Detecting Protein Function and
Protein-Protein Interactions
from Genome Sequences
Edward M. Marcotte, Matteo Pellegrini, Ho-Leung Ng,
Danny W. Rice, Todd O. Yeates, David Eisenberg*
A computational method is proposed for inferring protein interactions from
genome sequences on the basis of the observation that some pairs of interacting
proteins have homologs in another organism fused into a single protein chain.
Searching sequences from many genomes revealed 6809 such putative protein-
protein interactions in Escherichia coli and 45,502 in yeast. Many members of
these pairs were confirmed as functionally related; computational filtering
further enriches for interactions. Some proteins have links to several other
proteins; these coupled links appear to represent functional interactions such
as complexes or pathways. Experimentally confirmed interacting pairs are
documented in a Database of Interacting Proteins.
The lives of biological cells are controlled by
interacting proteins in metabolic and signal-
ing pathways and in complexes such as the
molecular machines that synthesize and use
adenosine triphosphate (ATP), replicate and
translate genes, or build up the cytoskeletal
infrastructure (1). Our knowledge of protein-
protein interactions has been accumulated
from biochemical and genetic experiments,
including the widely used yeast two-hybrid
test (2). Here we ask if protein-protein inter-
actions can be recognized from genome se-
quences by purely computational means.
Some interacting proteins such as the Gyr
A and Gyr B subunits of Escherichia coli
DNA gyrase are fused into a single chain in
another organism, in this case the topoisom-
erase II of yeast (3). Thus, the sequence
similarities of Gyr A (804 amino acid resi-
dues) and Gyr B (875 residues) to different
segments of the topoisomerase II (1429 resi-
dues) might be used to predict that Gyr A and
Gyr B interact in E. coli.
To find other such putative protein inter-
actions in E. coli, we searched the 4290
protein sequences of the E. coli genome (4 )
for these patterns of sequence homology (5).
We found 6809 pairs of nonhomologous se-
quences, both members of the pair having
significant similarity (6) to a single protein in
some other genome that we term a Rosetta
Stone sequence because it deciphers the in-
teraction between the protein pairs. The 4290
proteins could form at most (4290)
2
/2 ⫽ 9 ⫻
10
6
pair interactions, but we would expect
many fewer interactions in a functioning cell;
roughly 2 to 10 interactions for each protein
does not seem unreasonably many.
Each of these 6809 pairs is a candidate for
a pair of interacting proteins in E. coli. Five
such candidates are shown in Fig. 1. The first
three pairs of E. coli proteins were among
those easily determined from the biochemical
literature in fact to interact. The final two
pairs of proteins are not known to interact.
They are representatives of many such pairs
whose putative interactions at this time must
be taken as testable hypotheses.
We devised three independent tests of in-
teractions predicted by the method we term
domain fusion analysis, each showing that a
reasonable fraction may in fact interact. The
first method uses the annotation of proteins
given in the SWISS-PROT database (7 ). For
cases where the interacting proteins have
both been annotated, we compare their anno-
tations, looking for a similar function for both
members of the pair. Similar function would
imply at least a functional interaction. Of the
3950 E. coli pairs of known function, 2682
(68%) share at least one keyword in their
SWISS-PROT annotations (ignoring the key-
word “hypothetical protein”), suggesting re-
lated functional roles. When pairs of annotat-
ed E. coli proteins are selected at random,
only 15% share a keyword. In short, of the E.
coli pairs that the domain fusion analysis
turns up as candidates for protein-protein in-
teractions, more than half have both members
with a similar function; the method therefore
seems to be a robust predictor of protein
function. Where the function of one member
of a protein pair is known, the function of the
other member can be predicted. Performing a
similar analysis in yeast turns up 45,502 pro-
tein pairs. Of the 9857 pairs of known func-
tion, 32% share at least one keyword in their
annotations compared with 14% when pro-
teins are selected at random.
The second test of the interactions predict-
ed by the domain fusion analysis uses as
confirmation the Database of Interacting Pro-
teins (8). This database is a compilation of
protein pairs that have been found to interact
in some published experiment. As of Decem-
ber 1998, the database contained 939 entries,
724 of which have both members of the pair
listed in the ProDom database. Of these 724
pairs, we found 46 or 6.4% linked by Rosetta
Stone sequences. We expect this percentage
to rise as more genomes are sequenced.
The third test of domain fusion predic-
tions is by another computational method for
predicting interactions (9), the method of
phylogenetic profiles, which detects func-
tional interactions by analyzing correlated
evolution of proteins. This method was ap-
plied to the 6809 interactions predicted by the
domain fusion analysis for E. coli proteins.
Some 321 of these predictions (⬃5%) were
suggested by the phylogenetic profile method
to interact, more than eight times as many
interactions in common as for randomly cho-
UCLA–Department of Energy Laboratory of Structural
Biology and Molecular Medicine, Departments of
Chemistry and Biochemistry and Biological Chemis-
try, Box 951570, University of California at Los An-
geles, Los Angeles, CA 90095–1570, USA.
*To whom correspondence should be addressed: E-
mail: david@mbi.ucla.edu
Fig. 1. Five examples
of pairs of E. coli pro-
teins predicted to inter-
act by the domain fu-
sion analysis. Each pro-
tein is shown schemat-
ically with boxes rep-
resenting domains [as
defined in the ProDom
domain database (17)].
For each example, a
triplet of proteins is pic-
tured: The second and
third proteins are pre-
dicted to interact be-
cause their homologs
are fused in the first
protein (called the Rosetta Stone protein in the text). The first three predictions are known to interact
from experiments (18). The final two examples show pairs of proteins from the same pathway (two
nonsequential enzymes from the histidine biosynthesis pathway and the first two steps of the proline
biosynthesis pathway) that are not known to interact directly.
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www.sciencemag.org SCIENCE VOL 285 30 JULY 1999 751
sen sets of interactions. Given that the do-
main fusion method and the phylogenetic
profile method rest on entirely different as-
sumptions, this level of overlap of predictions
tends to support the predictive power of both
methods.
The discovery of many possible pair in-
teractions between proteins of E. coli encour-
aged us to look for coupled interactions,
where A is predicted to interact with B and B
with C, and so forth. That is, we asked if the
domain fusion method can turn up complexes
of proteins or protein pathways. As Fig. 2
shows, suggestive information on both path-
ways and complexes did emerge from linked
pairs of E. coli proteins. The pathways for
shikimate biosynthesis and purine biosynthe-
sis are shown in Fig. 2 (pathways A and C,
respectively). The enzymes in these pathways
for which links were found to other members
of the same pathway are shown in bold type.
The precise links suggested by Rosetta Stone
sequences are shown in Fig. 2 (B and D).
Some of these discovered links are between
sequential enzymes in the pathway, and oth-
ers are between more distant members, per-
haps suggesting a multienzyme complex. An
alternative explanation of the same findings
is that enzymes in the pathway are expressed
in a fused form in some organisms as an aid
in regulation of expression; in this case,
linked members of a pair would not neces-
sarily bind to each other (see below).
To evaluate the reliability of domain fu-
sion predictions of protein interactions, it is
helpful to consider why the method should
work in the first place. This emerges from
considerations of protein affinity. It follows
from the laws of thermodynamics that the
fusion of protein domains A and B into a
single protein chain can profoundly enhance
the affinity of A for B. The reason for this is
that fusion greatly reduces the entropy of
dissociation of A with B, thereby reducing
the association free energy of A to B (10).
This reduction in entropy is often expressed
as an increase in the effective concentration
of A with respect to B. The concentrations of
proteins in E. coli cells tend to be on the order
of micromolar (11), whereas the effective
concentrations of fused proteins can be ⬃mil-
limolar or even greater (12). Put another way,
the standard free energy of dissociation for
protein subunits from a complex is typically 8
to 20 kcal/mol at 27°C (corresponding to
dissociation constants of 10
⫺6
to 10
⫺14
M)
(13) and can be reduced by ⬃10 kcal/mol
when the subunits are fused into a single
protein chain. Because affinity between pro-
teins A and B is greatly enhanced when A is
fused to B, some interacting pairs of proteins
may have evolved from primordial proteins
that included the interacting domains A and B
on the same polypeptide, as shown in Fig. 3.
We term this pathway the Rosetta Stone hy-
pothesis for evolution of protein interactions.
Also in support of the Rosetta Stone pathway
is the observation that protein-protein inter-
faces have strong similarity to interdomain
interfaces within single protein molecules
(14 ).
It is important to realize that the domain
fusion analysis makes two distinct predic-
tions. First, it predicts protein pairs that have
related biological functions—that is, proteins
that participate in a common structural com-
plex, metabolic pathway, or biological pro-
cess. Prediction of function is robust: For E.
coli, general functional similarity was ob-
served in over half the testable predictions.
Second, the method predicts potential pro-
tein-protein interactions. For this more spe-
cific prediction, the considerations of protein
affinity and evolution aid understanding in
which cases the domain fusion method will
miss pairs of interacting proteins (false neg-
atives) and in which cases it will turn up false
candidates for interacting pairs (false posi-
tives). One reason for missing interactions is
that many protein-protein interactions may
have evolved through other mechanisms,
such as gradual accumulation of mutations to
evolve a binding site. In these cases, there
never was a fusion of the interacting proteins,
and so no Rosetta Stone sequence can be
found. Second, even in other cases where the
interacting partners were once fused, the
fused protein may have disappeared during
the course of evolution, and so there is no
Rosetta Stone relic remaining to decipher
binding partnerships. As more genomes are
sequenced, however, there is a higher chance
of finding Rosetta Stone sequences.
Fig. 2. Reconstruction of two
metabolic pathways in E. coli,
with only interactions predicted
by the domain fusion method.
Pathways A and C are the known
pathways for biosynthesis of
shikimate and purine, respective-
ly; they are ordered by the tra-
ditional method of successive
action of the enzymes on the
known metabolites. Pathways B
and D are constructed from the
proteins in pathways A and C
with connections predicted by
the domain fusion method. In
both cases, more than half of the
proteins in the biochemical path-
way are predicted by the domain
fusion method to interact with
other proteins of the pathway. It
is possible that these groupings
represent multiprotein complexes. Enzymes stacked together (for example, AroK and AroL) are
homologs.
Fig. 3. A model for the evolution
of protein-protein interactions.
The Rosetta Stone model starts
with the fusion of the genes that
code for the noninteracting do-
mains A and B, leading to expres-
sion of the fused two-domain
protein AB (19). In the fused pro-
tein, the domains have a rela-
tively high effective concentra-
tion, and relatively few muta-
tions create a primitive binding site between the domains that is optimized by successive
mutations. In the second line, the interacting domains are separated by recombination with
another gene to create an interacting pair of proteins A and B. An interacting pair of proteins A and
B can be created by fission of a protein, so that the preliminary fusion step is not essential to the
Rosetta Stone hypothesis. The lower righthand step shows another possible mutation, a loop
deletion that leads to a domain-swapped homodimer. This evolutionary path to homooligomers
has been discussed earlier (20) and is the analog for homooligomers of the evolutionary path
suggested here for heterooligomers.
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False predictions of physical interac-
tions may be made by the domain fusion
analysis in cases where domains are fused
but not interacting. This may be so when
proteins have been fused to regulate coex-
pression or protein signaling. For these cas-
es, the “interaction” of the proteins can be
a functional interaction rather than a phys-
ical interaction. Other false predictions can
arise because the domain fusion analysis
cannot distinguish between homologs that
bind and those that do not. As an example,
consider the signaling domains SH2 and
SH3. The kinase domain and the SH2 and
SH3 domains of the src homology kinase
interact with one another in the src mole-
cule (15), but homologs of these domains
are found in many other proteins, and it is
certainly untrue that all SH2 domains inter-
act with all SH3 domains. A similar prob-
lem crops up with epidermal growth factor
and immunoglobulin domains. The false
positive rate in E. coli due to the inability to
distinguish homologs is about 82% (16 ).
That is, although the domain fusion analy-
sis gives a robust prediction of protein
function of the form “A is functionally
linked to B,” only a subset of these putative
interactions represent physical interactions
between proteins.
To quantify and reduce errors in predict-
ing protein-protein interactions, we calculat-
ed the occurrence of “promiscuous” domains
such as SH3 that are present in many other-
wise different proteins. These domains can be
identified and removed during domain fusion
analysis. In the ProDom database of domains,
we counted the number of other domains that
each domain could be linked to using the
domain fusion method. As shown in Fig. 4,
about 95% of the domains are linked to only
a few other domains. For the 7842 domains in
the ProDom domain database for which we
can find Rosetta Stone links, only about 5%
are “promiscuous,” making more than 25
links to other domains. That is, by filtering of
only 5% of all domains from our domain
fusion predictions, we can remove the major-
ity of falsely predicted interactions. When
this type of filtering is applied to the 3531
Rosetta Stone links of E. coli found with the
ProDom analysis, the number is reduced to
749. Although dropping the number of pre-
dictions, this filtration step increases the like-
lihood that predicted links represent true
physical interactions by 47% over the unfil-
tered predictions. Also, after filtering out pro-
miscuous domains, the average false positive
rate in E. coli due to the inability to distin-
guish homologs drops to 65%. The practical
result of domain fusion analysis is that many
protein interactions can be predicted from
genome sequences, permitting experimental-
ists to focus on promising interactions.
In summary, genomic information opens
new paths to biochemical discoveries. The
finding in a genome of many pairs of protein
sequences A⬘ and B⬘ that are both homologs
to a single sequence A
∧
B in another genome
suggests the possibility that A⬘ and B⬘ are
binding partners and provides robust func-
tional information about A⬘ and B⬘. System-
atic searches of this sort may lead to identi-
fications of new pathways and protein com-
plexes in organisms.
References and Notes
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mains in every one of the 64,568 SWISS-PROT pro-
teins was prepared, as well as a list of all proteins that
contain each of the 53,597 ProDom domains. Then
every protein in ProDom was considered for its ability
to be a linking (or Rosetta Stone) member in a triplet.
All pairs of domains that are both members of a given
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when the sequences align with a statistically signifi-
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in other genomes, n ⫻ m total comparisons are
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potential true positives calculated for all domain
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Rosetta Stone protein, there are n proteins with the
first domain but not the second and m proteins with
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21. Supported by the following grants: Department of
Energy (DOE) DE-FC03-87ER-60615, NIH PO1 GM
31299, and NSF MCB 94 20769. E. M. was supported
by a DOE Hollaender fellowship. We thank M. K.
Baron for her work with the Database of Interacting
Proteins.
28 December 1998; accepted 23 June 1999
Fig. 4. The detection of “promis-
cuous” domains for filtering of
false interactions by the domain
fusion method. For each protein
domain (as defined in the Pro-
Dom database), we calculated
the number of Rosetta Stone
links that could be found to oth-
er domains. Plotting this distri-
bution shows that for most do-
mains (⬃95%), only a few Ro-
setta Stone links are found. For
the remaining ⬃5% of domains,
many links are found. These
“promiscuous” domains are do-
mains such as the SH3 domains
and ATP-binding cassettes that
are found in many otherwise un-
related proteins.
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