)), the lipid head groups could clearly be seen in the 2jFoj ÿ jFcj map and could be modelled with the molecular structure of PGP-Me: 20 % of the total lipid found in purple membrane is actually glycolipid sulphate and 10 % consists of squalene (Kates et al., 1982). However, we could neither identify a density accommodating a glycolipid sulfate nor could we model a squalene molecule into any density in the lipid region. We think that some of the PGP-Me molecules are interchangeable with glycolipid sulphate, but the small amount of glycolipids present made it dif®cult to observe them in our density map. As shown in Figure 5(a) and (b), ®ve of the eight lipid molecules are located in the extracellular leaflet of the lipid bilayer, while the other three are found in the cytoplasmic lea¯et. The representations of the cytoplasmic and extracellular halves of the 2D crystal demonstrate that the lipid molecules in our model are found at almost the same positions as the lipid molecules shown in Figure 12 of Grigorieff et al. (1996). However, in our model two lipid molecules are missing in the cytoplasmic lea¯et. The positions of the two missing lipids are located around the 3-fold axis. It might be that these lipid molecules do not exactly obey p3 symmetry and they are thus smeared out upon symmetrisation. Another very likely reason for the loss of their densities could be their high temperature factors. The membrane surfaces could be determined from the positions of lipids in the direction perpendicular to the membrane plane (Figure 4(c)). The

869 positions of the surfaces were de®ned as the height of the oxygen atoms in the hydroxyl groups of the glycerol, which form ester bonds to the fatty acid chains in the lipid molecules. The distance between the average z-position of these oxygen atoms on the extracellular and the cytoplasmic side was Ê , while the standard deviations of their 31.6 A Ê and 3.5 A Ê, z-positions on the two sides were 1.6 A respectively. The higher standard deviation in the z-position of the lipid molecules in the cytoplasmic lea¯et may be related to the higher temperature factors of the protein molecule on that side. The lipids in the centre of the bR trimer in the cytoplasmic lea¯et were excluded for the determination of the membrane surface, because they were separated from the lipids outside the bR trimer and were found at a different height. The different height of the hydrophobic bR regions interacting with the lipids inside and outside of the trimer was already illustrated by the orthorhombic form of the purple membrane, which was determined Ê by electron crystallography to a resolution of 6.5 A (Leifer & Henderson, 1983). In the orthorhombic form of purple membrane, bR does not form trimers and the individual monomers are tilted by 2  to the membrane compared to the proteins in the native p3 crystal form, indicating different heights of the hydrophobic areas around the bR monomer. The positions of the lipids relative to the bR molecule revealed that only the membrane-spanning helices of the protein are interacting with the fatty acid tails of the lipid molecules. This appears to be a general feature of integral membrane proteins, because the low dielectric constant in the hydrophobic core region of the lipid bilayer has a stabilising effect on the secondary structure of the protein. More speci®c to bR are the quite different characteristics of the two protein surfaces. On the cytoplasmic side, the transmembrane helices protrude from the membrane surface and long ¯oppy loops connect them, leading to high temperature factors in this region. On the extracellular side, the transmembrane helices are completely buried in the lipid bilayer, and they are connected by short loops and an antiparallel b-sheet, leading to a very ¯at surface and low temperature factors on this side of the membrane (Figure 5(c)).

Figure 4. The arrangement of secondary structure elements in bR and their irregularities. The representations (a), (b) and (c) are colour-coded as retinal in pink, side-chains of acidic and basic amino acids in red and blue, respectively, Tyr in green, Trp in brown and Phe in yellow. (a) and (b) In these ribbon diagrams, helical regions are represented as ribbons and b-sheets as arrows. Side-chain atoms and the retinal molecule are presented as stick models and the colour gradient from sky-blue (low) to orange (high) indicates the temperature factors of the backbone atoms. The viewing direction in (b) is approximately opposite to that in (a). (c) In this diagram, the one-letter symbols of the bR amino acid sequence were projected on the Ca positions of the backbone. Regions assigned to helices and to antiparallel b-strands are represented by red and green boxes, respectively. Two helical segments in a single transmembrane span indicate the presence of a kink in the transmembrane helix at the residue where the two boxes overlap, for which the angle between the two helical segments was larger than 10  . Secondary structure conformations were assigned to the amino acids using the program DSSP (Kabsch & Sander, 1983). The 310-helices and the p-helices at the ends of some transmembrane helices were included in the helical regions. The interfaces between hydrophobic and hydrophilic regions estimated from the position of the lipid molecules are marked by blue lines, where the thickness represents the standard deviation of the position of the oxygen atoms at the interfaces.

870

Charge Distribution in Bacteriorhodopsin

Figure 5. (legend opposite)

871

Charge Distribution in Bacteriorhodopsin

Previously (Kimura et al., 1997), we estimated the position of the cytoplasmic and extracellular surfaces from the distribution of the nitrogen and oxygen atoms in the hydrophilic amino acid sidechains. On the cytoplasmic side, the z-position of the hydrophobic-hydrophilic interface estimated from the hydrophilic side-chains is signi®cantly different from the z-position of the boundary between lipid tails and head groups we determined in this work. This deviation might be caused by the orientation of the head groups of the lipids. In the cytoplasmic lea¯et, the head groups project over the hydrophobic-hydrophilic interface, while, on the extracellular surface, they lie down and thus contribute to the very ¯at surface of this side. Polarisation in the backbone Due to the different scattering characteristics of ionised and neutral atoms especially in the low-resolution range (Figure 1(a)), there should be signi®cant differences between the jFoj map and the jFcj map, when neutral scattering factors are used to calculate the jFcj map. Thus, we calculated a jFoj ÿ jFcj map including low-resolution data using scattering factors for neutral atoms (Figure 6(b)). The main differences in the jFoj ÿ jFcj map were found around the main-chain regions and we interpreted these differences to come from polarisation in the polar groups of the backbone. Thus, we examined the magnitude of polarisation of the carbon and oxygen atoms in the peptide bonds of the backbone by comparison of crystallographic re®nement results using linear combinations of scattering factors for neutral and ionised atoms (see Materials and Methods). The scattering factors of partially charged atoms were approximated by a linear combination of scattering factors of neutral and ionised atoms, varying the ratio of the linear combination from 0.0 to 1.0 by steps of 0.1. The R-factors and free R-factors in the re®nements were calculated for each value. Because the difference in the scattering factors of neutral and ionised atoms is most prominent in the resolution range Ê , the low-resolution data, which were up to 8.0 A excluded from the re®nement of our atomic model, were included for these re®nements. Moreover, in the calculations we assumed that all the oxygen and carbon atoms in the backbone had an equal but opposite charge. The result of these calculations showed that the free R-factor was minimised when the relevant atoms were assumed to

have a partial charge of 0.4, while the R-factor was minimised at a ratio of 0.5, as shown in Figure 6(a). These values are very close to the values used in molecular dynamics calculations for partially charged oxygen and carbon atoms in the backbone, which are ÿ0.5 and 0.5, respectively, in the XPLOR toph19x.pro and tophcsdx.pro parameters (Brooks et al., 1983; BruÈnger et al., 1987). To con®rm that the difference in the R-factors is really due to actual differences in the densities around the backbone, we calculated a jFoj ÿ jFcj map using scattering factors for partially (0.5) charged atoms and compared it with that calculated using scattering factors of neutral atoms. In both maps, regions of densities above the 3.5s level from the mean density were located around the backbone atoms. The actual value of s was bigger in the latter map and the volume above the 3.5s level (we used the same s value for both cases) in the jFoj ÿ jFcj map was reduced by 7.3 % assuming partially charged atoms. Thus, the ®t in real space between the jFoj and jFcj maps in the region of the backbone atoms could be improved by assuming partial charges describing polarisation of the carbon and oxygen atoms in the peptide bonds. It is important to point out that no corresponding densities above the 3.5s level show up in the jFoj ÿ jFcj map calculated without low-resoluÊ ), even if the scattering tion data (lower than 8.0 A factors of neutral atoms were used. This is consistent with our hypothesis that the differences are due to the different electron scattering factors of neutral and charged atoms, which are most different in the low-resolution range. The remaining differences in the jFoj ÿ jFcj map assuming partially charged atoms could possibly be explained by polarisation between nitrogen and hydrogen atoms in the backbone peptide groups. This could not be taken into account for the re®nements, because electron scattering factors of ionised nitrogen and hydrogen atoms are not provided in the International Tables in X-ray Crystallography (1974) and could not be estimated (see Discussion). Visualisation of positive charges We also found some strong peaks above the 3.5 s level around some side-chains in our Ê jFoj ÿ jFcj map, calculated with all data from 54 A Ê resolution. The peaks above the 3.5 s level to 3 A were around ®ve acidic residues, Asp36, Glu74, Asp102, Glu194 and Asp212, as shown in Figure 7.

Ê slices of (a) the cytoplasmic and (b) the extracellular half of Figure 5. Lipid molecules in the 2D crystal of bR: 20 A the 2D crystal are shown, where the protein is represented by a ribbon model and the lipid molecules by ball-andstick models. Only those lipid molecules are coloured that directly interact with the membrane-spanning helices of a single bR molecule (red). The membrane-spanning helices of surrounding bR molecules, which were directly interacting with the red bR molecule, are coloured in green and blue. The symmetry-related lipid molecules are shown in the same colour. (c) The coloured molecules in (a) and (b) are viewed from the direction parallel with the membrane. (a) to (c) Were produced using the programs MOLSCRIPT (Kraulis, 1991) and RASTER3D (Bacon & Anderson, 1988; Merrit & Murphy, 1994). (d) Typical densities in the 2jFoj ÿ jFcj map representing lipid molecules are shown. The modelled lipid molecules are drawn in the same colours as in (a) to (c).

872

Charge Distribution in Bacteriorhodopsin

Figure 6. (legend opposite)

Charge Distribution in Bacteriorhodopsin

We interpret these densities to re¯ect positive charges, because they disappeared when the jFoj ÿ jFcj map was calculated without the low-resolution data (data not shown). However, we could not see densities corresponding to positively charged amino acid residues, probably because most of them form salt-bridges to negatively charged residues. In addition, since no cation was included in our atomic model, the jFoj ÿ jFcj map shows stronger peaks where positive charges exist in the structure but the atoms have not been modelled than at positively charged residues where neutral side-chains were included in the model. The position of positively charged atoms might not be at the centre of the peaks found in the jFoj ÿ jFcj map, because the map could be affected from experimental noises. However, positive charge should be around the peaks, because these peaks were intensi®ed by including the low-resolution data for the calculation of the jFoj ÿ jFcj map, where the charge effect is signi®cant. Although the position of peaks in the jFoj ÿ jFcj map might not be very reliable, we could categorise the difference peaks into two types according to the appearance of the 2jFoj ÿ jFcj map in the regions of the peaks in the jFoj ÿ jFcj map. One type has densities above the 1.0 s level at the same position in the 2jFoj ÿ jFcj map (Asp36 and Asp102). The other type also has densities in the 2jFoj ÿ jFcj map, but Ê apart from those in the these are about 1.0 A jFoj ÿ jFcj map (Glu74, Glu194 and Asp212). We interpreted the former peaks as cations, because they have strong scattering factors even at high resolution, which can be detected in the 2jFoj ÿ jFcj map. On the other hand, we interpreted the latter peaks as water molecules or hydroxonium ions, because they have no signi®cant scattering factors at high resolution, but instead, they have an accompanying atom that is not positively charged; this point is further discussed below.

Discussion Data treatment in electron crystallography We analysed our electron crystallographic data using the CCP4 (1994) package and re®ned the atomic model for bR using the program X-PLOR (BruÈnger, 1988), a procedure adopted from X-ray crystallography. However, some procedures had to be modi®ed due to the different features of electron and X-ray crystallographic data sets. Electron crystallography depends on collecting electron diffrac-

873 tion patterns from many different 2D crystals, while X-ray diffraction data sets are taken from only a few 3D crystals. Thus, smooth scaling as used in Xray crystallography (Kabsch, 1988) could not be applied to electron crystallographic data sets. Moreover, the continuous layer-lines in the Z*-direction and the asymmetry of the data in parallel and perpendicular directions to the tilt axis are thought to affect poor overall statistics of the data, and a more sophisticated treatment of the data was required. First, we explored the merging procedure for electron crystallographic data where the amplitudes were derived from electron diffraction patterns and the phases were directly measured by image processing of electron micrographs. In our previous work (Kimura et al., 1997), electron diffraction data were processed with the CCP4 program package in the same way as X-ray diffraction data are usually processed, though asymmetric temperature factors were used in the parallel and perpendicular direction to the tilt axis for highly tilted specimens. In that approach, we selected good electron diffraction data, as judged from the statistics given by the programs, to be averaged into the ®nal data set. This resulted in very good R-factors (Friedel R-factor of 10.7 % and merging R-factor of 15.6 %) with a completeness of the data of 90 %. The phase data, on the other hand, were merged as completely as possible without a strict preselection, and the merged phase data set was subsequently improved by applying density modi®cations, as usually done in X-ray crystallography. This yielded a merging phase residual of 26.7  . At the beginning of our current electron crystallographic re®nement, we used amplitude data converted from the merged intensity data set by the program TRUNCATE (French & Wilson, 1978), which takes into account the treatment of the negative intensities, as done by Henderson et al. (1990). However, we found that we could improve the R-factor after re®nement when re¯ections with negative intensities were set to zero instead of treating them by TRUNCATE assuming Bayesian statistics. The R-factors calculated from the same initial model with the former and the latter method were 28.2 % and 26.4 %, respectively. The reason for this difference might be found in the way that the current programs work to merge electron crystallographic intensity data. The 2D crystals consist of only one crystalline layer and therefore the data in the Z*-direction are not concentrated in discrete spots but form continuous functions along recipro-

Figure 6. Comparison of re®nement results using various ratios of atomic scattering factors for neutral and charged atoms. (a) R-factors and free R-factors calculated using scattering factors of partially charged atoms for carbon and oxygen atoms in the peptide group. The R-factors are shown in red, while the free R-factors are in blue. The same partial charge values were assumed for both the carbon and oxygen atoms in the backbone. The minimum value for the R-factor and the free R-factor were at the ratios of 0.4 and 0.5, respectively. (b) and (c) The jFoj ÿ jFcj maps (red contours) were calculated and the structures of bR (stick models) were re®ned using the scattering factors of neutral carbon and oxygen atoms and 0.5 for partially ionised atoms for the backbone peptide group. The jFoj ÿ jFcj maps are contoured at the 3.5 s level. In both maps, the regions contoured in red are mainly around the backbone atoms.

874

Charge Distribution in Bacteriorhodopsin

Figure 7. The jFoj ÿ jFcj map calculated including low-resolution data. The peaks above the 3.5 s level in the jFoj ÿ jFcj map around Asp36, Glu74, Asp102, Glu194 and Asp212 are shown by red cages, and we suggest that these peaks represent positively charged atoms. Peaks above 3.5 s were not observed in the difference maps calculated without the low-resolution data. The peaks in (a) have corresponding densities in the 2jFoj ÿ jFcj maps, which are contoured at the 1.0 s level in sky blue, while the peaks in (b) have small regions of densities (marked by arrow Ê apart from them. heads) above 1.0 s that are about 1.0 A

Charge Distribution in Bacteriorhodopsin

cal lattice lines. The programs currently used to scale and de-twin electron crystallographic data sets (Baldwin & Henderson, 1984), however, treat the Fourier data in the Z*-direction as if they were discrete diffraction spots under the assumption of Ê . Then we statistically a crystal thickness of 500 A averaged the intensities into discrete data points Ê in the assuming a lattice parameter of 100 A Z*-direction. This approach might not be ideal, and thus we examined the use of LATLINE (Agard, 1983) to merge both amplitude and phase information at the same time. LATLINE was especially designed to handle the continuous functions found along the reciprocal lattice lines in Fourier transforms of 2D crystals. It works by ®tting curves to the non-uniformly sampled amplitude and phase data in the Z*-direction, assuming a de®nite value for the thickness of the 2D crystals. By using this program for merging, the accuracy of the phase data becomes very important, because the curves for amplitudes and phases are not ®tted independently. Therefore, the curve ®tted to the phase data also in¯uences the curve ®tted to the amplitude data. Unfortunately, phases extracted from electron micrographs were less accurate than the intensity data obtained from electron diffraction patterns, especially in the highresolution range. To overcome this problem, we compared amplitudes extracted from the electron micrographs with intensities determined from the electron diffraction patterns as described in Materials and Methods. Based on this comparison, we selected for merging only the phases that showed a good agreement of the image amplitude with the corresponding electron diffraction intensity. On the other hand, the strict preselection of intensity data using the differences from the averaged intensities, which were calculated assuming discreteness in the Z*-direction, was abandoned. Although this new merging procedure made the statistics of the data worse, as shown in Table 1, it signi®cantly improved the resulting R-factor after re®nement (from 28.2 % to 24.2 %). We think that we could improve the Friedel and merging R-factors if we preselected the intensity data using the Friedel difference of each re¯ection, but we did not further investigate the merging procedure because the merged data already gave a good R-factor. As the next step, we investigated the differences in the re®nement of electron and X-ray crystallographic data that are caused by the different scattering factors of the relevant atoms for electrons and X-rays. When we scale the electron scattering factor of a carbon atom to its scattering factor for X-rays, it is immediately evident that the scattering factor of a hydrogen atom is much larger for electrons than for X-rays (Figure 1(b)). Thus, the contribution of electron scattering by hydrogen atoms to the overall scattering factor of the entire protein is much larger than in X-ray crystallography, even if the hydrogen atoms are not ionised. Therefore, we compared the R-factors resulting from re®nements with and without hydrogen atoms. It was dif®cult

875 to include all hydrogen atoms into the XPLOR parameters for protein crystallographic re®nement, because the bond-length and bond-angle parameters were derived from a statistical survey of X-ray structures of small compounds in the Cambridge Structural Database and these are only available for polar hydrogen atoms (Engh & Huber, 1991). Thus, we could include only polar hydrogen atoms in the calculation, which is acceptable because polar hydrogen atoms should have a larger contribution to the overall scattering factor compared to hydrogen atoms carrying no partial charge induced by polarisation. Starting from the same initial model, re®nements were performed where polar hydrogen atoms were either included in the calculations or not. Although the resulting R-factors were almost the same, the geometric parameters of the re®ned structures were signi®cantly different. In the Ramachandran plot calculated by PROCHECK, the number of residues in the most favourable region was 148 (77.9 % of all non-glycine and non-proline residues) when polar hydrogen atoms were included, but only 137 (72.1 %) when polar hydrogen atoms were excluded. Therefore, polar hydrogen atoms were included in all re®nement cycles using XPLOR, except for the ®nal step. They were excluded from the model at the ®nal step, since a resolution of Ê is not suf®cient to determine the position of 3.0 A the hydrogen atoms. Interpretation of low-resolution data in terms of charge distribution Interpretation of low-resolution data is dif®cult because of the bigger effects of inelastic scattering and the background deriving from the solvent. However, we think that our qualitative interpretation of the low-resolution data is not strongly affected by these effects. Our improved treatment of the background in our electron diffraction patterns by subtracting a smooth surface (see Materials and Methods), representing the background scattering of ¯at uniform sheets of amorphous ice and carbon ®lm, allowed us to exclude the background more accurately. The effect of inelastic scattering is thought to be the same for every re¯ection, and the systematic error to produce the result interpretable in terms of charge distribution is dif®cult to imagine. Moreover, if we assumed a partial charge only on the oxygen atoms and no partial charge on the carbon atoms, the R-factor and free R-factor increased with the increase of the partial charge on the oxygen atoms (data not shown). Therefore, we think that the decrease of the R-factor and free R-factor especially in the low-resolution range can be interpretable as the polarisation of the backbone atoms. The polarisation between a nitrogen and a hydrogen atom was not included in our evaluation of the magnitude of backbone polarisation. The reason for this is that in International Tables for X-ray Crystallography (1974) we could not ®nd a

876 value for the scattering factors of a negatively charged nitrogen atom and a positively charged hydrogen atom, although the polarisation of these atoms is well known. The lack of a value for the scattering factor of a positively charged hydrogen atom was signi®cant, because we were not able to approximate it satisfactorily. Combining the scattering factors of a neutral lithium atom and a positively charged nucleus estimated from an oxygen atom could not produce a well-®tted scattering factor of a positively charged lithium atom, which is also a monovalent cation like a proton (Figure 1(a)). Therefore, we chose not to use a scattering factor of a positively charged hydrogen atom calculated in the described way. Because of the missing scattering factors of some ionised atoms, the re®nement of our electron crystallographic data might have some systematic error if not enough low-resolution data were excluded. Accordingly, we excluded all low-resolution data Ê . However, exclusion of data up to 5 A Ê up to 8.0 A resolution would be even better, because the scattering factor of a negatively charged oxygen atom is negative in the resolution range lower than Ê . Unfortunately, we were not yet able to 5.5 A Ê resolution for the exclude all the data up to 5.0 A re®nement, because the remaining data were insuf®cient compared to the degree of freedom in the re®nement of the model (Table 1). Thus, our re®nement may suffer from some problems in the backbone peptide groups and in the side-chains of the charged residues. We found bending of the transmembrane helices at almost the same height as their contact regions to the retinal and we interpreted them as kinks because of the irregularities of secondary structures around the bending regions. However, some of the kinks may result from insuf®cient treatment of the low-resolution data in the re®nement. We are convinced of the existence of the bends in these regions but some of them might rather be interpreted as bends preserving hydrogen networks found in the ordinary a-helical conformation than actual kinks. Two different types of positive charges In the jFoj ÿ jFcj map we found ®ve strong peaks above the 3.5 s level around acidic residues. We grouped these peaks into two categories depending on the appearance of the densities in the 2jFoj ÿ jFcj map around the peaks. Two of the ®ve peaks in the jFoj ÿ jFcj map, around Asp36 and Asp102, also showed some intensities above 1.0 s level at the same position in the 2jFoj ÿ jFcj map (Figure 7(a)). In addition, the region of the peaks was bigger than the corresponding peaks in the jFoj ÿ jFcj map. Thus, the densities in the 2jFoj ÿ jFcj map indicated the existence of positively charged atoms with signi®cant scattering factors even in the high-resolution range, and we think that these peaks represent cations for example, sodium or potassium ions. Both acidic residues, Asp36 and Asp102, are located at the cytoplasmic surface. Moreover, one of

Charge Distribution in Bacteriorhodopsin

two cation-binding sites, which were determined by incubation of cation-depleted bR with pentaammineaquocobalt(III) tetra¯uoroborate, was located in the sequence from Val101 to Gln105 (Engelhard et al., 1989), and this result corroborates our assignment of cations to the visualised positively charged atoms. The other three peaks, around Glu74, Glu194 and Asp212, were visible only in the jFoj ÿ jFcj map and there were no corresponding densities above the 1.0 s level at the same position in the 2jFoj ÿ jFcj map (Figure 7(b)). Instead, densities above the 1.0 s level were found in the 2jFoj ÿ jFcj Ê apart from the peaks in the map about 1 A jFoj ÿ jFcj map, although the peaks in the 2jFoj ÿ jFcj map are smaller than the peaks interpreted as cations. Notably, there were two peaks between Arg82 and Glu194 in the jFoj ÿ jFcj map (red contour in Figure 7) and a peak in the 2jFoj ÿ jFcj map (blue contour) between these two peaks. We think that these peaks in the jFoj ÿ jFcj map are due to positively charged hydrogen atoms of a hydroxonium ion or a polarised water molecule. The accompanying density peaks in the 2jFoj ÿ jFcj map would represent the oxygen atom of the water molecule and its distance and angle to the hydrogen atoms seems to be reasonable. The reason for the appearance of hydrogen atoms for only three water molecules or ions might lie in their close vicinity to negatively charged residues, which leads to a stronger polarisation of these particular water molecules compared to other water molecules. These molecules may also have a lower temperature factor than other water molecules because of their relatively ®xed position, presumably due to the stronger interaction with negatively charged residues. Ê resolution Recently, the structure of bR at 2.3 A was determined by X-ray diffraction using 3D crystals grown in lipidic cubic phase (Luecke et al., 1998). The positions of the three ®xed water molecules in their structure do not correspond to the positions of the hydrogen atoms we describe here. In our map, we could not observe densities corresponding to water molecules 401 and 402 reported by Luecke et al. (1988), and we modelled Arg82 at the position of water molecule 403. On the other hand, the position of the hydrogen atom that is close to Asp212 in our map corresponds to the position of Arg82 in the X-ray structure. The position of Arg82 in our previous paper is similar to that in the X-ray structure, but in the process of re®nement the side-chain moved to a slightly different position. Thus, we are not certain whether the re®nement improved the accuracy of the position for the side-chain. The density of the water molecule close to Arg82 or the positive charge on Arg82 might affect the re®nement, resulting in assignment of the wrong position to Arg82. However, our observation of a positively charged hydrogen atom close to Asp212 is consistent with both situations, because the hydrogen atom could be interpreted as one of Arg82, if the assignment is

877

Charge Distribution in Bacteriorhodopsin

wrong. The other water molecule or ion in our map, which is situated close to Glu194 in the proton pathway of bR, also shows up as a peak in the electron density map determined by X-ray diffraction, although Luecke et al. (1988) did not assign a water molecule to that density. Previously (Kimura et al., 1997), we interpreted Asp36, Asp96, Asp102, Asp115 and Glu194 as being protonated and other acidic residues as being negatively charged from our experimental maps with and without the low-resolution data. According to our assignment of cations and positively charged hydrogen atoms presented here, it seems that the three neutral residues, Asp36, Asp102 and Glu194, are actually negatively charged. However, the negative charge on the three residues could not be visualised in our experimental map, because of their interaction with the positively charged atoms. Thus, residues Asp96 and Asp115 could be interpreted as protonated. From vibrational spectroscopy of bR mutants, Asp96 and Asp115 are thought to be protonated (Braiman et al., 1988), and this is in good agreement with our result. Significance of the charge observations Here, we propose that two kinds of observation could be interpreted in terms of charge distribution in bR, namely the polarisation of the polar groups in the main-chain and the presence of positively charged atoms visualised in the difference map. We will now discuss the signi®cance of the signals for these two observations. The ®rst observation, the polarisation of the polar groups in the main chain, is suggested by the improvement of the R-factor and the free R-factor when we used the scattering factors of polarised atoms rather than neutral atoms. The peaks above the 3.5 s level were only observed in the difference map when the low-resolution data was included into the calÊ resolution were culation. If data lower than 8 A excluded, no signi®cant peak could be observed in the difference map calculated from the atomic model with a free R-factor of 33.4 %. Because the Ê to 6.0 A Ê is 33.5 % and the free R-factor from 80 A same noise level can be expected, the peaks above the 3.5 s level are very unlikely to derive from low-resolution noise. Therefore, we conclude that there are systematic differences in the low-resolution range between the experimental data and the amplitudes calculated from the atomic model using the scattering factor of neutral atoms. We think that the systematic differences at lowresolution can be explained, at least partly, by polarisation of polar groups in the main chain, such as CO and NH, because the overall R-factor and free R-factor became smaller when the scattering factors of polarised atoms were used. The decrease of the R-factor and free R-factor in the low-resolution range, where the difference of atomic scattering factors between ionised and neutral atoms are prominent, were more signi®cant than

those in the high-resolution range. The R-factor Ê to 6.0 A Ê were dropped and free R-factor from 80 A from 28.0 % to 26.9 % and from 33.5 % to 31.9 %, respectively. The decreases of the R-factor and free R-factor over 1.0 % are very unlikely to occur by coincidence. Moreover, the peaks in the difference map were observed mainly in the main chain region of the transmembrane helices, where the average RMS distance of the Ca atoms between our model and the one determined by Henderson and co-workers (2brd in PDB) was Ê . Thus, the systematic differences less than 1.0 A at low-resolution between the experimental data and the model consisting of neutral atoms can be reliably interpreted in terms of polarisation in the backbone. The second observation, peaks above the 3.5 s level in the difference map in the region of some acidic side-chains, was interpreted in terms of positively charged atoms. These peaks were observed only when low-resolution data were included into the calculation and therefore come from the lowresolution data. In the difference map without the low-resolution data where the free R-factor is 33.4 %, we could observe some peaks above the 1.5 s level. Therefore, we can also expect these 1.5 s level noises from the low-resolution data with the free R-factor of 33.5 %. Peaks above the 3.5 s level cannot be attributed to noise, because piling up locally two peaks of 1.5 s level noise could not result in peaks above the 3.5 s level. Moreover, the difference map, which is calculated from the two data sets divided into half randomly, gave no peak above the 3.5 s level and only the peaks above the 2.0 s level were observed (data not shown). Thus, we think that almost all peaks in the side-chain region come from the systematic differences at lowresolution, and that the differences can be interpreted from the positively charged atoms in bR. However, the noises of the 1.5 s level can affect the positions of the peaks above the 3.5 s level in the difference map. The positions of the peaks in the difference map might not be very accurate. Therefore, the classi®cation of the peaks in the difference map from the positions of the corresponding peaks in the 2jFoj ÿ jFcj map can be wrong, though the classi®cation in this work relies on the relative size of the peaks in the difference map compared with the corresponding peaks in the 2jFoj ÿ jFcj map. We think that the bigger size of the peaks in the 2jFoj ÿ jFcj map could be reliably interpreted as a combination of the positive charge on it and the contribution of the high-resolution data from cations. Thus, the assignment of cations to the bigger peaks in the 2jFoj ÿ jFcj map is thought to be reasonable. Proton pumping pathway Based on the charge distribution in a bR molecule shown here, we can propose the probable change of charge distribution in the proton path-

878

Charge Distribution in Bacteriorhodopsin

Figure 8. Ball-and-stick representation of side-chain atoms lining the extracellular half of the proton pathway. Helix G is drawn in ribbon representation. The oxygen and nitrogen atoms are coloured in red and blue, respectively. The light blue oxygen atoms belong to water molecules or hydroxonium ions, which were assigned from the peaks we interpreted as positively charged hydrogen atoms. The red arrows in the view indicate the interactions to link protonation of Asp85 with deprotonation from the extracellular region.

way at an early stage of the photocycle. As in Figure 8, we found two negatively charged acidic residues, Asp212 and Glu194, indirectly interacting with Arg82 through a hydroxonium ion or a water molecule. The two molecules interacting with Arg82 are ionised or highly polarised, because the positive charge on their hydrogen atoms could be seen in the jFoj ÿ jFcj map. We think that the interactions between the acidic residues and the basic residue, through an ion or a water molecule, stabilises the positive charge on Arg82. Thus Glu204, Ê apart from Arg82, could be protowhich is 4.0 A nated, as suggested by a Fourier transform infrared spectroscopy study (Brown et al., 1995), though we could not observe the negative charge on it in our experimental map. When the Schiff base protonates Asp85 and becomes neutral, the interaction between Asp212 and the Schiff base changes, and the stabilisation of the positive charge on Arg82 through the hydrogen bond network, including ions or water molecules, decreases. This would lead to a stronger interaction between Arg82 and Glu204 as an ion pair, and therefore promote deprotonation of Glu204, which is thought to be the terminal proton-releasing residue at the extra-

cellular surface (Brown et al., 1995). Alternatively, a hydroxonium ion or a water molecule interacting with Arg82 might release a proton. In both cases, protonation of Asp85 causes deprotonation from the extracellular surface. The linkage between Asp85 and Glu204 or a water molecule through Asp212 is supported by the perturbed interaction between these two residues in a Y185F mutant (Richter et al., 1996), because Tyr185 makes a hydrogen bond with Asp212. In addition, the result that the E194C mutation inhibits fast proton release in bR (Balashov et al., 1997) supports the idea of stabilisation of the positive charge on Arg82 by Glu194 through an ion or a water molecule and may suggest that a proton is released from a hydroxonium ion or a water molecule interacting with Glu194. To prove this hypothesis, atomic models of the intermediates of the bR photocycle must be determined, which are necessary if the proton pumping mechanism should be fully understood. Charge distribution in the intermediates, which can be visualised by electron crystallography as shown here, would be very useful for the elucidation of the proton pumping mechanism.

879

Charge Distribution in Bacteriorhodopsin

Figure 9. (legend overleaf )

880

Materials and Methods Sample preparation and data collection Sample preparation and recording of diffraction patterns and electron micrographs were performed as described (Kimura et al., 1997). Brie¯y, purple membrane was prepared from the retinal-de®cient Halobacterium salinarium mutant strain JW5. After addition of all-trans retinal, membranes were fused with dodecyltrimethylammonium chloride (Baldwin & Henderson, 1984) and subsequently prepared for electron cryo-microscopy by rapid freezing including 3 % (w/v) trehalose. Electron diffraction patterns and images were collected in a JEM4000SFX and JEM3000SFF (JEOL) transmission electron microscope at a specimen temperature below 20 K (Fujiyoshi et al., 1991). Total electron doses for diffraction patterns and images were kept below 10 and 30 elecÊ 2, respectively. trons/A Image processing Integrated intensities for each re¯ection were calculated from electron diffraction patterns according to Ceska & Henderson (1990), subtracting a smooth background surface as described below. While most diffraction patterns were acquired with a 1k  1k slow scan CCD camera (GATAN), some diffraction patterns were recorded on SO-163 ®lms (Kodak) and scanned with a ¯at-bed micro-densitometer (Perkin-Elmer). Variations in absorbance in the slow scan direction of the micro-densitometer were eliminated and then the recorded densities were converted to electron exposure using look-up tables measured from uniform illumination of the electron beam. These compensations were not done for data collected with the slow-scan CCD camera. After a smoothed radial density curve was subtracted, a smooth surface was subtracted, which was estimated from the asymmetric background noise, deriving essentially from the carbon ®lm used as specimen support. The asymmetric background densities were sampled in the centres between two adjacent diffraction spots, the positions of which were determined as their centre of gravity. From the sampled densities, a smooth surface representing the asymmetric background was calculated using the FITVSF subroutine in the PLOT79 library (Akima, 1979). After subtraction of the smooth surface, the intensity of each spot was integrated and Friedel pairs were averaged for further analysis. The typical decrease of Friedel R-factors obtained by subtracting a smooth background surface was about 1 % for diffraction patterns from untilted specimens and about 2 % for diffraction patterns from tilted specimens. Phase information was extracted from electron micrographs according to Henderson et al. (1990) using modi®ed MRC image processing programs. Additional programs were written to reduce the user input, making the processing of many images more ef®cient. Most tilted images were digitised using a LeafScan45 (Scitex) because of its faster scanning speed (Mitsuoka et al.,

Charge Distribution in Bacteriorhodopsin 1997), although a PDS 1010 microdensitometer (PerkinElmer) was initially used to scan the untilted and some of the tilted images. The quality of the resulting amplitudes and phases are shown in Figure 9. Merging of intensities and phases Initially, intensities calculated from the electron diffraction patterns were merged by ®tting curves along each of the lattice lines using a damped sinc function with de-twinning (Baldwin & Henderson, 1984; Ceska & Henderson, 1990), and subsequent scaling using the CCP4 package (Collaborative Computational Project, Number 4, 1994). By comparing the merged electron diffraction intensities with the amplitude data extracted from micrographs, we evaluated the quality of the image data and rejected some bad re¯ections from the image data set (Figure 9). A modi®ed Wilson plot was drawn by plotting the ratios between the diffraction intensities and the squared image amplitudes against (siny/l)2. A parabola was then ®tted to the experimental curve and the maximum resolution was determined as the minimum of the parabola where the Wilson plot ¯attens out, because the ®tted curve will adopt a positive slope where the image amplitudes consist only of white noise. Re¯ections with deviations larger than 3 s from the ®tted curve were eliminated from the image data set. All the diffraction intensities and the phases from the processed images were merged using the program LATLINE (Agard, 1983). Negative intensities were converted to amplitudes of value zero. The resulting merging R-factor and the phase residual are shown in Table 1, together with other crystallographic parameters. The ®gures of merit of the merged data set were calculated from the standard errors on the phases estimated by LATLINE and the phase information was improved by solvent ¯attening and histogram matching using DM (Cowtan, 1994) to calculate a map for initial modelling. Electron crystallographic refinement The atomic model of bR between amino acid residues 6 and 227 was built into the density map using the program O (Jones & Kjeldgaard, 1993). Starting from the initial model, the entire process of electron crystallographic re®nement was performed by the program X-PLOR (BruÈnger, 1988). Simulated annealing followed by conventional re®nement resulted in a structural model Ê and with an R-factor of 23.5 % for data between 8.0 A Ê resolution. The side-chain atoms and the backbone 3.0 A atoms of the same residue were grouped and given the same temperature factors in the re®nement cycles, although the temperature factor of each atom was estimated in the ®nal calculation. The free R-factor from about 5 % of the total re¯ections within the same resolution range was 33.3 %. The number of degrees of freedom for the re®nement was 7641 including polar hydrogen atoms, while the number of included re¯ections was 6107, and both amplitudes and phases were used in the re®nement. In the last cycle of re®nement,

Figure 9. Quality assessment of the processed images. (a) A typical distribution of IQ values at various tilt angles is shown. The IQ values, de®ned as 7/(signal-to-noise ratio) (Henderson et al., 1990), are indicated by the size of the squares (IQ 1-7). (b) The ratio of diffraction intensity to the square of the image amplitude is plotted as a function of (siny/l)2 for typical images at various tilt angles. Only the re¯ections shown by circles were used to merge the phase information. The re¯ections in the tilted images are divided into sectors, parallel and perpendicular to the tilt axis, for which the data are shown in different grey levels (darker for the data parallel with the tilt axis).

881

Charge Distribution in Bacteriorhodopsin two water molecules in the proton pathway were included in the model, while the polar hydrogen atoms were omitted. This modi®cation in the last cycle resulted in a higher R-factor (23.7 %) but the free R-factor decreased (33.0 %). In our re®nement, we tried to optimise the phase data (phase residual) as well as the amplitude data (R-factor). The topology and parameter ®les for the retinal were prepared from high-resolution structures found in the Cambridge Structural Database (Allen & Kennard, 1993). The ®les for the lipid molecules were ®rst created from the ten lipid molecules in the model described by Grigorieff et al. (1996) and then recalculated using only the eight lipid molecules found in our model. In the re®nement performed to evaluate the polarisation of the backbone atoms, we used the re¯ections Ê and 3.0 A Ê. between 54.0 A Secondary structure Hydrogen bond networks were assigned by the program DSSP (Kabsch & Sander, 1983). The neighbouring hydrogen-bonded turns of transmembrane helices were included in the helical regions in Table 2. The assignment of b-sheets was also done by DSSP. Using the program LSQMAN (Kleywegt & Jones, 1994), model helices, which were created by MOLEMAN2 (Kleywegt & Jones, 1997), were ®tted to the transmembrane helices in the region where there was no irregularity of hydrogen bond networks determined as described above. The bending angle of the kinks was calculated from the tilt angle of the two helices ®tted to the same transmembrane helices in the different regions. Scattering factors To re®ne the atomic model of bR using electron crystallographic data, we had to use scattering factors for electrons rather than those for X-rays. The tabulated form of electron scattering factors calculated by the independent atom model is found in the International Tables for X-ray Crystallography (1974), which we converted into the form of four Gaussian coef®cients and a constant (required for X-PLOR) by the program SCATTER (Ceska, 1994). However, the scattering factors of some atoms in the ionised state are not available. Thus, to evaluate the polarisation between carbon and oxygen in the backbone (see Discussion), we had to make a crude approximation for the scattering factor of a positively charged carbon atom by addition of the scattering factor of a neutral carbon atom and that of a positively charged nucleus. The scattering factor of a positively charged nucleus was estimated from the difference between neutral oxygen and an ionised oxygen atom (Figure 1(a)). The value estimated in this way was again converted into the form used by X-PLOR. In addition, we assumed partially charged atoms, and the scattering factors of these atoms were estimated as the linear combination of scattering factors for neutral and charged atoms. These values were only used to estimate the polarisation in the backbone. We are aware of the fact that these assumptions are not accurate and that for a quantitative analysis of the ionisation state of various residues and molecules, the scattering factors must be calculated more precisely and treated more completely. However, because we discuss only semi-quantitative events, such as whether an atom is polarised or not, we think that our approach is acceptable.

Protein Data Bank The re®ned model was deposited in the Protein Data Bank (Brookhaven) and the ID code for the coordinate entry is 2at9.

Acknowledgements We express our sincere thanks to Dr Sriram Subramaniam, Dr Thomas Walz and Dr Robert M. Glaeser for critical reading of the manuscript. This work has been supported by the Japan Society for the Promotion of Science (JSPS-RFTF96L00502). Finally, we thank all our colleagues for their valuable comments and support to our work.

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Edited by R. Huber (Received 6 April 1998; received in revised form 30 December 1998; accepted 30 December 1998)