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* Howard Hughes Medical Institute, Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York; and
Department of Microbiology and Immunology, Weill Medical College of Cornell University, New York, New York
Correspondence: Address reprint requests to Barry Honig, Dept. of Biochemistry and Molecular Biophysics, Columbia University, 630 W. 168th St., New York, NY 10032. Tel.: 212-305-7970; E-mail: bh6{at}columbia.edu.
| ABSTRACT |
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| INTRODUCTION |
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The large number of structures available for soluble proteins has enabled the construction of increasingly accurate homology models for sequence-related proteins and the development of fold-recognition methods that identify structural homologs even when a sequence signal is weak. Structural genomics initiatives are increasing the database of available structures, and computational methods for structure and function prediction are an essential feature of these large-scale efforts (Burley and Bonanno, 2003
; Goldsmith-Fischman and Honig, 2003
). Homology modeling has also been widely applied to membrane proteins (Strahs and Weinstein, 1997
; Capener et al., 2000
; Dwyer, 2001
; Becker et al., 2003
) and is likely to become more accurate as the database of solved structures increases. One of the goals of the current work is to increase the amount of information available for the structure prediction of membrane proteins by exploiting information available in the large data set of soluble proteins. It is widely recognized that prediction of membrane-protein structure may in many ways be easier than for soluble proteins given the constraints provided by the lipid bilayer and the fact that so many membrane proteins are mostly helical (Chamberlain et al., 2003
). Transmembrane (TM) helices are largely, but not exclusively, hydrophobic and consist of stretches of
1530 residues (von Heijne, 1994
). Since a variety of algorithms are available that predict the location and topology of TM helices with considerable accuracy (Engelman et al., 1986
; von Heijne, 1992
; Jones et al., 1994
; Persson and Argos, 1994
; Rost et al., 1995
, 1996
; Cserzo et al., 1997
; Tusnady and Simon, 1998
), to a first approximation, membrane-protein structure prediction can be viewed in many cases as a problem of packing multiple helices. Knowledge of packing patterns in both membrane and soluble proteins of known structure can provide important information that can be applied to this challenging problem. Significant progress in the ab initio packing of pairs of helices has recently been reported (Fleishman and Ben-Tal, 2002
; Kim et al., 2003
). The combination of database and biophysical approaches may prove to be particularly effective.
In this article, we report a detailed comparison of helix packing in membrane and soluble proteins. The structure alignment algorithm of PrISM (Yang and Honig, 1999
) was used to search the Protein Data Bank (PDB) (Berman et al., 2000
) for pairs of interacting helices in soluble proteins that align well with pairs of helices in membrane proteins. (A database of corresponding groups of helices is available on our websitehttp://trantor.bioc.columbia.edu/packing_pattern). We analyzed and compared the geometries and packing patterns of four data sets of interacting helix pairs: helix pairs extracted from membrane-protein structures; helix pairs in soluble proteins that were detected by PrISM to be structurally similar to the membrane-protein helix pairs (two sets were constructed; see below) and helix pairs in soluble proteins from a nonredundant subset of the PDB. Our results reveal that there can be striking similarities in the geometric and sequence-based properties of individual groups of helices despite significant differences in the composition of residues in the interfaces of membrane proteins, as compared with soluble proteins. The energetic factors that drive membrane-protein folding, and their relationship to those that drive soluble-protein folding, are discussed and the possibility of using the soluble protein database in the modeling of membrane proteins is considered.
| MATERIALS AND METHODS |
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Angles between helix axes were obtained with the HA2 program (Fleishman and Ben-Tal, 2002
), where a helix axis is defined as the line joining the geometrical centers of a set of four C
atoms at each end of the helix.
Irregular helices
Riek et al. (2001)
have pointed out that many TM helices have distinct non-
-helical elements. All TM helices that contain deviations from an
-helical geometry are identified in the supplementary material (Table 1). Four types of irregularities were identified: kink (K); 310-helix or tight turn (310);
-helix or wide turn (
); and unwound helix (U). Kinks appear to be associated with nonideality in neighboring residues that frequently form tight (K-310) or wide (K-
) turns.
The location of kinks in TM and soluble helices were identified using the criterion of Bansal et al. (2000)
, who noted that when the angle of a local bend in a helix is >20°, then the hydrogen bond connecting i and i + 4 residues is broken. On this basis, a local bending angle >20° was used to identify kinked helices. The calculations disregarded the four residues at both termini where deviations from ideality often occur. Other deviations from an ideal
-helix were defined using the HELANAL program (Bansal et al., 2000
). First, the number of residues per turn and the rise per residue were calculated using a sliding window of four amino acids. Next, each window (or helical turn) was labeled as either
-, 310-, or
-helix according to the following ranges of values that are based on textbook definitions of helices (Creighton, 1984
; Barlow and Thornton, 1988
). A turn was defined as
-helical if the number of residues in the turn was in the range between 3.4 and 4.0 and the rise per residue was between 1.36 Å and 1.76 Å. A 310-helix was defined as having <3.4 residues per turn and a >1.76 Å rise per residue. A
-helix was defined as having >4.0 residues per turn and a <1.36 Å rise per residue. If both criteria were not satisfied the turn was considered to be
-helical.
To eliminate false positives, once the irregular turns had been identified, the dihedral angles of the residues in those turns were calculated using DSSP. Specifically, we defined a turn to be irregular only if at least one of the residues in that turn had dihedral angles in the following ranges (Creighton, 1984
; Barlow and Thornton, 1988
):
< 66.5 and
> 29.5 for a 310-helix; and
> 59.5 and
< 55.5 for a
-helix. Finally, visual inspection of each TM helix was used to verify the reliability of our results and to identify unwound regions of the helices. This process involved looking for obvious deviations from the
-helical backbone structure and hydrogen-bonding pattern. Two 310-turns were found by inspection to correspond to unwound regions of a helix and one missed
-turn was identified. In all other cases, visual inspection confirmed the identification of the helical irregularities. We were able to identify every irregular helix found by Riek et al. (2001)
. In addition, we found irregularities in five helices that were not documented by Riek et al., including helices 4, 5, and 7 of the calcium ATPase (1eul), helix 5 of halorhodopsin (1e12), and helix 5 of the photosynthetic reaction center (1prc).
Structural superposition
Structural alignments were carried out with the PrISM program (Yang and Honig, 2000
). The groups of interacting membrane-protein helices extracted from the structures in Table 1 ("queries") and listed in the supplementary material (Table 1), were used as substructures to search the 90% PDB_SELECT database with PrISM's structure superposition module. An alignment ("hit") was considered to be significant if at least 75% of the alpha carbon backbone of the query TM helix pair superimposed structurally to within a protein structural distance (PSD) of 0.5 to the soluble helix pair. PSD is a structural similarity measure that accounts for both the relative orientation of secondary structural elements in the two structures and the root mean-square deviation (RMSD), reflecting PrISM's two-stage structure superposition methodology (Yang and Honig, 2000
). A PSD of 0.5 is roughly equivalent to an RMSD of 3.5 Å. In general, a number of hits were found for each query, yielding both pairwise and multiple structural alignments. Structure-based sequence alignments were obtained in each case.
Sequence conservation analysis
We analyzed sequence conservation within families of membrane proteins (see below) using ConSurf (Armon et al., 2001
; Glaser et al., 2003
), a method that employs a physiochemical conservation grade to identify conserved positions in a multiple sequence alignment. The method makes use of phylogenetic trees to ensure that observed levels of conservation are weighted according to evolutionary distance. PSI-BLAST (Altschul et al., 1997
) searches against the nonredundant protein sequence database were used to identify sequence homologs for each membrane-protein structure; the PSI-BLAST hits (after five iterations) along with the seed sequence constitute a "family." An E-value of 1 x 105 was used to select hits after all stages of the PSI-BLAST searches (Armon et al., 2001
; Glaser et al., 2003
). ClustalW (Thompson et al., 1997
) was used to create multiple sequence alignments for each family. Multiple alignments were not created for proteins for which PSI-BLAST found five homologs or less. These included: fumarate reductase (1qla), the light-harvesting complex II (1lgh), chain C of the aberrant ba3-cytochrome c oxidase (1ehk), chains G and I of cytochrome bc1 (1ezv), chains I, K, and L of cytochrome c oxidase (1occ), chain H of the photosynthetic reaction center (1prc), and chains I, J, M, and X of photosystem I (1jb0).
Surface area
We calculated the lipid-accessible surface area for the TM residues of all membrane proteins using SURFV (Sridharan et al., 1992
). The percentage of residue exposed to the lipid was obtained by dividing the accessible area of the residue in the protein by the area of that residue calculated for the same side-chain conformation within a Gly-X-Gly tripeptide with identical backbone structure. All residues in the TM helices studied here were divided into three groups: interacting residues, defined as residues that have over 80% of their surface area buried in the protein core; partially buried residues, defined as residues that have buried surface areas between 50 and 80%; and residues facing the lipid, defined as residues with more than 50% of their surface area accessible.
| RESULTS |
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0.5 (RMSDs ranging from 0.5 Å to 3.5 Å). In this way, 5552 pairs of helices from a nonredundant set of soluble proteins were identified and form the third data set to be considered in the analyses below (termed the homologous set). For reference, using a tighter cutoff of 2.0 Å, nearly half (128) of the interacting TM helix pairs have a soluble hit.
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proteins,
/ß proteins, and
+ ß proteins. Examples of backbone alignments are shown in Fig. 1. Fig. 1 a shows the best structural alignment found between any two TM and soluble helix pairs. The backbones are 100% aligned with a very low RMSD (0.7 Å). Fig. 1 b shows the worst alignment obtained within the chosen structural similarity threshold. The higher RMSD (3.5 Å) is clearly reflected by the lower quality of the superposition.
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atoms very close together (48 Å) and their C-termini far away from each other (>20 Å). Despite the fact that a large fraction of the helix pairs with no hits are irregular, 114 (56%) of the TM helix pairs with hits have at least one irregular helix. In the analysis of the lowest PSD hits for each TM helix pair, in 66% of the cases, kinked helices in TMs are aligned with regular helices in soluble proteins, reflecting the fact that our cutoff is not highly restrictive. In 34% of the cases there are kinked helices in both the membrane protein and its corresponding soluble-protein helix pair.
Examples of well-aligned helices
Fig. 2 illustrates an example of two well-aligned helix pairs (PSD = 0.046; RMSD = 0.7 Å): helices 18 and 19 from cytochrome c oxidase (1occ) and helices 7 and 8 from chaperone HSC20 (1fpo). The figure displays the superimposed backbones and the side chains of the interfacial residues. In addition to the backbones, the side chains of the interfacial residues superimpose remarkably well and in some cases have essentially the same conformations. We have found many cases where aligned side chains adopt similar conformations, especially when the residue is the same in both interfaces (see, e.g., Val-121 (1fpo) and Val-136 (1occ) in Fig. 2).
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Helix lengths
Fig. 3 shows the distribution of helix lengths for all four sets of helices. There is a strong preference for helices longer than 20 residues in membrane proteins, where we also observe somewhat longer helices than reported by Bowie, with some helices containing as many as 42 residues. Most of the helices in the soluble protein set are between 10 and 19 residues long with an average length of 18 ± 7 residues, compared to an average length of TM helices of 26 ± 6. Helix lengths in the homologous set are very similar to helices in the soluble set. The distribution of helix lengths for the best-hit set is shifted toward longer helices, as expected, with an average length of 24 ± 9 residues. In contrast to TM helices, there are very few helices in soluble proteins longer than 25 residues, and these belong to the family of coiled coils.
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10% of the interacting helices in soluble proteins have packing angles outside of this range. The soluble protein data set and the homologous set show a weaker preference than the TM helices for class c packing whereas the best-hit set does show a strong preference for this orientation. Normalized frequencies, as used by Bowie, where the frequencies are divided by the frequencies of the same packing angle for noninteracting helices, were also calculated and found to give the same conclusions (data not shown).
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21 residues. The range of values is such that loop length does not appear to be a good indicator of whether two helices will interact; indeed, there are cases where very short loops connect noninteracting helices.
Interhelical distances
As shown in Fig. 5, interacting helices in membrane proteins tend on average to be closer together than interacting helices in soluble proteins. The average of the shortest C
-C
distance between any two helices is 5.5 ± 1.2 Å for membrane proteins, 6.0 ± 1.1 Å for the soluble set, 5.8 ± 1.1 Å for the homologous set, and 5.7 ± 1.1 Å for the best-hit set. As will be discussed below, the fact that interhelical distances are, on average, smaller in TM helices than in soluble proteins does not necessarily imply that membrane proteins are more closely packed (where packing is defined in terms of the volume of cavities between residues) but rather appears to reflect the size of the residues in the helix-helix interface. Indeed, over a third of the interacting helices in soluble proteins have smaller C
-C
distances than the average for interacting TM helices. Since the above averages are within one standard deviation, it is feasible that the values for the soluble and TM data sets might approach one another as the number of TM protein structures increases. To check the likelihood of this, an unpaired two-tailed t-test was carried out, and the difference between these two data sets was found to be statistically significant, with p < 0.0001. As was the case for the packing angles, it is apparent that the PSD cutoff used for the homologous set is not stringent enough to detect a distribution that is significantly shifted from that of the full soluble-protein data set. In contrast, the best-hit set shows a distribution that is similar to that of TM helix pairs.
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33% of the TM helices, 26% of the best hits, and 11% of each of the soluble and the homologous set helices are kinked. In addition, 1% of the TM helices have an unwound segment. However, as expected, fully unwound helices are not observed in the data set of soluble proteins in this study, since helical regions (including
-, 310-, and
-helices) were identified using DSSP only.
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-C
distances (<4.5 Å). The distance of 4.5 Å was chosen as a cutoff because it is
1 standard deviation less than the average distance between helices in TM helix pairs. The number of glycine residues is significantly increased in closely packed helices in all four data sets, and increases are also observed for Ala and Ser residues. It is clear that these three residues, and in particular Gly and Ala, are used to facilitate close packing between helices.
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of the pairs of helices in all four data sets contain at least one AxxxA motif (Table 2). In contrast, the TM set of helix pairs is the only case where a very high proportion contains the GxxxG motif (30%), consistent with the relative enrichment of glycine residues in TM proteins (Fig. 8). It can be seen that the percentage of helix pairs that contain AxxxA and GxxxG motifs increases significantly in all four data sets when considering only those helix pairs separated by <4.5 Å. The only exception is a small decrease in the number of GxxxG motifs in the best-hit set, perhaps reflecting the small number of pairs of helices, and correspondingly poor statistics, for this data set. In agreement with previous work then, it is apparent that the three sequence motifs facilitate the close packing of
-helices, and that the over-representation of glycine residues leads to increases in the number of closely associated pairs of helices in TM proteins.
However, we also observed cases where closely associated TM pairs with one of the three sequence motifs were able to superimpose almost perfectly on a pair of helices from the soluble set that had no corresponding sequence motifs. In such cases, the side chains of the larger residues located in the interface of helices from the soluble set were oriented sideways, away from the interface, thus allowing very close approach of the two helices. An example of this can be found in the structural alignment of helices 1 and 4 of the glycerol facilitator (1fx8) with helices 7 and 20 of nitroreductase (1f5v), from the best-hit set, which has a C
RMSD of 1.4 Å, and a PSD of 0.085. The AxxxA motif in the TM protein aligns structurally with methionine and glutamine residues in the positions corresponding to the alanine residues, but the side chains of the larger amino acids are oriented away from the interface so that the helix backbones are only 4.9 Å apart at their closest point (cf. 4.3 Å in the TM helix pair). More generally, in only 18% of cases does the structural superposition of motif-containing helix pairs from the TM and best-hit set cause the corresponding sequence motifs to be aligned. Thus, although the presence of a motif in a soluble protein facilitates closer approach of the helices, and hence a TM-like packing interaction, the matching of sequence motifs should probably not be considered a reliable modeling heuristic. Nonetheless, the overlap of structural properties between membrane- and soluble-protein helix pairs suggests that soluble proteins may be useful as templates during membrane-protein modeling in that the backbone geometries in the two sets of helices can overlap remarkably well.
Hydrogen bonds
A total of 147 side chain-side chain hydrogen bonds and 133 side chain-backbone hydrogen bonds were identified in the 265 pairs of membrane-protein helices using the geometric criteria of Stickle (Stickle et al., 1992
) as implemented in the GRASP2 program (Petrey and Honig, 2003
). Briefly, these require an angle of 90180° at the donor atom, and an angle of 90180° or 60180° (for sp2 and sp3 hybridized acceptors, respectively) at the acceptor atom; the heavy-atom bond distance must be <3.2 Å, and deviations from planarity of the entire group are allowed for up to 60° or 90° (for sp2 and sp3 hybridized acceptors, respectively). Fig. 9 shows the distribution of interhelical hydrogen bonds in helix pairs from membrane and soluble proteins. In both cases there is an average of
1 hydrogen bond per pair, although
1/2 of the helix pairs have no hydrogen bonds. These numbers are similar to those published earlier for a smaller set of membrane proteins by Adamian and Liang (2002)
, who noted that every TM helix makes at least one hydrogen bond. Overall, the distribution shown in Fig. 9 is remarkably similar for both membrane and soluble proteins. We find that membrane proteins have
50% side chain-backbone hydrogen bonds and 50% side chain-side chain hydrogen bonds. Soluble proteins in all three data sets have a higher percentage of side chain-side chain hydrogen bonds (72%, 74%, and 62% for soluble, homologous, and best-hit groups, respectively). The percentage of side chain-backbone hydrogen bonds (70%) is somewhat higher for TM helix pairs whose backbones are closer than 4.5 Å.
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| DISCUSSION |
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The main conclusion of this work is that most helix-helix interaction patterns seen in membrane proteins also appear in soluble proteins. This suggests that the soluble-protein database might provide a useful resource as templates for modeling helix-helix packing for many TM helix pairs. Most of the exceptions correspond to cases where the TM helix is irregular, a property that appears far more common in membrane proteins than in soluble proteins. As discussed above this appears correlated with the fact that TM helices are longer and therefore have a higher probability of having an irregularity somewhere. Identifying the locations of helical kinks and irregularities poses a serious challenge to homology modeling efforts. The fact that, at least in some cases, similar irregularities can be found in soluble proteins should prove to be helpful in developing prediction procedures. The recent article of Riek et al. (2001)
identified some "fuzzy" sequence signals that are characteristic of different types of helical kinks and described changes in axial direction at different types of helical boundaries. It will be of interest to determine whether sequence patterns associated with irregularities in soluble proteins can be used to enhance the statistics for such analysis.
It is clear from our study and from earlier work that similar packing constraints are operable in both soluble and membrane proteins. Grooves-into-ridges rules are largely obeyed and there are no dramatic differences between the packing patterns in the two types of proteins. Those differences that do existi.e., TM helices are much longer on average than those in soluble proteins, and there is a narrower distribution of packing anglesappear attributable to the constraints imposed by the lipid bilayer. There are, however, less obvious differences that have been detected previously, some of which are confirmed in the current study. The most notable of these is that the interhelical distances appear to be statistically significantly shorter on average in membrane proteins than in soluble proteins, an effect that appears due in part to the increased presence of small amino acids in the helical interface (Eilers et al., 2002
) such as the GxxxG and AxxxA motifs. However, our analysis also indicates that in some cases, close approach of helices in soluble-protein structures is achieved by other means, such as orientation of bulky side chains away from the helix-helix interface.
There is as yet no firm explanation as to why membrane proteins appear designed to have many short interhelical contact distances. One possibility that has been suggested is that tight packing contributes to membrane protein stability. However, it is important to point out that shorter helical contact distances do not necessarily imply stronger van der Waals forces since these are correlated with packing density and not the distance between helical axes. Indeed, our observation of a large number of pairs of helices in membrane proteins that are structurally equivalent to those found in soluble proteins suggests that the packing forces are similar in both cases. Bowie and coworkers have recently provided strong evidence that packing interactions provide an important driving force for helices in membrane proteins (Faham et al., 2004
). There are apparent differences between the driving forces for interhelical association in membrane and soluble proteins since the hydrophobic effect is only operative in the latter case. This might suggest a stronger driving force for association in the aqueous phase; however, the hydrophobic effect in soluble proteins is largely offset by the free energy penalty associated with desolvating hydrogen-bonded groups as two helices are brought together (Gilson and Honig, 1989
). Thus, it may well be that tight packing plays a comparable role in both types of proteins. However, at present this issue remains unresolved. Indeed the role of tight packing in driving the folding of soluble proteins has been difficult to clearly establish and is still an area of considerable uncertainty (see, e.g., Honig, 1999
; Liang and Dill, 2001
). A similar balance of forces between helices in membrane and soluble proteins is also consistent with the observation that the number of interhelical hydrogen bonds per helix is almost identical for helices in the two environments (Fig. 9, and Adamian and Liang, 2002
).
It is interesting to consider the issue of relative packing forces in light of the study of Eilers et al. (2000)
who found that helices in membrane proteins have higher packing values than helices in soluble proteins. The data of Eilers et al. (2000)
suggests that the results of the two analyses are not mutually inconsistent. A packing value is the fraction of the occluded surface of a residue that is in contact with other residues and the distribution of distances to neighboring atoms (Fleming and Richards, 2000
). The distribution of distances is directly related to the packing density but the relationship of buried area to packing density is more complicated. For example, a residue could be 50% buried with its buried area closely packed, whereas another residue might be 75% buried with its buried region less tightly packed against neighboring atoms. Two such residues might have the same packing value but would reflect a different balance of forces. It is interesting in this regard that Eilers et al. find no significant difference in the packing values between residues in membrane and soluble proteins that are >30% buried (Table 4 of Eilers et al., 2000
). Rather, the largest difference they detect between water-soluble and membrane proteins is in the fraction of residues that are more than 30% exposed (
16% in membrane proteins and
25% in soluble proteins). This suggests that the surfaces of soluble proteins are more irregular than those of membrane proteins, but that the interiors of the two classes of proteins are, in fact, very similar in packing density. This, in turn, might reflect the fact that the surfaces of membrane proteins contact alkane chains whereas those of soluble proteins interact with small water molecules that can more easily penetrate jagged, irregular surfaces.
If stability is the main reason for the close approach of many TM helices, what other causes are suggested? One possibility is simply that close approach in the contact region may allow helices to form larger interfaces, which in turn may facilitate their remaining in contact for a longer distance. This in turn may be required since TM helices must typically span the full width of the lipid bilayer. It was shown above that interacting helices in membrane proteins have larger interfaces on average than in soluble proteins. In Fig. 12 we plot interface size as a function of the shortest C
-C
distance. The strong correlation that is observed suggests that geometric rather than energetic factors may be responsible for the increased number of small residues in helical interfaces in membrane proteins. Finally, it is possible that the smoother helical faces that result from having small interfacial residues may facilitate interhelical motion, which appears important in the function of membrane proteins (see, e.g., Curran and Engelman, 2003
).
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Finally, the fact that so many pairs of helices in membrane proteins have close structural homologs in soluble proteins demonstrates that helical interfaces can be quite similar even if the protein surface, and solvent environment, are very different. This in turn suggests that solubilizing membrane proteins by mutating surface residues would not introduce forces that disrupt the internal packing of the protein. Of course small differences in the conformational free energies between the folded and unfolded states have the potential of complicating this strategy in many cases.
| SUPPLEMENTARY MATERIAL |
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| ACKNOWLEDGEMENTS |
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Support from the National Science Foundation (MCB-0416708 to B.H. and MCB-0212362 to D.M.) is gratefully acknowledged.
Submitted on July 15, 2004; accepted for publication September 27, 2004.
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