| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
1 Faculty of Pharmacy, The University of Sydney, Sydney, N.S.W. 2006, Australia
2 Arthritis and Inflammation Research Program, The Garvan Institute of Medical Research, Sydney, N.S.W. 2010, Australia
Reprint requests to: Dr. W. Bret Church, Molecular Biotechnology Program, Department of Biochemistry G08, The University of Sydney NSW 2006, Australia; e-mail: b.church{at}biotech.usyd.edu.au; fax: 61–2–9351–5858.
(RECEIVED February 15, 2001; FINAL REVISION April 19, 2001; ACCEPTED May 3, 2001)
3 Present address: Molecular Biotechnology Program, Department of Biochemistry, The University of Sydney, Sydney, N.S.W. 2006, Australia. 
Article and publication are at http://www.proteinscience.org/cgi/doi/10.1101/ps.6301
 |
Abstract |
|---|
 TOP Abstract IntroductionResultsDiscussionMaterials and methodsReferences |
|---|
Keywords: Membrane proteins; transmembrane helices; fold recognition; molecular modeling; protein structure; structure prediction; GPCRs
|
Introduction |
|---|
|
TOPAbstractIntroductionResultsDiscussionMaterials and methodsReferences |
|---|
Comparative modeling of the three-dimensional structures of proteins based on sequence similarity can now be applied with reasonable accuracy to ten times more protein sequences than the number of experimentally determined protein structures (Sanchez and Sali 1997). Although this approach becomes unreliable when the sequence identity drops below 20–30% (Sander and Schneider 1991), it has been estimated that more than 25% of all sequences in the SWISS-PROT sequence database can be modeled by homology (Rost et al. 1995). The success of such modeling aside, knowledge about the structure of IMPs remains sparse because so few high-resolution three-dimensional structures are available (Table 1
). This lack of experimental data means that it is not usually possible to use sequence homology methods to build accurate three-dimensional models of IMPs.
|
In the Profiles-3D inverse-folding method (Biosym/Molecular Simulations, Profiles-3D 95.0), the physicochemical environments of residues in the three-dimensional structures of proteins are quantified in terms of (1) the area of a residue's side chain buried away from the aqueous phase, (2) the fraction of side-chain area in contact with a polar environment (polar atoms from the aqueous phase and from other residues), and (3) local secondary structure (Bowie et al. 1991; Luthy et al. 1992). Based on these criteria, the probability of finding specific residues in a particular class of environment can be estimated by analyzing the well-defined structures of a set of water-soluble proteins. These probabilities are used to generate a 3D
1D scoring table which can be used to link sequences and three-dimensional structures together; that is, possible structures for a protein can be generated following the conversion of the string of residues to a string of environment classes. In addition to finding compatible structures for a given sequence, the alignment of an amino acid sequence with a 3D profile can be used for other purposes such as testing the validity of a preliminary or model structure, and finding sequences compatible with a defined structure.
We considered that such a general quantitative description of environment preference could be adapted to predict structural features of IMPs. Despite the difference in polarity of their surrounding environments, it has been suggested that IMPs and water-soluble proteins are variations on common structural themes, differing primarily in the polarity of the residues on the protein surface (Rees et al. 1989). Our aim was to modify the Profiles-3D approach so that it would take into account the fact that certain residues in IMPs are exposed to a lipid environment rather than an aqueous environment. By making this correction, it should be possible to predict structural features of IMPs and to assess the validity of both experimentally determined and modeled structures of IMPs.
|
Results |
|---|
|
TOPAbstractIntroductionResultsDiscussionMaterials and methodsReferences |
|---|
shows the total of the compatibility scores for ten representative IMPs whose structures are known to high resolution. When using the Profiles-3D program alone, the assumption is made that all residues on the surface of the protein are exposed to an aqueous environment. This gives rise to totals of the compatibility scores which are less than the scores expected for these proteins based on their sequence lengths. In fact, for bacteriorhodopsin, the value of the total score is close to the lowest acceptable score. A score below this indicates that the structure is incorrect. In this case, however, the low Profiles-3D score probably does not indicate an incorrect structure but rather indicates that 56% of the surface area of bacteriorhodopsin is exposed to a lipid rather than an aqueous environment.
|
and A*b (see Materials and Methods for details). On this basis, the totals of the compatibility scores for these proteins are now similar to or exceed the expected scores in all cases (Table 2
). As expected, the biggest percentage correction was for bacteriorhodopsin, whose score improved 
150%. Other than for halorhodopsin and mechanosensitive ion channel, the relative improvements are smaller for the other proteins such as cytochrome c oxidase and the photosynthetic reaction center because a smaller percentage of residues are in contact with lipid.
Grigorieff et al. (1996) reported the presence of ten lipid molecules (phosphoric acid 2,3-bis-(3,7,11,15-tetramethyl-hexadecyloxy)-propyl ester 2-hydroxo-3-phosphonoxy-propyl ester) associated with bacteriorhodopsin. The lipid molecules are mainly in contact with helices I, II, IV, VI, and VII. In contrast, helices II and V are not covered or are only partially covered by the lipid molecules. The compatibility scores for the residues in contact with the lipid molecules decreased after eliminating the lipid molecules, whereas the scores for residues which were not covered by the lipid molecules remained the same (Fig. 1). This result also highlights the need to consider the presence of a lipid environment when calculating compatibility scores.
|
-helices of bacteriorhodopsin, photosynthetic reaction center, and cytochrome c oxidase, we calculated the areas of the side chains exposed to lipid and averaged this area per residue. We then calculated the compatibility score for each of these transmembrane domains assuming that the protein had been inserted into a membrane, subtracted the score calculated assuming an aqueous environment, and divided the difference by the number of residues involved. The final value is a measure of the improvement in the compatibility score for the transmembrane domain compared to what would normally be calculated using Profiles-3D. Figure 2 shows the correlation between this improved score and the average area of side chain exposed to lipid. As expected, those transmembrane domains which had the greatest area per residue exposed to the lipid had the largest improvement in their compatibility score per residue.
|
shows that the total of the compatibility scores for helix VII of bacteriorhodopsin was maximal near the beginning and end of the rotation process (i.e., near 0° and 360°), which corresponds to the native position of the helix in the 3D structure. The total generally falls in the middle of the rotational range, indicating that residues were being placed in incompatible environments. Similar trends were observed for helices I–V of this protein. Helix VI, however, was an exception with the plot showing a broad maximum centered at 130° (data not shown) and the value at 0° being among the lowest calculated. The results for all helices were similar in both the presence and absence of retinal.
|
100°, resulting in the loss of one residue from one end of the transmembrane segment, and the addition of a new residue to the other end of the segment. Figure 3B shows that the total of the compatibility scores for helix II of bacteriorhodopsin drops progressively from its maximum value obtained with the helix in the native position. This was also the case for helices I–V, and VII, both in the absence and presence of retinal. Again, helix VI did not exhibit the same behavior as the other helices; it showed no obvious trend with rotation.
Validating the location of transmembrane domains using REPIMPS
We tested whether our method could accurately locate the transmembrane domain of IMPs containing a single helix crossing the membrane. First, a preliminary set of 15 proteins was selected from the SWISS-PROT and Tr EMBL protein sequence databanks, each protein believed to contain a single -helical TM domain. The polypeptide for each selected protein was folded into a single ideal helix. Compatibility scores for each residue based on a lipid environment were calculated, and the resulting values were plotted against the residue number for each of the 15 proteins. Figure 4 shows the result for HLA class I histocompatibility antigen (SWISS-PROT code 30443). The compatibility scores for residues 308–332 are all strongly positive, indicating that this region defines the transmembrane domain. The boundaries of the domain are sharply defined, because the compatibility scores of consecutive residues switched from being negative immediately outside the transmembrane domain to positive within the domain. Other methods (Table 3) of estimating the location of transmembrane domains also place the transmembrane domain of HLA class I histocompatibility antigen in this region, and the same region is reported in SWISS-PROT (Bairoch and Apweiler 2000).
|
|
). For 14 of the 15 proteins, REPIMPS selected the SWISS-PROT deposited location of the transmembrane domain and was superior to the other five methods. For one of the proteins (neurogenic locus delta protein precursor, SWISS-PROT accession number P10041), REPIMPS selected a sequence for the transmembrane domain (residues 595–619) different from that listed in the SWISS-PROT database (residues 654–677). However, all of the other five methods used selected a region similar to that selected by REPIMPS as being transmembrane, and none predicted the location stated in the database. For two other proteins, the Ser/Thr-protein kinase IRE1 precursor (SWISS-PROT accession number P32361) and a 40.1 kD protein encoded by the HMC operon of Desulfovibrio vulgaris (SWISS-PROT accession number P33389), REPIMPS selected the correct position of the transmembrane domain plus one and two additional regions, respectively, as transmembrane domains.
|
-helix) at each starting position of the sliding window was calculated and plotted against the starting position (Fig. 5). A line of moving average per eight data points gave rise to seven peaks corresponding to the positions of the seven transmembrane segments of bacteriorhodopsin (Fig. 5).
|
|
Discussion |
|---|
|
TOPAbstractIntroductionResultsDiscussionMaterials and methodsReferences |
|---|
. By taking into consideration the fact that certain residues in IMPs are exposed to a lipid environment, the total of the compatibility scores for a series of IMPs whose three-dimensional structures are known universally improved such that they were now close to or exceeded the expected scores (Table 2; Fig. 1). In addition, the greater the average area of exposure of transmembrane residues to the lipid environment, the greater the improvement in the compatibility score (Fig. 2). Thus, correcting for the presence of the lipid environment surrounding transmembrane segments is an essential step for reasonable modeling and verification of the three-dimensional structures of IMPs. It should be possible to refine this approach by producing a scoring table specifically for the transmembrane segments based on the currently available three-dimensional structures of IMPs. The table itself could be refined as further high-resolution structures of IMPs become available. The relative orientation and depth of the helical transmembrane segments are important structural features of IMPs. Usually the decision on determining the interior-facing side or lipid-facing side of helical transmembrane segments is made by the analysis of hydrophobicity moments or conservation patterns in these regions. In general, the hydrophobic and less-conserved side is more likely to face toward the lipid bilayer (Baldwin et al. 1997). However, sometimes a clearly more hydrophobic side of a transmembrane helix is not apparent or there are no homologous proteins to determine the conserved face of the helix.
The suitability of our method for determining the relative orientation of TM segments can be inferred by the results shown in Figure 3. Although the biologically relevant form of bacteriorhodopsin is the trimer (Grigorieff et al. 1996; Muller et al. 1997; Moller et al. 2000), we have performed calculations on monomeric bacteriorhodopsin on the basis that contacts between monomeric subunits in the trimer are predominantly hydrophobic (e.g., see PDB accession number 1AP9). Our method predicted the correct orientation of six out of seven helical transmembrane segments of bacteriorhodopsin; that is, the highest total of the compatibility scores belonged to the helix in its native orientation, while deviation from the native position reduced the total. Helix VI proved to be the exception, indicating either that our methodology needs to be improved or that some functional significance is associated with this helix. Subramaniam et al. (1999) suggested that the movements of four helices (I, II, VI, and VII) are involved in bacteriorhodopsin's proton pumping. For example, helix VII moves in the transition between states BR and M resulting from an isomerization of retinal (Luecke et al. 1999), and it has been suggested that at least two residues, Val177 and Trp182, move in helix VI. Luecke et al. (1999) also suggested a refinement of the description of a tilt in helix VI, with Tyr185 and Pro186 acting as a hinge during proton pumping. In addition, helix VI may play a role in other states of the transport cycle, including state O. Our method cannot describe precise conformational changes, but it may be useful in identifying regions in IMPs that have functional consequences.
We also used REPIMPS to predict the TM segments of IMPs which span the bilayer just once. Figure 4 shows the TM region of the HLA histocompatibility antigen predicted by our method, which is in agreement with the reported results (Bairoch and Apweiler 2000). In a further test, the accuracy of predicting TM segments by our method for a set of 15 such proteins was compared to that of other methods. The results in Table 4 strongly support the capability of the method to predict the location of helical TM segments with greater accuracy than a series of other methods. The only `incorrect' predictions made by REPIMPS were as follows: For the neurogenic locus delta protein precursor (SWISS-PROT accession number P10041), the single transmembrane domain selected was shifted 60 residues to the N-terminal side of the location of the domain, as deposited in SWISS-PROT. However, all of the other five prediction methods used also located the transmembrane domain to the same position as REPIMPS, and none predicted the location listed in SWISS-PROT. For the 40.1 kD protein encoded by the HMC operon of D. vulgaris (SWISS-PROT accession number P33389), REPIMPS selected two additional transmembrane segments in addition to the correct segment. The location of one of the `incorrect' segments (residues 229–247) was also predicted by TopPred, whereas the location of the second `incorrect' segment (residues 6–33) was predicted by three of the five other methods used. For the Ser/Thr-protein kinase IRE1 precursor (SWISS-PROT accession number P32361), REPIMPS selected one additional transmembrane segment (residues 8–26) in addition to the correct segment (residues 531–555). However, all of the other methods predicted the presence of the additional transmembrane segment.
In a final validation of the REPIMPS method, we tested its ability to successfully predict the location of the seven transmembrane segments for bacteriorhodopsin (Fig. 5). This involved transforming the structure of bacteriorhodopsin into an ideal helix and calculating the compatibility scores for the residues assuming the whole structure was placed in a lipid environment. Under these circumstances, those residues that would normally be extramembrane and therefore exposed to the aqueous environment should receive low compatibility scores. Within the -helical transmembrane domains of the native structure, there should be a periodicity in the residues facing the lipid environment based on the natural periodicity of the -helix of 3.6 residues/turn, and those residues would be expected to receive a high compatibility score. Using this approach (Fig. 5), we observed seven maxima, with each maximum located close to the center of a transmembrane domain of bacteriorhodopsin.
In summary, we have modified an environment-based inverse-folding method originally developed for water-soluble proteins. This approach has the potential to assess the validity of experimentally determined IMP structures and model structures and to predict structural features of IMPs of unknown structure. We are in the process of optimizing the parameters for our method and extending the work presented here to test other structural parameters such as packing. For example, it may be possible to develop other potential terms based on the success of other inverse-folding methods used for water-soluble proteins. In addition, we are in the process of refining our method for assessing the reliability of models of IMP structures by encompassing a description of the membrane environment. Methodologies based on inverse-folding potentials promise advantages over sequence-alignment methods. Because only a small number of existing structural templates for IMPs exist, we hope to examine the generality of the templates themselves, with the goal of reducing reliance on multiple sequence alignment and secondary structure in predicting the three-dimensional structures of IMPs.
|
Materials and methods |
|---|
|
TOPAbstractIntroductionResultsDiscussionMaterials and methodsReferences |
|---|
The Profiles-3D software
For each residue in a protein of known three-dimensional structure, the Profiles-3D software will calculate (1) the area of each residue's side chain that is buried away from the aqueous phase (Bowie et al. 1991), (2) the fraction of the area of each residue's side chain that is in contact with polar atoms (either from the solvent or other atoms in the protein), and (3) the secondary structure (-helix, ß-strand, and other) for the residue based on the KABSCH-SANDER algorithm (Kabsch and Sander 1983). Based on this information, each residue is assigned to one of 18 environment classes. A profile table can then be constructed in which each position in the sequence is assigned an environment class and a compatibility score for the residue filling the position. The compatibility scores are derived from a basic set of 16 water-soluble proteins whose three-dimensional structures are known to high resolution and which represent a variety of protein folds. The total of the compatibility scores, taking into account the size of the protein, can be used to assess the validity of the structure.
Correcting compatibility scores for residue side-chains in a lipid environment
For IMPs whose three-dimensional structures are known to high resolution (Table 1), a significant proportion of the residues would normally be in contact with lipids of the membrane rather than the aqueous environment. Thus, a correction to values of the areas of a side chain buried away from the aqueous phase and in contact with polar atoms is required for those residues within the membrane. The equation used to correct the fractional area of side chain in contact with polar atoms, F*, is:
 | (1) |
carbon atom (Bowie et al. 1991). For those residues within the membrane, the total area of side chain buried away from the aqueous environment (A*b) was considered to be equal to At. By using F*, A*b, and the local secondary structure of each residue located within the membrane of an IMP, it is possible to assign the appropriate environment class for each residue from the set of 18 environment classes. In this way, a residue exposed to lipid will be assigned differently and will have a new compatibility score, whereas a residue exposed to the aqueous phase will retain the original class and compatibility score normally assigned by Profiles-3D.
Table 2 shows those proteins for which corrected compatibility scores were obtained. Each of these proteins (except for porin and outer membrane phospholipase A) contains helical transmembrane domains. An empirical approach was used to identify the boundary between those residues in the polypeptide sequences exposed to the aqueous phase and those buried in the membrane. This was done by first calculating (using Profiles-3D) the compatibility scores for each residue in an IMP assuming that the IMP was exposed only to water, and then recalculating (using an in-house Fortran program) the values using Equation 1 assuming the protein was entirely within the lipid membrane. For the proteins with helical transmembrane domains, the point within each helix at which a marked improvement in the compatibility score was observed for the lipid-based value over the water-based value was taken to be the boundary (Table 3). This approach accommodates the situation where a helical region may extend beyond the membrane into the aqueous environment. In 75% of cases, this boundary was clear. In those cases where the boundary was not as clearly defined by this approach, one turn of helix was considered to lie outside of the lipid membrane. A similar approach was used to locate the boundaries of porin. In those cases where the boundary was not clear, it was assumed that charged or polar residues (Ser, Thr, Tyr, Asn, Gln) represented the location of the boundary and that residues at the top of the ß turns were located outside of the membrane. It was assumed that water molecules filled the pore of the protein.
Once the boundaries were located, the total of the compatibility scores for an IMP structure was calculated using the lipid-based values for those residues located in the lipid bilayer and water-based values for those residues lying outside the bilayer (Table 3).
Rotation of individual helices within bacteriorhodopsin
Bacteriorhodopsin was selected because it contains seven close-to-ideal helices approximately perpendicular to the membrane. The crystallized protein appears to retain both native conformation and activity (Portmann et al. 1991; Landau and Luisi 1993; Hochkoeppler et al. 1995). The rotation of individual helices was performed in two ways: (1) An individual helix was selected, the long axis of the helix located, and the amide bonds at the boundaries of the helix cleaved. Fixed rotations of 10° around the long axis were then performed through the InsightII command line. After each rotation, the amide bonds were reformed, and the total of the compatibility scores for the chosen helix was recalculated. (2) An individual helix was selected and effectively screwed into or out of the membrane one residue at a time. In order to simulate this type of rotation, we used the mutation tool of the Swiss-PdbViewer program (v3.5b1). The backbone coordinates of the selected helix remained the same but the first residue of the helix within the lipid environment was replaced by the previous residue. In the same way, the second residue was replaced by the first residue. This residue replacement procedure was continued up to the end of the membrane region of the helix and left the last residue, previously lying within the membrane, now lying outside of it. This in fact simulates the translation of the helix into the membrane by a distance corresponding to the vertical distance between two consecutive C in helix and a 100° rotation around the helix axis. The mutation tool in Swiss-PdbViewer automatically selects the most favorable rotamer to minimize steric clashes while increasing the number of hydrogen and disulfide bonds (Ponder and Richards 1987). Any remaining steric clashes were eliminated later either manually or using the "Fix selected side chains" option from the Tools menu.
Detecting the transmembrane region of IMPs with a single transmembrane domain
The sequences of a random selection of 15 IMPs each believed to contain a single -helical transmembrane domain were downloaded from SWISS-PROT and Tr EMBL. For this set, the highest pairwise alignment score was 19%. The sequence for each selected protein was folded into a single ideal helix using the Swiss-PdbViewer program (v3.5b1). The -helical structures were built from the sequences in FASTA format (Guex and Peitsch 1997). Side chains were placed automatically by the program in most favorable rotamer (Ponder and Richards 1987). A compatibility score for each residue in each protein was then calculated based on all residues being in a lipid environment.
Several other prediction methods were used to detect the location of transmembrane regions of the set of 15 single -helix-containing IMPs listed in Table 4. These programs were run from their web sites with the various options set at default values. The names and the web addresses of these programs are as follows: SOSUI (Hirokawa et al. 1998), http://sosui.proteome.bio.tuat.ac.jp/sosuiframe0E.html.; SPLIT35 (Juretic and Lucin 1998), http://pref.etfos.hr/split/; Tmpred, http://www.ch.embnet.org/software/TMPRED_form.html; TMHMM (v. 0.1) (Sonnhammer et al. 1998), http://www.cbs.dtu.dk/services/TMHMM-1.0/; and TopPred2 (von Heijne 1992), http://www.sbc.su.se/erikw/toppred2/.
Predicting the location of the seven transmembrane domains in bacteriorhodopsin
The sequence of bacteriorhodopsin was folded into a single ideal helix using the Swiss-PdbViewer program, as described above, and the compatibility score for each residue was then calculated based on all residues being in a lipid environment. A Fourier analysis was performed on the string of compatibility scores using a Fortran program modified from the original code of Cornette (Cornette et al. 1987). The program calculated the power spectrum of the Fourier analysis using a sliding window of 14–18 residues.
|
Acknowledgments |
|---|
The publication costs of this article were defrayed in part by payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 USC section 1734 solely to indicate this fact.
|
References |
|---|
|
TOPAbstractIntroductionResultsDiscussionMaterials and methodsReferences |
|---|
Bairoch, A. and Apweiler, R. 2000. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res. 28: 45–48.
Baldwin, J.M., Schertler, G.F.X., and Unger, V.M. 1997. An alpha-carbon template for the transmembrane helices in the rhodopsin family of G-protein-coupled receptors. J. Mol. Biol. 272: 144–164.[CrossRef][Medline]
Berman, H.M., Westbrook, J., Feng, Z., Gililand, G., Bahat, T.N., Weissig, H., and Shindyalov, P.E. 2000. The protein data bank. Nucleic Acids Res. 28: 235–242.
Bowie, J.U. and Eisenberg, D. 1993. Inverted protein structure prediction. Curr. Opin. Struct. Biol. 3: 437–444.
Bowie, J.U., Luthy, R., and Eisenberg, D. 1991. A method to identify protein sequences that fold into a known three-dimensional structure. Science 253: 164–170.
Brunger, A.T., Adams, P.D., and Rice, M.L. 1998. Recent developments for the efficient crystallographic refinement of macromolecular structures. Curr. Opin. Struct. Biol. 8: 606–611.[CrossRef][Medline]
Bryant, S.H. and Lawrence, C.E. 1993. An empirical energy function for threading protein sequence through the folding motif. Proteins 16: 92–112.[CrossRef][Medline]
Case, D.A. 1998. The use of chemical shifts and their anisotropies in bimolecular structure determination. Curr. Opin. Struct. Biol. 8: 624–630.[CrossRef][Medline]
Ceska, T.A. and Henderson, R. 1990. Analysis of high-resolution electron diffraction patterns from purple membrane labeled with heavy-atoms. J. Mol. Biol. 213: 539–560.[CrossRef][Medline]
Chang, G., Spencer, R.H., Lee, A.T., Barclay, M.T., and Rees, D.C. 1998. Structure of the MscL homolog from Mycobacterium tuberculosis: A gated mechanosensitive ion channel. Science 282: 2220–2226.
Chirino, A.J., Lous, E.J., Huber, M., Allen, J.P., Schenck, C.C., Paddock, M.L., Feher, G., and Rees, D.C. 1994. Crystallographic analyses of site-directed mutants of the photosynthetic reaction center from Rhodobacter sphaeroides. Biochemistry (Mosc). 33: 4584–4593.[CrossRef]
Cornette, J.L., Cease, K.B., Margalit, H., Spouge, J.L., Berzofsky, J.A., and DeLisi, C. 1987. Hydrophobicity scales and computational techniques for detecting amphipathic structures in proteins. J. Mol. Biol. 195: 659–685.[CrossRef][Medline]
Deisenhofer, J., Epp, O., Sinning, I., and Michel, H. 1995. Crystallographic refinement at 2.3 A resolution and refined model of the photosynthetic reaction centre from Rhodopseudomonas viridis. J. Mol. Biol. 246: 429–457.[CrossRef][Medline]
Dotsch, V. and Wagner, G. 1998. New approaches to structure determination by NMR spectroscopy. Curr. Opin. Struct. Biol. 8: 619–623.[CrossRef][Medline]
Doyle, D.A., Cabral, J.M., Pfuetzner, R., and Michel, H. 1998. The structure of potassium channel: Molecular basis of K+ conduction and selectivity. Science 280: 69–77.
Ermler, U., Fritzsch, G., Buchanan, S.K., and Michel, H. 1994. Structure of the photosynthetic reaction centre from rhodobacter sphaeroides at 2.65 angstroms resolution: Cofactors and protein-cofactor interactions. Structure 2: 925–936.[Medline]
Godzik, A. 1995. In search of the ideal protein sequence. Protein Eng. 8: 409–416.
Godzik, A., Kolinski, A., and Skolnick, J. 1993. De novo and inverse folding predictions of protein structure and dynamics. J. Comput. Aided Mol. Des. 7: 397–438.[CrossRef][Medline]
Goffeau, A., Nakai, K., Slonimski, P., and Risler, J.L. 1993. The membrane proteins encoded by yeast chromosome III genes. FEBS Lett. 325: 112–117.[CrossRef][Medline]
Grigorieff, N., Ceska, T.A., Downing, K.H., Baldwin, J.M., and Henderson, R. 1996. Electron-crystallographic refinement of the structure of bacteriorhodopsin. J. Mol. Biol. 259: 393–421.[CrossRef][Medline]
Guex, N. and Peitsch, M.C. 1997. SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling. Electrophoresis 18: 2714–2723.[CrossRef][Medline]
Henderson, R., Baldwin, J.M., Ceska, T.A., Zemlin, F., Beckmann, E., and Downing, K.H. 1990. Model for the structure of bacteriorhodopsin based on high-resolution electron cryo-microscopy. J. Mol. Biol. 213: 899–929.[Medline]
Hirokawa, T., Boon-Chieng, S., and Mitaku, S. 1998. SOSUI: classification and secondary structure prediction system for membrane proteins. Bioinformatics 14: 378–379.
Hochkoeppler, A., Landau, E.M., Venturoli, G., Zannoni, D., Feick, R., and Luisi, P.L. 1995. Photochemistry of a photosynthetic reaction centre immobilized in lipidic cubic phases. Biotechnol. Bioeng. 46: 93–98.
Hu, W.P., Godzik, A., and Skolnick, J. 1997. Sequence-structure specificity—how does an inverse folding approach work? Protein Eng. 10: 317–331.
Hubbell, W.L., Gross, A., Langen, R., and Lietzow, M.A. 1998. Recent advances in site-directed spin labeling of proteins. Curr. Opin. Struct. Biol. 8: 649–656.[CrossRef][Medline]
Iwata, S., Ostermeier, C., Ludwig, B., and Michel, H. 1995. Structure at 2.8 Å resolution of cytochrome c oxidase from Paracoccus denitrificans. Nature 376: 660–669.[CrossRef][Medline]
Jones, D.T. 1998. Do transmembrane protein superfolds exist. FEBS Lett. 423: 281–285.[CrossRef][Medline]
Jones, D.T., Bryson, K., Tress, M.L., and Hadley, C. 1999. Successful protein fold recognition using sequence and secondary structure constrained threading methods. Proteins S3: 104–111.
Jones, D.T., Taylor, W.R., and Thornton, J.M. 1992. A new approach to protein fold recognition. Nature 358: 86–89.[CrossRef][Medline]
Juretic, D. and Lucin, A. 1998. The preference functions method for predicting protein helical turns with membrane propensity. J. Chem. Inf. Comput. Sci. 38: 575–585.[CrossRef]
Kabsch, W. and Sander, C. 1983. Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22: 2577–2637.[CrossRef][Medline]
Kimura, Y., Vassylyev, D.G., Miyazawa, A., Kidera, A., Matsushima, M., Mitsuoka, K., Murata, K., Hirai, T., and Fujiyoshi, Y. 1997. Surface of bacteriorhodopsin revealed by high-resolution electron crystallography. Nature 389: 206–211.[CrossRef][Medline]
Koepke, J., Hu, X., Muenke, C., Schulten, K., and Michel, H. 1996. The crystal structure of the light-harvesting complex II (B800-850) from Rhodospirillum molischianum. Structure 4: 581–597.[Medline]
Koretke, K.K., Russell, R.B., Copley, R.R., and Lupas, A.N. 1999. Fold recognition using sequence and secondary structure information. Proteins S3: 141–148.
Kreusch, A., Neubueser, A., Schiltz, E., Weckesser, J., and Schulz, G. 1994. The structure of the membrane channel porin from Rhodopseudomonas blastica at 2.0 angstroms resolution. Protein Sci. 3: 58–63.[Abstract]
Kyrpides, N.C. 1999. Genomes OnLine Database (GOLD 1.0): A monitor ofcomplete and ongoing genome projects world-wide. Bioinformatics 15: 773–774.
Landau, E.M. and Luisi, P.L. 1993. Lipidic cubic phases as transparent, rigid matrices for the direct spectroscopic study of immobilized membrane proteins. J. Am. Chem. Soc. 115: 2102–2106.[CrossRef]
Luecke, H., Richter, H.T., and Lanyi, J.K. 1998. Proton transfer pathway in bacteriorhodopsin at 2.3 angstrom resolution. Science 280: 1934–1937.
Luecke, H., Schobert, B., Richter, H.T., Cartailler, J.P., and Lanyi, J.K. 1999. Structural changes in bacteriorhodopsin during ion transport at 2 angstrom resolution. Science 286: 255–260.
Luthy, R., Bowie, J.U., and Eisenberg, D. 1992. Assessment of protein models with three-dimensional profiles. Nature 356: 83–85.[CrossRef][Medline]
Marassi, F.M. and Opella, S.J. 1998. NMR structural studies of membrane proteins. Curr. Opin. Struct. Biol. 8: 640–648.[CrossRef][Medline]
McDermott, G., Prince, S.M., Freer, A.A., Hawthornthwaite-Lawless, A.M., Papiz, M.Z., Cogdell, R.J., and Isaacs, N.W. 1995. Crystal structure of an integral membrane light-harvesting complex from photosynthetic bacteria. Nature 374: 517–521.[CrossRef]
Mitsuoka, K., Hirai, T., Murata, K., Miyazawa, A., Kidera, A., Kimura, Y., and Fujioshi, Y. 1999. The structure of bacteriorhodopsin at 3.0 Å resolution based on electron crystallography: Implication of the charge distribution. J. Mol. Biol. 286: 861–882.[CrossRef][Medline]
Moller, C., Buldt, G., Dencher, N.A., Engel, A., and Muller, D.J. 2000. Reversible loss of crystallinity on photobleaching purple membrane in the presence of hydroxylamine. J. Mol. Biol. 301: 869–879.[CrossRef][Medline]
Muller, D.J., Schoenenberger, C.A., Schabert, F., and Engel, A. 1997. Structural changes in native membrane proteins monitored at subnanometer resolution with the atomic force microscope: A review. J. Struct. Biol. 119: 149–157.[CrossRef][Medline]
Murzin, A.G. 1999. Structure classification-based assessment of CASP3 predictions for the fold recognition targets. Proteins S3: 88–103.
Okada, T., Trong, I.L., Fox, B.A., Behnke, C.A., Stenkamp, R.E., and Palczewski, K. 2000. X-Ray diffraction analysis of three-dimensional crystals of bovine rhodopsin obtained from mixed micelles. J. Struct. Biol. 130: 73–80.[CrossRef][Medline]
Palczewski, K., Kumasaka, T., Hori, T., Behnke, C.A., Motoshima, H., Fox, B.A., Le Trong, I., Teller, D.C., Okada, T., Stenkamp, R.E., et al. 2000. Crystal structure of rhodopsin: A G protein-coupled receptor. Science 289: 739–745.
Pebay-peyroula, E., Rummel, G., Rosenbusch, J.P., and Landau, E.M. 1997. X-ray structure of bacteriorhodopsin at 2.5 angstroms from microcrystals grown in lipidic cubic phases. Science 277: 1676–1681.
Ponder, J.W. and Richards, F.M. 1987. Tertiary templates for proteins. Use of packing criteria in the enumeration of allowed sequences for different structural classes. J. Mol. Biol. 193: 775–791.[CrossRef][Medline]
Portmann, M., Landau, E.M., and Luisi, P.L. 1991. Spectroscopic and rheological studies of enzymes in rigid lipidic matrices: The case of a-chymotripsin in lysolectin/water phase. J. Phys. Chem. 95: 8437–8440.[CrossRef]
Rees, D.C., DeAntonio, L., and Eisenberg, D. 1989. Hydrophobic organization of membrane proteins. Science 245: 510–513.
Rost, B., Casadio, R., Fariselli, P., and Sander, C. 1995. Transmembrane helices predicted at 95% accuracy. Protein Sci. 4: 521–533.[Abstract]
Sanchez, R. and Sali, A. 1997. Advances in comparative protein-structure modelling. Curr. Opin. Struct. Biol. 7: 206–214.[CrossRef][Medline]
Sander, C. and Schneider, R. 1991. Database of homology-derived protein structures and the structural meaning of sequence alignment. Proteins 9: 56–68.[CrossRef][Medline]
Schertler, G.F., Villa, C., and Henderson, R. 1993. Projection structure of rhodopsin. Nature 362: 770–772.[CrossRef][Medline]
Sippl, M.J. 1990. The calculation of conformational ensembles from potentials of mean force, an approach to the prediction of local structures in globular proteins. J. Mol. Biol. 213: 659–683.
Sippl, M.J. 1995. Knowledge-based potentials for proteins. Curr. Opin. Struct. Biol. 5: 229–235.[CrossRef][Medline]
Snijder, H.J., Ubarretxena-Belandia, I., Blaauw, M., Kalk, K.H., Verheij, H.M., Egmond, M.R., Dekker, N. and Dijkstra, B.W. 1999. Structural evidence for dimerization- regulated activation of an integral membrane phospholipase. Nature 401: 717–721.[CrossRef][Medline]
Sonnhammer, E.L.L., von Heijne, G., and Krogh, A. 1998. A hidden Markov model for predicting transmembrane helices in protein sequences. Proc. Int. Conf. Intell. Syst. Mol. Biol. 6: 175–182.[Medline]
Stoddard, B.L. 1998. New results using laue diffraction and time-resolved crystallography. Curr. Opin. Struct. Biol. 8: 612–618.[CrossRef][Medline]
Stowell, M.H., McPhillips, T.M., Rees, D.C., Soltis, S.M., Abresch, E., and Feher, G. 1997. Light-induced structural changes in photosynthetic reaction centre: Implications for mechanism of electron-proton transfer. Science 276: 812–816.
Stowell, M.H.B., Miazawa, A., and Unwin, N. 1998. Macromolecular structure determination by electron microscopy: New advances and recent results. Curr. Opin. Struct. Biol. 8: 595–600.[CrossRef][Medline]
Subramaniam, S., Lindahl, M., Bullough, P., Faruq, A.R., Tittor, J., Oesterhelt, D., Brown, L., Lanyi, J.K., and Henderson, R. 1999. Protein conformational changes in the bacteriorhodopsin photocycle. J. Mol. Biol. 287: 145–161.[CrossRef][Medline]
Takeda, K., Sato, H., Hino, T., Kono, M., Fukuda, K., Sakurai, I., Okada, T., and Kouyama, T. 1998. A novel three-dimensional crystal of bacteriorhodopsin obtained by successive fusion of the vesicular assemblies. J. Mol. Biol. 283: 463–474.[CrossRef][Medline]
Tsukihara, T., Aoyama, H., Yamashita, E., Tomizaki, T., Yamaguchi, H., Shinzawa-Itoh, K., Nakashima, R., Yaono, R., and Yoshikawa, S. 1996. The whole structure of the 13-subunit oxidized cytochrome c oxidase at 2.8 Å. Science 272: 1136–1144.[Abstract]
von Heijne, G. 1992. Membrane protein structure prediction. Hydrophobicity analysis and the positive-inside rule. J. Mol. Biol. 225: 487–494.[CrossRef][Medline]
Weiss, M.S. and Schulz, G.E. 1992. Structure of porin refined at 1.8 Å resolution. J. Mol. Biol. 227: 493–509.[CrossRef][Medline]
Yoshikawa, S., Shinzawa-Itoh, K., Nakashima, R., Yaono, R., Yamashita, E., Inue, N., Yao, M., Fei, M.J., Libeu, C.P., Mizushima, T., et al. 1998. Redox-coupled crystal structural changes in bovine heart cytochrome c oxidase. Science 280: 1723–1729.
Zhang, Z.L., Huang, L.S., Shulmeister, V.M., Chi, Y.-I., Kim, K.K., Hung, L.-W., Crofts, A.R., Berry, E.A., and Kim, S.-H. 1998. Electron transfer by domain movement in cytochrome bc1. Nature 392: 677–684.[CrossRef][Medline]
CiteULike 
Connotea 
Del.icio.us 
Digg 
Reddit 
Technorati What's this?
| |||||||||||||||||||||||
