Protein Engineering vol.11 no.12 pp.1155–1161, 1998
Sequence properties of GPI-anchored proteins near the ω-site:
constraints for the polypeptide binding site of the putative
transamidase
Birgit Eisenhaber1,2,3, Peer Bork1,2 and
Frank Eisenhaber1,2
1European
Molecular Biology Laboratory, Meyerhofstrasse 1, Postfach
10.2209, D-69012 Heidelberg and 2Max-Delbrück-Centrum für Molekulare
Medizin, Robert-Rössle-Strasse 10, D-13122 Berlin-Buch, Germany
3To
whom correspondence should be addressed, at EMBL.
E-mail: birgit.eisenhaber@embl-heidelberg.de
Glycosylphosphatidylinositol (GPI) anchoring is a common
post-translational modification of extracellular eukaryotic
proteins. Attachment of the GPI moiety to the carboxyl
terminus (ω-site) of the polypeptide occurs after proteolytic
cleavage of a C-terminal propeptide. In this work, the
sequence pattern for GPI-modification was analyzed in
terms of physical amino acid properties based on a database
analysis of annotated proprotein sequences. In addition to
a refinement of previously described sequence signals, we
report conserved sequence properties in the regions ω –
11...ω – 1 and ω F 4...ω F 5. We present statistical
evidence for volume-compensating residue exchanges with
respect to the positions ω – 1...ω F 2. Differences between
protozoan and metazoan GPI-modification motifs consist
mainly in variations of preferences to amino acid types at
the positions near the ω-site and in the overall motif length.
The variations of polypeptide substrates are exploited to
suggest a model of the polypeptide binding site of the
putative transamidase, the enzyme catalyzing the GPImodification. The volume of the active site cleft accommodating the four residues ω – 1...ω F 2 appears to be ~540 Å3.
Keywords: amino acid index/GPI-anchor/post-translational
modification/transamidase
Introduction
Many proteins of eukaryotic organisms and their viruses are
post-translationally modified with a glycosylphosphatidylinositol (GPI) anchor to be subsequently immobilized on the
extracellular side of the plasma membrane. Attachment of the
GPI moiety to the carboxyl terminus (ω-site) of the polypeptide
occurs by a transamidation reaction within the endoplasmatic
reticulum following proteolytic cleavage of a C-terminal
propeptide from the proprotein (Udenfriend and Kodukula,
1995b). Little is known about the putative transamidase but
its substrate, the C-terminal sequence segment carrying the
GPI-modification signal, has been investigated in detail by
site-directed mutations in a few model proteins (Moran et al.,
1991; Coyne et al., 1993; Bucht and Hjalmarsson, 1996;
Furukawa et al., 1997; Yan et al., 1998). Unfortunately, this
signal is relatively weakly defined by the available experimental
data and appears to be composed of three sequence regions:
(i) the GPI-modification site (ω-site), (ii) a moderately polar
spacer region with a length of about 8–12 residues (region ω
1 1 to about ω 1 10) and (iii) an additional hydrophobic
C-terminal segment with a length of 10–20 residues (beginning
© Oxford University Press
with about ω 1 11). The efficiency of GPI-modification is
highly dependent on the amino acid type at some sequence
positions (for example, from ω to ω 1 2) but not in other
regions where length requirements and average hydrophobicity
(e.g. for the C-terminal segment) appear sufficient (Caras and
Weddel, 1989; Moran et al., 1991; Udenfriend and Kodukula,
1995b; Furukawa et al., 1997).
The successful progress of many large-scale genome projects
and the subsequent efforts at the functional characterization
of proteins known by sequence only stimulate analyses of
amino acid sequence patterns responsible for post-translational
modifications and prediction techniques for modification sites.
It should be noted that the annotation of a protein as being
GPI-anchored is very valuable functional information since it
both defines the subcellular localization and limits the range
of possible cellular determinations. Especially for the analysis
of expressed sequence tags (ESTs), which very often contain
information on C-terminal protein sequences, a GPImodification prediction tool would be extremely valuable. An
early attempt at a prediction algorithm used only amino acid
type preferences in the ω...ω 1 2 region (Udenfriend and
Kodukula, 1995a).
As a result of the experimental work of many groups,
sequence databases such as SWISS-Prot (Bairoch and
Apweiler, 1998) have accumulated more and more sequences
of GPI-anchored proteins, a resource that has not been exploited
yet for the detailed analysis of the GPI-modification motif. In
this paper, we present an analysis of the available sequence
data aimed at a more complete description of this sequence
signal in terms of physical properties of amino acid residues
that are probably conserved at the motif positions. It is our
basic working assumption that the database sequences explore
the GPI-modification motif in the sequence space sufficiently
exhaustively. Based on the variety of substrate sequences, we
propose a refined model of the polypeptide binding site of the
putative transamidase.
Concept and methodical details
Database searches
A database analysis program was written in C-language to
subselect database entries (via inspection of text segments
associated with given keys such as KW or FT for regular
expressions) from SWISS-Prot (Bairoch and Apweiler, 1998)
and to calculate statistics with respect to taxonomic subdivisions, propeptide length and confidence level of the ω-site
determination (annotated with ‘BY SIMILARITY’ or ‘POTENTIAL’, or without any comment, which can be considered as
experimental verification in most cases, as discussed below).
In the present release 35 of SWISS-Prot, 327 entries are
labeled with the keyword ‘GPI-ANCHOR’ but only 157 among
them have an annotation with respect to the ω-site in the
feature table (lipid modification). In the case of VSY3_TRYCO
(P20949), a question mark is given instead of the sequence
position of the cleavage site. For DAF_CAVPO (Q60401), the
1155
B.Eisenhaber, P.Bork and F.Eisenhaber
GPI-anchored form is buried among a large number of splicing
variants. Thus, 155 sequences remain for further analysis. The
list is available on the World Wide Web (http://www.emblheidelberg.de/~beisenha/GPI/gpi.html).
Confidence of the GPI-modification site annotation: status of
the experimental verification
The dataset of 155 proteins comprises 64 entries with annotations of the ω-site based on similarity to other GPI-modified
sequences, another 55 entries with sites described as potentially
GPI-modified and the remaining 36 cases do not have further
specification. The literature for these latter 36 entries has been
analyzed in detail.
The experimental verification of a protein being GPImodified at a given site requires an expensive laboratory effort
involving diverse techniques adapted to the specificity of the
protein being studied. The most direct, unambiguous approach
includes sequencing of the protein itself, its proteinase digestion
into smaller peptides under appropriate conditions, the separation of the peptide with a GPI group and the physico-chemical
characterization of this peptide and the GPI-modified amino
acid residue in it with radioactive labeling, chemical peptide
sequencing, composition analysis, NMR, mass spectrometry,
etc. (Killeen et al., 1988; Clayton and Mowatt, 1989; Misumi
et al., 1990; Stahl et al., 1990; Moran et al., 1991; Nuoffer
et al., 1991; Sugita et al., 1993). The literature references in
SWISS-Prot give evidence for a GPI-site determination with
such an approach for the 59-nucleotidases 5NTD_HUMAN
(P21589) and 5NTD_RAT (P21588), an acetylcholinesterase
ACES_TORCA (P04058), the MRC OX-45 surface antigen
BCM1_RAT (P10252), the complement decay-accelerating
factor DAF_HUMAN (P08174, P09679), the surface glycoproteins CD59_HUMAN (P13987), GAS1_YEAST (P22146,
P23151) and GP63_LEIMA (P08148, P15906), the dipeptidase
MDP1_HUMAN (P16444), the procyclin PARB_TRYBB
(P09791), the alkaline phosphatase PPB1_HUMAN (P05187)
and prion protein PRIO_MESAU (P04273), in all for 12
examples.
Given experimental evidence that the protein being studied
is indeed GPI-anchored (for example, with phospholipase C
or D solubilization experiments), the comparison of the mRNA
sequence with that of the mature protein also allows one to
localize the ω-site at the C-terminus (Sikorav et al., 1988;
Korinek et al., 1991; Suzuki et al., 1993). Such data are
available for many of the 12 examples listed above and also
for the entries 5NTD_BOVIN (Q05927), ACES_TORMA
(P07692) and BCM1_HUMAN (P09326). Data for the effects
of site-directed mutations at the ω-site (Yan and Ratnam, 1995)
have been reported for folate receptor variants FOL1_HUMAN
(P15328) and FOL2_HUMAN (P14207). Thus, the database
references supply full experimental verification for a total of
17 examples.
The ω-sites for sequences in entries BCM1_MOUSE
(P18181), CGM6_HUMAN (P31997) and PARA_TRYBB
(P18764) have been assigned by similarity to other, almost
identical, entries as explained in the corresponding references.
The literature (which is mostly dated before 1988) given for
the remaining 16 entries does not contain GPI-modification
site assignments at all. Although their SWISS-Prot sequence
descriptions have been recently updated, the foundation for
this change cannot be verified by the annotation. This does
not necessarily mean that the ω-site assignment is not reliable
since the experimental results may be contained in papers not
1156
referred to or may not have been published at all. For example,
experiments proving the ω-site location in the variant surface
glycoprotein VSG117 (entry VSM4_TRYBB, P02896, most
recent literature reference from 1982) have been described by
Moran and Caras (1994).
Analysis of the multiple alignment of the GPI-modification
signal in proproteins
The gapless multiple alignments of the proprotein sequences
with respect to the ω-site (from ω – 30 to the C-terminal end)
have been used to determine the relative occurrences p(a,i) of
amino acid types a at given motif positions i. The propeptide
sequence in the ω-site region has to fit into the catalytic site
of the putative transamidase over about a dozen residues.
Hence there is little possibility of accommodating gaps that
are otherwise normal in loops between secondary structural
elements.
Two different mechanisms have been used for balancing the
representation of different classes of sequences in the alignment. First, the largest subset of sequences with maximal
pairwise sequence identity below 30% (only for the sequence
segments ω – 30...ω – 1 and ω 1 3...ω 1 8 since the regions
ω...ω 1 2 and .ω 1 8 are known to be compositionally
biased) has been determined following published algorithms
(Heringa et al., 1992; Hobohm et al., 1992). The resulting set
consists of 44 sequences for Metazoa but only 18 proteins for
Protozoa.
The second technique (PSIC: position-specific independent
counts) is more elegant and uses the information from all
sequences in the multiple alignment (Sunyaev et al., 1998,
submitted). In brief, we compute an effective number n(a,i)eff
of observations of amino acid type a at alignment position i
(i.e. the number of independent sequences that carry the same
amount of information as available correlated ones) and
determine p(a,i) as
n(a,i)eff
p(a, i) 5
(1)
Σ n(b,i)eff
b
The summation is carried out over all amino acid types b. The
value n(a,i)eff is thought to depend on the overall similarity of
sequences having the common amino acid type a at the
alignment position considered. The idea is that the observation
of amino acid type a in a subset of sequences provides the
less new information compared with a single observation of a
[implying a smaller n(a,i)eff], the more similar the sequences
in the subset are in other alignment positions. In the PSIC
approach, the frequency of identical alignment positions F(a,i)
in the subset of sequences having the same amino acid type a
at alignment position i is used as similarity measure and is set
equal to the probability of identical alignment positions for
n(a,j)eff random sequences. Thus, the solution of the equation
F(a,j) 5 Σ qbn(a,j)eff
b
(2)
for n(a,j)eff is an estimate of the number of independent
observations of amino acid type a at position j in the alignment.
The value qb is the default frequency of amino acid type b in
a sequence database. The effective relative amino acid type
occurrences (1) have been computed for the alignment range
from ω – 15 to the C-terminal end.
Correlation analysis between observed amino acid
occurrences in the alignment and amino acid properties
For each alignment position studied, the correlation coefficients
between the vector of 20 amino acid-type frequencies and the
GPI-modification sequence motif
Fig. 1. Length distribution of C-terminal propeptides. The data for the total dataset of 155 SWISS-Prot entries and for the taxons Fungi, Protozoa and
Metazoa separately are listed. The bin width for the sequence length is four residues.
vectors of amino acid indices quantifying physical properties
of amino acid types were calculated. In addition to the database
of 402 amino acid indices (Tomii and Kanehisa, 1996), we
used also our own amino acid property library with additional
236 entries (http://www.embl-heidelberg.de/~beisenha/GPI/
gpi.html). As outlined in the Appendix, all correlation coefficients above 0.70 can be considered statistically significant
(confidence level α 5 0.001).
Results and discussion
Taxonomic and length distribution
The taxonomic distribution of the 155 fully described proproteins with GPI-modification signal is very uneven. We found
104 examples for Metazoa (99 proteins from Vertebrata are
among them), 40 proteins from mostly parasitic Protozoa, 10
entries from Fungi (mostly yeast) and one for a human Herpes
virus. Although GPI-anchoring has been described for an alga
(Morita et al., 1996) and an archaebacterium (Kobayashi et al.,
1997), there is no entry with an annotated ω-site in the SWISSProt database.
The length distribution of C-terminal propeptides with
respect to taxonomic subgroups is shown in Figure 1. It should
be noted that some propeptide lengths might be too short
owing to a premature stop of sequencing or frameshift errors.
The total length range is between 9 and 56 residues but most
proteins cluster between 18 and 29 residues. If we restrict the
dataset of 155 proteins to entries without annotations of the
ω-site by similarity (64 entries) or as potential (55 entries),
the remaining 36 propeptides have a length between 17 and
31 residues. Only 16 of all 155 examples are outside this
range and it appears very unlikely that the ω-site is correctly
annotated for these proteins or that their sequence is complete
(Table I). In agreement with individual experimental findings
(Moran and Caras, 1994), the database statistics support the
observation that mostly metazoan propeptides are longer than
those of Protozoa (with our results, about 4–8 residues).
Analysis of physical requirements of sequence positions
For a more detailed analysis, we concentrated on the two
largest taxonomic subsets with propeptide length between 17
and 31 residues: 94 metazoan and 36 protozoan proteins. To
identify physical requirements at sequence positions near the
ω-site, the site of propeptide cleavage and GPI-attachment,
gapless multiple alignments for each taxonomic subdivision
with respect to the ω-site were produced. The relative frequency
of amino acid type occurrence at each alignment position was
calculated after balancing for redundancy due to similar
sequences with the two methods outlined in the Methods
section. The correlation coefficients r of this 20-dimensional
frequency vector with any of 638 amino acid property indices
were computed. All significant correlations (r . 0.70, see
Appendix) were selected. The highest correlations are presented
in Table II. The total computation results are available via
http://www.embl-heidelberg.de/~beisenha/GPI/gpi.html.
The N-terminal side of the ω-site. The N-terminal side of the
ω-site has not attracted much attention from experimentalists
since no obvious amino acid conservation could be detected
(Moran et al., 1991). Indeed, we found no significant property
conservation in the sequences for all sites N-terminal to ω –
11. To our surprise, the region ω – 11...ω – 1 may be
characterized as unstructured, flexible and polar as the many
high correlations to polarity, hydrophobicity (with minus sign)
and coil preference scales as well as to average amino acid
composition in sequence databases evidence. At the position
ω – 1, size restrictions start to play a role as the anti-correlation
to amino acid size shows. There are no obvious differences
between metazoan and protozoan proproteins.
Interestingly, Bucht and Hjalmarsson (1996) produced
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B.Eisenhaber, P.Bork and F.Eisenhaber
Table I. List of SWISS-Prot entries with extreme propeptide length
SWISS-Prot ID
Accession No.
Taxon
Propeptide
length
Reasons for possibly
doubtful annotations
BST1_MOUSE
CNTR_HUMAN
CNTR_RAT
HYA1_CAVPO
VCA1_MOUSE
GP46_LEIAM
GP63_LEIGU
GP42_RAT
LY6A_MOUSE
LY6C_MOUSE
LY6F_MOUSE
LY6G_MOUSE
MSA1_SARMU
PAG1_TRYBB
YJ90_YEAST
YJ9P_YEAST
Q64277
P26992
Q08406
P23613
P29533
P21978
Q00689
P23505
P05533
P09568
P35460
P35461
Q01416
Q01889
P47178
P47179
Metazoa
Metazoa
Metazoa
Metazoa
Metazoa
Protozoa
Protozoa
Metazoa
Metazoa
Metazoa
Metazoa
Metazoa
Protozoa
Protozoa
Fungi
Fungi
32
36
36
37
34
56
45
16
15
15
15
15
16
9
16
15
B
A
A
C
A, B
A, B, C
B, C
A, D
D
D
A, D
D
D
A, D
D
A, D
All entries with propeptide length outside the range of 17–31 residues are presented. These outliers are possibly incorrectly annotated since their propeptide
assignment is in contradiction with the following experimental results for other examplary proteins: (A) the occurrence of an extremely large amino acid or
proline in the region ω...ω 1 2 (Moran et al., 1991; Udenfriend and Kodukula, 1995b); (B) large charged residues in the spacer region (Beghdadi-Rais et al.,
1993); (C) several extremely polar residues in the hydrophobic C-terminal tail behind ω 1 9 (Udenfriend and Kodukula, 1995b; Yan et al., 1998); and (D)
smaller than minimal length of propeptide for efficient GPI-anchoring (Moran et al., 1991; Coyne et al., 1993; Yan and Ratnam, 1995).
Table II. Correlation between the (effective) amino acid composition at alignment positions (relative to the ω-site) and amino acid properties
P
Metazoa
c
Protozoa
Commentary
Property
c
–11
0.83*
0.88
N–Terminal helix
Glu
ROBB760102
ONE_AA__E_
–10
0.70
Polar
JANJ780101
–9
0.82*
0.83
Polar
Glu
NAKH920103
ONE_AA__E_
–8
–0.76*
0.92
Hydrophobic
Ser
ROSG850101
ONE_AA__S_
AA comp.
DAYM780101
–0.76
–7
–2
–1
0.81*, 0.85
0.82*, 0.82
0.74*, 0.79
0.74
–0.71*
0.81*, 0.70
0.82*
–0.89
–0.77
Commentary
Property
Coil
Flexibility
QIAN880134
KARP850102
Hydrophobic
WERD780101
Cys, Pro
Coil
TWO_AA_CP
QIAN880131
Hydrophobic
CIDH920101
Coil
ROBB760112
Size
CHAM810101
Size
CHAM810101
0
0.85*, 0.80
0.90*, 0.96
Composition ω 1 0
Ser
UDF_OMEG0
ONE_AA__S_
0.90*, 0.92
0.83*, 0.71
Composition ω 1 0
Ser
UDF_OMEG0
ONE_AA__S_
1
0.98*, 0.94*
Tiny
ZVEL_TINY_
0.76
0.94, 0.92
Tiny
Composition ω 1 0
ZVEL_TINY_
UDF_OMEG0
2
0.96*, 0.97
0.76*
Composition ω 1 2
Tiny
UDF_OMEG2
ZVEL_TINY_
0.95*, 0.84
0.76
Ser
Tiny
ONE_AA__S_
ZVEL_TINY_
4
0.78
0.85*, 0.93
Hydrophobic
Leu, Ser
NAKH900105
TWO_AA_LS
0.81
0.82,
Hydrophobic
Hydrophobic
NAKH900105
NAKH920105
5
0.85*
0.72
Hydrophobic
Hydrophobic
NAKH900105
NAKH900112
0.82*,0.81
0.72*, 0.77
Aliphatic
Hydrophobic
ZVEL_ALI1_
NAKH920105
7
0.75*, 0.71
Tiny
ZVEL_TINY_
8
0.90
Turn
TANS770104
The highest correlations c between the amino acid composition (for the largest subset of sequences with low pairwise sequence identity; in the case of the
PSIC method, the effective amino acid composition) at alignment positions and amino acid property indices are listed (correlation coefficients for the largest
subset of sequences with low pairwise sequence identity are marked with asterisks). P is the position relative to the ω-site. The commentary denotes the class
of the property index. The full data of the property entry with the ID listed in the table can be found at http://www.embl-heidelberg.de/~beisenha/GPI/
gpi.html. The compositions for positions ω 1 9 to the end correlate uniformly with hydrophobic scales and the results are not listed here. Entries without
underscores are from the Japanese property library (Tomii and Kanehisa, 1996), the others are from our own library. The composition of ω 1 0 and ω 1 2
corresponds to the data in Table II of Udenfriend and Kodukola (Udenfriend and Kodukula, 1995a).
numerous mutations to Thr and Ser in the ω – 11...ω-1 region
of Torpedo californica acetylcholinesterase since they expected
the ω-site at a position which later was shown to be ω – 6
1158
and observed no change in GPI-anchoring efficiency. Both Thr
and Ser fit well into regions with low internal affinity to local
structure. Also, single deletions in the ω – 11...ω – 1 region
GPI-modification sequence motif
of hGH-DAF (Moran et al., 1991) had no effect on GPIanchoring. Inspection of the sequence shows that a histidine,
a polar residue often observed outside secondary structures, is
at position ω – 11 after deletion.
We interpret the sequence requirement in the ω – 11...ω –
1 region in such a way that, apparently, the catalytic site of
the putative transamidase is buried in a cavity or in a narrow
invagination. Probably, there is a need for a linker region
connecting the folded substrate protein with the residue at the
ω-site which is hidden by catalytic residues deep inside the
active enzyme. It would be of interest to test this hypothesis
experimentally by placing a peptide sequence with strong
internal α-helical preference into the respective sequence
region.
The cleavage and GPI-attachment region. With respect to the
whole region ω – 1...ω 1 2, size restrictions for the amino
acid side-chains are evident (Table II). This is the major reason
for the amino acid conservation at the ω-site: almost exclusively
Ser (44% of all sequences in the largest subset with low
pairwise sequence identity), Asp, Asn, Ala and Gly for Protozoa
and also with decreasing occurrence Ser (48%), Gly, Asn, Asp
and Cys for Metazoa, an amino acid composition that is only
slightly modified with respect to taxonomic groups compared
with previous reviews (Udenfriend and Kodukula, 1995b). At
other positions, the size requirements appear not to be as strict
as for the ω-site (Udenfriend and Kodukula, 1995b) but a
larger amino acid at one of the positions seems to require a
compensating smaller amino acid at another position (Coyne
et al., 1993; Moran and Caras, 1994). Thus, the active site of
the putative transamidase and the channel communicating with
the environment have a limited volume to accommodate the
substrate polypeptide.
For the largest subset of sequences with low pairwise
sequence identity (for 44 metazoan and 18 protozoan sequences
separately), we calculated the average volume and its variance
for residues at each position from ω – 1 to ω 1 2 separately
and for all combinations of several positions out of the region
ω – 1...ω 1 2. We used the residue volume scale of Harpaz
et al. (1994). The relation F between the sum of squared
volume variances σi2 for independent sequence positions i1,
i2, ...and the squared volume variance σ(i1, i2, ...) for correlated
positions
F5
Σσ 2i
i
σ(i1, i2, ...)2
(3)
is a measure of volume compensation among positions. The
comparison of variances in Equation (3) for the uncorrelated
and the correlated positions is carried out with Fisher’s criterion
(Kendall and Stuart, 1977). For absence of correlations, the
total variance is just the sum of variances for the individual
sequence positions. The interdependence is statistically significant if F . Fcritical (the decision criterion Fcritical is 1.67
and 2.23 for 5% significance for Metazoa and Protozoa,
respectively). We find the largest values of F for the pair ω –
1 and ω 1 2 in the case of Metazoa (F 5 1.80 . Fcritical) and
for the pair ω – 1 and ω 1 1 in the case of Protozoa
(F 5 1.77). The relation F is also high for the total region
ω – 1...ω 1 2 (1.46 for Protozoa and 1.24 for Metazoa). Thus,
at least for Metazoa, the number of data is sufficient to prove
the existence of mutual volume compensation for residues at
positions ω – 1 and ω 1 2. The results indicate that this is
probably also true for the whole region ω – 1...ω 1 2 as well
as for Protozoa, although the number of sequences is not
sufficient to reach the 5% confidence threshold.
Our data allow us to estimate also the volume of the active
site cavity. The volume of the substrate region ω – 1...ω 1 2
is 423 (656) Å3 for Metazoa and 422 (650) Å3 for Protozoa;
i.e. the two values are very similar. Thus, the volume of the
active site cleft of the putative transamidase appears to be
about 540 (5 420 1 2·60) Å3 (2σ rule corresponding to the
5% confidence level). We do not take the volume of the largest
available substrate as an estimate since its ω-site assignment
may be incorrect.
Given the volume restriction as the major sequence requirement for the region ω – 1...ω 1 2, we can explain the finding
of Kodukula et al. (1993), who reported insensitivity of
position ω 1 1 with respect to amino acid type (except for
Pro) in the case of the human placental alkaline phosphatase.
The positions ω – 1, ω and ω 1 2 are occupied by Thr,
Asp and Ala, respectively, having a total volume of about
327 Å3. Most residues are smaller than 200 Å3 and will fit
well into the remaining space of the catalytic cavity. Even Trp
(volume 232 Å3) can enter, although with difficulty as the
GPI-modification activity lowered to a tenth of that of the
wild type indicates.
The spacer region. We find only a few sequence positions in
the region ω 1 3...ω 1 8 that show signs of amino acid
property conservation. In both in metazoan and in protozoan
examples, the positions ω 1 4 and ω 1 5 have a significant
tendency to be occupied with hydrophobic amino acids,
especially leucine. Only in metazoan proteins is serine also
frequent at ω 1 4. For the same taxonomic group, the ω 1 7
site is mostly occupied by small residues and, at the ω 1 8
site, residues with high turn propensity are preferred.
Mutational studies of exemplary proteins also demonstrate
that amino acid type preferences in the region ω 1 3...ω 1 8
are weak. The major restriction is the length of a moderately
polar stretch between the ω-site and the C-terminal hydrophobic
tail (Coyne et al., 1993; Furukawa et al., 1997). A large
number of charged residues is usually not tolerated (BeghdadiRais et al., 1993). The substitution G237D in the β-type folate
receptor proprotein (reduced by the C-terminal 5 residues)
resulted in a sharp decrease of GPI-anchoring activity (Yan
et al., 1998) in agreement with the tendency for tiny amino
acids at ω 1 7 (our observation). A similar substitution G237M
in the otherwise intact β-type folate receptor proprotein had
no effect (Yan and Ratnam, 1995). Substitutions of the ω 1
5 site to Pro or Ser in Thy-1 mutants had no measurable effect
on GPI-anchoring (Beghdadi-Rais et al., 1993). Thus, we
conclude that the sequence preferences in our dataset (hydrophobic residues at ω 1 4 and ω 1 5; for Metazoa, tiny
residues at ω 1 7 and turn residues at ω 1 8) are not
obligatory but express the ability of these sequences to interact
with the binding site of the putative transamidase more
efficiently.
The C-terminal hydrophobic tail. Beginning with ω 1 9, the
amino acid composition at the alignment position correlates
well with hydrophobicity scales (at least one scale with a
correlation coefficient above 0.90 from ω 1 10 on, Leu is the
dominant amino acid type except for ω 1 15 in the case of
Metazoa) in both taxons Protozoa and Metazoa. Therefore, the
difference in length of the moderately polar spacer region
between the two taxons as observed by Moran and Caras
(1994) appears at best species-specific, but their finding is
1159
B.Eisenhaber, P.Bork and F.Eisenhaber
Table III. Sequence properties of the C-terminal propeptide near the ω-site
Position relative Protozoa
to the ω-site
Metazoa
–11...–1
0
Unstructured region
Ser (48%), Gly, Asn, Asp,
Cys
Tiny (Gly, Ala, Ser)
Ala 1 Gly (70%)
Hydrophobic
Onset of hydrophobic region
1
2
4...5
9
15
Unstructured region
Ser (44%), Asp, Asn, Ala,
Gly
Similar to position 0
Ser 1 Ala (94%)
Hydrophobic
Onset of hydrophobic
region
up to about ω 1 25,
mostly Leu
–
up to about ω 1 31, mostly
Leu
Ser 1 Thr 1 Ala (60%)
This table summarizes the results of the correlation analysis with amino
acid property indices. The percentage data of amino acid occurrence are
related to the alignment of sequences in the largest subset with pairwise
sequence identity below 30%. For detailed explanations, see Results and
discussion.
unfortunately not supported by our sequence analysis of a
large number of GPI-anchored proteins. The difference in total
motif length between Protozoa and Metazoa discussed above
may be completely attributed to length differences of the
hydrophobic C-terminal tail.
For many metazoan sequences in the dataset, position ω 1
15 is occupied by small amino acids such as Ser, Thr and Ala
(60% of all sequences in the largest subset with pairwise
sequence identity below 30%). At the same time, the substitution L245S (5 ω 1 15) in the β-type folate receptor proprotein
(reduced by the five C-terminal residues) inhibited any GPIanchoring activity (Yan et al., 1998). Thus, the sequence
requirement of small amino acids for ω 1 15 might be
important for only a few taxonomic subgroups of Metazoa.
The necessity for a large hydrophobic C-terminal tail is a
well established experimental fact (Wang et al., 1997). Deletion experiments of C-terminal amino acids show for the
59-nucleotidase (Furukawa et al., 1994) and for synthetic GPImodification signals (Coyne et al., 1993) in metazoan cell
system that the hydrophobic region should extend at least to
ω 1 21 for a measurable GPI-anchoring activity. Mutations to
polar residues in the C-terminal hydrophobic region generally
reduce the ability to be GPI-anchored, especially for the
positions between ω 1 10 and ω 1 17 (Yan et al., 1998). It
is assumed that the C-terminal hydrophobic segment forms
a helical structure inside the membrane (Udenfriend and
Kodukula, 1995b).
Summary of the GPI-modification motif. Our sequence analysis
results are summarized in Table III and Figure 2. The Cterminal GPI-modification signal appears to consist of four
sequence regions: (i) an unstructured linker region of about
11 residues (ω – 11...ω – 1); (ii) a region of small residues
(ω – 1...ω 1 2) including the ω-site for propeptide cleavage
and GPI-attachment; (iii) a spacer region (ω 1 3...ω 1 8) of
moderately polar residues with a possible hydrophobic island
(ω 1 4 and ω 1 5); and (iv) a hydrophobic tail beginning
with ω 1 9 up to the C-terminal end. This general scheme
might be varied in the case of specific species (for example,
small amino acids at ω 1 15 for various Metazoa) or less
efficient GPI-modification signals. The active site of the
putative transamidase appears to be a small volume cavity or
deep invagination. The enzymatic activity probably requires
1160
Fig. 2. Structural scheme for the putative transamidase. The putative
transamidase is thought to be a protein with a large membrane domain and
another ER (endoplasmic reticulum) domain. The scheme represents a
section through the enzyme. Inside surfaces of cavities and invaginations are
colored dark, the faces of the section are yellow. Important residues of the
substrate protein are shown with red circles and are numbered with respect
to the ω-site. The catalytic cavity contains the residues ω – 1...ω 1 2. This
location has to communicate with the GPI-moiety binding site. The channel
between the substrate protein in the ER lumen and the catalytic site is
occupied by the flexible polypeptide segment ω – 11...ω – 1. The spacer ω
1 3...ω 1 9 (with a possible special binding site for ω 1 4...ω 1 5) links
the residues in the catalytic cleft with the hydrophobic tail (possibly
forming an α-helix) embedded in the ER membrane.
propolypeptide binding over a considerable sequence length to
achieve correct register of strand cleavage and GPI attachment.
We emphasize that the conclusions in this work depend on
the assumption that the database sequences explore the available part of the sequence space for the GPI-modification motif
sufficiently exhaustively. Possible annotation errors for a few
sequences will not have a significant influence on the results
owing to the averaging procedure in the balanced multiple
alignment with many input sequences. Generally, our results
are in good agreement with experimental data published for
exemplary proteins. Therefore, the model of the hypothetical
binding site of the putative transamidase might be productively
used for the design of future mutation experiments.
Since GPI-modification is a strong marker for cellular
localization and function, an automatic prediction algorithm
for possible GPI-modification sites based on the sequence
features described in this work (as it is currently being
developed in our laboratories) would be a valuable tool for
the functional characterization of genomic sequences and ESTs.
Acknowledgement
The authors are grateful to J.G.Reich for valuable discussion of the results
and constant support during this work.
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Appendix
A decision criterion for statistical significance of a correlation
coefficient r is given by
tα ,
r √n – f
√1 – r 2
(4)
for n , 100 (Kendall and Stuart, 1977). Here, n is the number
of data points (n 5 20 amino acid types) and f represents the
number of conditions (total three: two for the linear regression
and one for the sum of all amino acid-type frequencies being
unity). The threshold tα is the argument of the Student’s
distribution function for a one-sided criterion with the
confidence level α (tα 5 4 for α 5 0.001). The inequality (4)
results in r . 0.696 after elementary transformations.
1161