Download Conformational flexibility may explain multiple cellular roles of PEST

PROTEINS: Structure, Function, and Bioinformatics 63:727–732 (2006)
SHORT COMMUNICATION
Conformational Flexibility May Explain Multiple Cellular
Roles of PEST Motifs
Kuljeet Singh Sandhu and Debasis Dash*
G. N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology (IGIB), CSIR,
Delhi, India
ABSTRACT
PEST sequences are one of the
major motifs that serve as signal for the protein
degradation and are also involved in various cellular processes such as phosphorylation and protein–
protein interaction. In our earlier study, we found
that these motifs contribute largely to eukaryotic
protein disorder. This observation led us to evaluate
their conformational variability in the nonredundant Protein Data Bank (PDB) structures. For this
purpose, crystallographic temperature factors,
structural alignment of multiple NMR models, and
dihedral angle order parameters have been used in
this study. The study has revealed the hypermobility of PEST motifs as compared to other regions of
the protein. Conformational flexibility may allow
them to participate in number of molecular interactions under different conditions. This analysis may
explain the role of protein backbone flexibility in
bringing about multiple cellular roles of PEST motifs. Proteins 2006;63:727–732. © 2006 Wiley-Liss, Inc.
INTRODUCTION
Tremendous amount of work gone into understanding
various proteolysis machineries has provided a detailed
insight into the biochemical mechanism of rapid protein
turn over process. Several sequence motifs acting as
protein degradation signals have been identified and experimentally validated in various proteins. Some of these are
KFRQ motifs, cyclin destruction box, carboxy terminal tag,
and widely studied PEST motifs. PEST motif was first
proposed by Rogers and colleagues in 1986 as motifs
locally enriched in proline (P), glutamic acid (E), serine (S),
or threonine (T) and, to a lesser extent, aspartic acid.
These motifs are generally, but not always, flanked by
clusters containing several positively charged amino acids.1 PEST regions have been shown as degradation signal
for ubiquitin-, caspase-, and calpain-mediated proteolytic
pathways.2– 4 Their role in protein degradation has been
validated by complete removal, transfer, and site-directed
mutagenesis.2– 6 More importantly, PEST motifs are also
found to be involved in various other cellular processes
such as protein–phosphorylation, protein–protein interaction, cell adhesion, etc.7–14 Our recent genome wide analysis on PEST motifs has revealed the abundance of PEST
©
2006 WILEY-LISS, INC.
motifs in eukaryotic proteomes. PEST motifs were found to
be overrepresented in the proteins belonging to nucleic
acid and protein binding, transcription regulation, and
signal transduction classes.15 They were also found to be
surface exposed, enriched in characterized disordered protein database, and contribute largely to eukaryotic protein
disorder.15 These observations motivated us to do a comprehensive conformational flexibility analysis of these motifs
that might provide insight and possible explanation for
their multiple cellular roles.
Conformation flexibility (or mobility) is an inherent
property of the protein structural behavior and is attributed to various biochemical activities. Although the existence of small- and large-scale protein motions has been
well reported, their roles in biological processes need to be
explored at a wider scale. Nevertheless, several types of
atomic motions have been assigned to certain specific
biological functions. One such example is the S-4 peptide
corresponding to a voltage-gated potassium ion channel,
which has high degree of conformational flexibility and can
undergo large changes in its structure in response to its
environment. This probably has important implications
for its role in the voltage activation process.16 Structural
flexibility has also been related to functional versatility of
small GTPases.17 Conformationally mobile regions of the
proteins have previously been shown to be more susceptible to various proteolysis machineries.18 –20 It has been
strongly emphasized that although the surface accessibility is a necessary requirement for proteolysis, the peptide
bonds present in the flexible regions are the preferred sites
of cleavage.20,21
The conformational flexibility or atomic fluctuations in a
protein can be measured by various methods like analyz-
The Supplementary Materials referred to in this article can be found
at http://www.interscience.wiley.com/jpages/0887-3585/suppmat/
*Correspondence to: Debasis Dash, G. N. Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and
Integrative Biology (IGIB), CSIR, Delhi University Campus, Mall
Road, Delhi-110 007, India. E-mail: [email protected]
Received 8 August 2005; Revised 6 December 2005; Accepted 7
December 2005
Published online 21 February 2006 in Wiley InterScience
(www.interscience.wiley.com). DOI: 10.1002/prot.20918
728
K. S. SANDHU AND D. DASH
ing crystallographic temperature factor (B-factor), root
mean square deviation (RMSD) of superimposed structures, order parameter, etc. B-factors (or temperature
factors, or Debye–Waller factor) obtained from X-ray crystallographic structure represents the smeared spots in the
electron density map due to thermal atomic motions. It is a
measure for the degree to which the electron density is
spread out, that is, a measure of atom oscillation or
vibration around the equilibrium position.22 B-factor is
given by
B i ⫽ 8␲ 2Ui2
where U2i is the mean square displacement of the atom i.
Careful analysis of these B- factors available in the PDB
files provides the measure of flexibility and dynamics of
the atoms of interest in the protein. B-factors have already
been used to evaluate the flexibility of regions of interest in
the proteins.23–25 Protein structure determined by nuclear
magnetic resonance (NMR) spectroscopy is often submitted as an ensemble of many models, each consistent with
the restraint set used. These models can also be used to
identify the flexible regions in the protein. This is achieved
by superimposing multiple structure models to calculate
the root mean square deviation (RMSD) of the backbone
atoms. Similarly, another parameter that reflects the atom
motions in the protein is the dihedral angle order parameter (s). Since the emergence of Ramachandran angles (␾,
␺), they are considered as measure of conformational
freedom of backbone atoms in the protein. Comparing the
␾, ␺ angles across different structures of the same protein
can provide an index of the backbone flexibility at each
residue. Dihedral order parameter is a derived notation
that reflects the local deformability of protein backbone.26
This is given by the following equation:
s(␹ i) ⫽
1
n
冏冘 冏
n
␹ij
j⫽1
where n is the total number of structures and ␹ij (j ⫽ 1…n)
is the two-dimensional (2D) unit vector with phase equal
to dihedral angle ␹i (where i is the residue number). Order
parameter for dihedral angles (␺, ␾) inversely correlates to
the local deformability of the backbone residues and
ranges from 0 to 1.26
We have implemented all of the aforementioned methods on 236 PEST containing PDB chains to examine the
backbone mobility in the PEST motifs. This is the first
comprehensive analysis of conformational flexibility in
PEST motifs known so far.
MATERIALS AND METHODS
Protein Dataset
A nonredundant dataset of 4588 PDB chains were
extracted from PDB-REPRDB server27 as on 14 December
2004 using following criteria: (1) length ⬎ 40; (2) resolution ⱕ 3 Å; (3) R factor ⬍ 0.3; and (4) sequence identity ⬍
30%, or RMSD ⱖ10 Å.
PEST Motif Search
PEST motifs were searched in the above data using
epestfind (Emboss). We obtained 236 nonredundant PESTPROTEINS: Structure, Function, and Bioinformatics
containing PDB chains, out of which 209 were X-ray
crystal structures and 27 were NMR structures.
Surface Accessibility and Secondary Structure
Accessible surface area (ASA) values were taken from
DSSP (definition of secondary structure prediction; http://
bioweb.pasteur.fr/seqanal/interfaces/dssp.html) profiles. A
residue was categorized as surface residue if its ASA
was ⱖ 25% of its nominal surface area.28 Only regular
secondary structures ␣-helix (H) and extended ␤-sheet (E)
were taken from DSSP profile and all others are classified
as irregular (U).
Crystallographic B-Factors
B-factors (temperature factors) of all C␣ atoms for each
protein were extracted from the PDB files and normalized
using following equation:
B⬘ ⫽
B⫺B
␴
where B is the actual B-factor, B is the average B-factor,
and ␴ is standard deviation for all C␣ atoms in each PDB.
Analysis of NMR Structures
NMR protein structures available in the Protein Data
Bank generally contain more than one structure models of
the same protein. The average or the representative
structure for each NMR entry was calculated using NMRclust software (http://neon.chem.le.ac.uk/olderado/). All
other models were then superimposed to this representative model in pairwise manner using VMD’s (http://
www.ks.uiuc.edu/Research/vmd/) structural alignment
module (STAMP). Dihedral angles (␾ and ␺ and order
parameters were calculated for each NMR ensemble using
PERL scripts developed in house.
RESULTS
Crystallographic B-Factor Analysis
The frequency distribution of normalized B-factors was
plotted for the PEST and non-PEST regions in the 209 X-ray
crystallographic structures. To verify whether the flexibility
in the PEST motifs is contributed by particular conformation, we also analyzed the B-factor distribution with respect
to various secondary structures, that is, helix (H), sheet (E),
and others (U) (Fig. 1). The individual plots for the PEST and
non-PEST residues in the different conformations revealed a
similar trend towards the higher flexibility in PEST regions
than in non-PEST regions. Interestingly, regardless of the
fact that most of the residues in the irregular conformations
are inherently flexible, PEST residues still show higher
flexibility in the dataset considered. PEST residues are found
to be flexible even in the most rigid ␤-sheet conformational
state, though to lesser extent as compared to other conformations (Fig. 1).
p Values of paired two-tailed t tests were calculated for
difference in the average B-factor values of PEST and
non-PEST regions. The p value was found to be significant
for each dataset considered (Table I). Thus, the distribution plots of normalized B-factors in various conformational locations clearly show the differential preference of
DOI 10.1002/prot
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MULTIPLE CELLULAR ROLES OF PEST MOTIFS
Figure 1. Frequency distribution plot of normalized B-factors for the PEST (dotted line) and non-PEST
residues (smooth line). (A) For all the resolved residues, (B) for residues falling in helices, (C) for residues
falling in sheets, and (D) for residues falling in other regions.
TABLE I. p Values of Paired Two-Tailed t Tests for
Difference in The average B-Factors of PEST and
Non-PEST Regions in Different Secondary
Structures (H, E, and U)
Secondary Structure
p Value
All
Helix (H)
Sheet (E)
Others (U)
1.35E-08
1.61E-05
0.001339
7.96E-09
TABLE II. RMSD (Å) Values for Random (Non-PEST) and
PEST Motifs in the NMR Ensembles
Root Mean Square Deviation (Å)
high B-factors (more flexible) in the PEST residues than
non-PEST residues.
Superimposition of NMR Models
PEST motifs of all the NMR models (of a single structure) were structurally aligned with the PEST motif of the
single representative model of the ensemble in a pairwise
manner. Root mean square deviation (RMSD) for each
ensemble is the average of all the pairwise RMSD values.
The average RMSD values for the PEST motif (RMSDP)
were compared with that for random motifs (RMSDR) of
length 15 to 30 amino acid residues from non-PEST
regions of the same protein chain. This analysis revealed
that PEST regions had comparatively higher RMSD values than non-PEST regions (Table II). The p value of the
paired two-tailed t test for difference between RMSDP and
RMSDR values was found to be significant (0.000629).
Dihedral Angle Order Parameters
To calculate deformability at each residue, order parameter (s) for the backbone dihedral angles (␾, ␺) was used.
PDB ID
Random Motif
PEST Motif
1ap8_
1d7q_A
1ddb_A
1gxe_A
1khm_A
1lmz_A
1n4t_A
1oqy_A
1pn5_A
1q38_A
1ri9_A
1sr3_A
1dip_A
1lv3_A
1t0g_A
1udl_A
1uey_A
1umq_A
1v27_A
1.75
0.83
0.61
2.25
1.45
0.64
0.88
5.89
2.48
0.92
0.21
1.04
2.38
3.01
0.47
2.24
0.33
1.23
0.78
4.06
8.63
4.01
6.48
0.4
0.95
1.24
7.48
2.93
4.81
0.17
2.63
8.22
6.59
0.9
2.76
2.28
4.37
1.1
Since the Omega (␻) does not contribute much to the
backbone flexibility, it is omitted from the analysis. The
frequency distribution of order parameters (for 24 NMR
structures that were submitted as ensembles) is plotted for
PEST and non-PEST regions. This analysis revealed higher
deformability in the PEST regions and less in the nonPEST regions. This was seen to be true for both ␾ and ␺
PROTEINS: Structure, Function, and Bioinformatics
DOI 10.1002/prot
730
K. S. SANDHU AND D. DASH
Figure 2. Frequency distribution of order parameter for (A) phi, (B) psi dihedral angles in PEST and
non-PEST regions of the NMR structures. Darker bars are for PEST and lighter for the non-PEST regions.
TABLE III. p Values of Paired Two-Tailed t Tests for the
Difference in the Average Dihedral Order Parameters
Between PEST and Non-PEST Regions
Order Parameter (s)
p Value
phi
psi
0.000415
9.66E-05
dihedral angles (Fig. 2). The p values of the paired
two-tailed t tests for the difference in the average values of
the order parameters (␾ and ␺) in PEST and non-PEST
regions were found to be significant (Table III).
DISCUSSION
Earlier, the structure function paradigm inferred that
the protein must acquire a stable conformation to carry out
its specific biological function. But with the emergence of
protein disorder concept, it is now believed that the
conformationally mobile regions in the proteins may have
their own importance in many biological processes. Although certain biological functions like enzyme catalysis,
epitope recognition, and receptor–ligand interaction do
require stable spatial organization in form of rigid fold for
the activity, functions related to cellular signaling and
regulation can be achieved by linear and flexible regions of
the protein. The structural variability is well documented
for functionally important regions for a number of proteins. For example, the flexibility in the coiled coil structure of DNA repair protein Rad50 is required to make a
specific orientation to accommodate the DNA replication
fork29 and the conformation flexibility plays a critical role
in modulating IgE interaction with Fc⑀RI receptor.30 Conformational fluctuations seem to be an important structural property of membrane-active fusion protein domains.31 It was found that structural mobility of D2 and
D3 loops of EcHsp31 chaperone leads to exposure of a
hydrophobic patch near the dimer interface that plays a
crucial role in recruiting the target protein.32 Sometimes,
flexibility also plays a role in enzyme activity by specific
domain or hinge movement.33 Posttranslational modifications (methylation, phosphorylation, ubiquitination, etc.)
of histone proteins occur on the flexible terminals.34,35 The
importance of unstructuredness for the protein phoshoryPROTEINS: Structure, Function, and Bioinformatics
lation is well explained by Iakoucheva and colleagues.36
Several types of protein–protein interactions have shown
the involvement of flexible unstructured regions.37 Conformational flexibility in the protein degradation sites has
also been studied to some extent. It has been reported that
the denatured and flexible proteins degrade more rapidly
than the compact ones.38,39 Zhang and colleagues reported
flexibility of PEST motif, a protein degradation signal, in a
rapidly degrading enzyme Ornithine decarboxylase.18 Degradation of some proteins is found to be inhibited when
stabilized against unfolding.40,41 A significant correlation
between sites of limited proteolysis and sites of high
B-factor values has already been reported.20 Recently,
Prakash and colleagues has shown that the unstructuredness is essential for the initiation of protein degradation in
ubiquitin-mediated degradation.42 The most preferred location of such unstructured regions was found adjacent to
ubiquitination sites.42 As an interesting phenomenon,
Picotti and colleagues has experimentally demonstrated
that the mutation of a helix-breaking Pro88 to helixinducing Ala/Gly residue in segment 82 to 94 of apomyoglobin stabilizes the protein from limited proteolysis by
various proteases. More interestingly, this chain segment
is in fact a PEST-like sequence (P88, E85, S92, and T95).21
Involvement of PEST motifs in various protein degradation machineries is well documented in the literature.1– 4
Apart from this, PEST motifs are also shown to interact
with several proteins.12,13 Systematic yeast two-hybrid
experiment has shown that a physical interaction between
the oligomerization domains of p73-␣ and p53 with HIPK2
(homeodomain interacting protein kinase 2) involves a
PEST sequence.9 The same PEST domain of mammalian
HIPK2 was shown to interact with US11 protein of herpes
virus (homeodomain interacting protein kinase 2)10 — an
example of multiple interaction partners of PEST motifs.
As an important observation we also found PEST motif
overlapping partially or completely with the protein–
protein interface in some of the protein complexes of our
dataset (see Supplementary Material). Several kind of
posttranslational modification sites map on or adjacent to
PEST motifs. Phosphorylation is well reported in the
serine/threonine residues of PEST motifs.7,43– 45 O-glycosylation of some proteins is shown to mask PEST sequence
DOI 10.1002/prot
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MULTIPLE CELLULAR ROLES OF PEST MOTIFS
Figure 3. Frequency distribution of normalized B-factors in PEST (dotted line) and non-PEST regions
(smooth line) for (A) PEST involved in protein–protein interaction dataset. p Value of paired two-tailed test for
difference in the average B-factors in PEST and non-PEST region is 0.00552. (B) rest of the dataset. The p
value found here is 1.87E-12.
and hence prevents the degradation pathway.46 SUMOylation of some proteins on the PEST motifs is also cited.47,48
Considering the role of flexibility in the above-mentioned functions and involvement of PEST motifs in such
functions, these motifs are expected to be flexible in
conformation. However, there is lack of comprehensive
structural studies that focus on this aspect. The present
study is a step in this direction.
Our comparative B-factor analysis explains that the
conformational flexibility is an inherent property of the
PEST motifs in the proteins (Fig. 1). This is true regardless
of their secondary structure, though the secondary structure analysis of PEST motifs showed their low occurrence
in the regular ␣-helices and ␤-sheets (see Supplementary
Material). The analysis of NMR ensembles showed that
the PEST motifs are highly perturbed as compared to
other parts of the protein. RMSD for the PEST motifs
differed significantly from that of random motifs selected
from the non-PEST regions of the protein. (p value ⫽
0.000629). The order parameter of dihedral angles (␾, ␺),
which provides the single residue perturbation, has also
given similar results. The PEST residues showed low order
parameters in comparison to non-PEST residues. We also
performed molecular dynamics (in water) and normal
mode analysis (NMA) for a few PDB structures. The initial
results support our earlier findings (see Supplementary
Material).
Additionally, we found that the PEST motifs that were
involved in protein–protein interaction (in our dataset)
were comparatively less flexible than the other ones (Fig.
3; also see Supplementary Material). This can be a possible
conformational consequence of protein–protein interaction. Earlier reports where the transition from disordered
to ordered state upon binding is reported may explain this
observation to some extent.37 Conformational transition is
reported during the heme binding to a PEST-like sequence
(82–94) in apomyoglobin. The interaction of heme molecule compensates the helix-breaking effect of Proline and
therefore leads to formation of helix-F in heme-bound
holomyoglobin state. This transition from disordered (loop)
to ordered (helix) state stabilizes the holomyoglobin from
rapid proteolysis.21 Such conformational transitions have
also been seen during phosphorylation of proteins that
subsequently affects the function.49 These conformational
transitions cannot be expected in the lack of enough
backbone flexibility in the corresponding peptide/protein.
Therefore, the role of PEST motif in the protein degradation and other important cellular processes can be explained considering its hyperflexibility and surface accessibility (see Supplementary Material). Their flexible nature
may be crucial for their recognition by multiple macromolecules. Conformational freedom may allow them to move
and/or acquire shapes corresponding to interacting partner and other physiological conditions. These flexible
regions can thus form multiple meta-stable conformations
for multiple interactions of high specificity but low affinity.
The interplay of conformational flexibility and other structural features of the PEST motifs need to be explored and
validated by experimental studies in future for a more
appropriate and complete understanding of PEST hypothesis.
CONCLUSION
Our analysis revealed that the protein degradation
signal motifs (PESTs) are comparatively more flexible
than other parts of the protein. Our observations suggest
that the conformational flexibility of PEST motifs is an
important requirement for its role in various cellular
processes.
ACKNOWLEDGMENT
The authors thank to Dr. Souvik Maiti, Ms. Mythily
Ganapathi, and Mr. G. P. Singh for their critical suggestions in writing the manuscript. Financial support from
CMM0017 to KSS and DD is gratefully acknowledged.
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DOI 10.1002/prot