Download Sequence to Structure Analysis of DOPA Protein from Mucuna

IJETST- Vol.||02||Issue||08||Pages 3083-3089||August||ISSN 2348-9480
2015
International Journal of Emerging Trends in Science and Technology
DOI: http://dx.doi.org/10.18535/ijetst/v2i8.12
Sequence to Structure Analysis of DOPA Protein from Mucuna pruriens: A
Computational Biology Approach
1 ϯ
Authors
Laxman Nagar * , Anuj Kumar2 ϯ, Vimala. Y1, MNV Prasad Gajula3,*
1
2
Department of Botany, Ch. Charan Singh University, Meerut 250004, UP, India
Bioinformatics Infrastructure Facility (BIF), CCS University, Meerut 250004, India
3
Institute of Biotechnology, PJTSAU, Rajendra Nagar, Hyderabad-500030, India
Ϯ Equal Contribution
*Corresponding Author
MNV Prasad Gajula
Institute of Biotechnology, PJTSAU, Rajendra Nagar, Hyderabad-500030, India
Email: [email protected]
Abstract
L-DOPA, (L-3, 4-dihydroxyphenylalanine), an anti-nutritional compound is an important intermediate of
secondary metabolism in higher plants and is known as a precursor of alkaloids, betalain, melanine, and
others. We analyzed the amino acid sequence of DOPA protein from M. pruriens by using computational
methods. The DOPA protein M. pruriens was subjected to sequence, structural and functional annotation.
Functional domain prediction through Conserved Domain Database (CDD) suggested that DOPA proteins of
M. pruriens contain Aspartate aminotransferase (AAT) superfamily associated with various cellular activities.
The analysis of predicted secondary structure by PsiPred and SOPMA has shown that high percentage of
helices in the protein structure makes DOPA more flexible for folding processes. Sub-cellular localization
predictions suggested it to be a cytoplasmic `protein. Homology modeling method was used to deduce the
three-dimensional (3D) structure of selected DOPA proteins from M. pruriens. From template search results it
has been identified that all the hypothetical proteins share more than 50% sequence identity with crystal
structure of Sus scrofa, indicating proteins are evolutionary conserved. Several quality assessment and
validation parameters computed indicated that predicted homology models are in accordance with literature.
Current study will help researchers to better understanding of the predicted models and refinement.
Key words: L-DOPA, Homology Modeling, Secondary Structure.
1. Introduction
L-DOPA, (L-3, 4-dihydroxyphenylalanine), an
anti-nutritional compound is an important
intermediate of secondary metabolism in higher
plants and is known as a precursor of alkaloids,
betalain, melanine, and others. It is also a precursor
of catecholamines in animals and anti-nutritional
compounds confer insect and disease resistance to
plants [1], [2]. L-DOPA is a potent neurotransmitter
precursor that is believed, in part, to be responsible
Laxman Nagar et al
for the toxicity of the Mucuna seeds [3]. L-DOPA
plays a very important role in plant physiology and
for the treatment of Parkinson's disease [4]. Plants
synthesize great variety of non-protein amino acids,
among which L-DOPA, a compound with strong
allelopathic activity, stands out [5]. This
allelochemical is found in large quantities (1% and
4–7% in the leaves and seeds, respectively) in velvet
bean [Mucuna pruriens (L.) var. utiliz], a legume of
the Fabaceae family that has a nutritional quality
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comparable to the soybean [6], [7]. Velvet bean is often
used for soil cover and as silage due to the large
amount of organic matter with high digestibility it
produces. It is estimated that velvet bean can release
about 100–450 kg ha−1 of L-DOPA into the soil.
Furthermore, its ability to control weeds and
nematodes greatly reduces the need to apply artificial
chemicals to the crops [6], [8], [9]. In addition, its
cultivation in tropical areas is aimed at enriching the
soil due to its ability to fix nitrogen [10].
In our study we have considered M. pruriens, which
is considered to be one of the most popular Indian
medicinal plant, traditionaly used in Ayurvedic
Indian medicine, for treatment of different diseases
including parkinsonism, male infertility, nervous
disorders, and also as an aphrodisiac [11]. Due to high
protein concentration (23–35%) M. pruriens is
considered an important source of various dietary
supplements [12], [7]. DOPA from this herbal medicine
plant has not been well studied so far at genomic
level and the x-ray crystal or NMR structure is also
not available in Protein Data Bank (PDB). So we
analyzed the amino acid sequence of DOPA protein
from M. pruriens by using different bioinformatics
algorithms. We predicted the 3D model structure of
DOPA from M. pruriens by using homology
modeling method. We then studied the
stereochemical properties of the modeled structure
using Ramachandran plot. We also compared the
amino acid sequence with the other DOPA protein
sequence reported in different organisms.
2. Methods
2.1 Sequence Retrieval and Functional Domain
Analysis
DOPA/tyrosine decarboxylase DC1 from M.
pruriens was obtained from the Protein sequence
database of NCBI (GI: ABK97629). Functional
domain analysis was assessed using Conserved
Domain Database (CDD) available at NCBI which is
a collection of multiple sequence alignment
representing protein domains conserved in molecular
evolution. It contains the alignment data from protein
families’ databases such as Pfam and SMART [13],
[14]
.
Laxman Nagar et al
2015
2.2
Characterization
of
DOPA/tyrosine
decarboxylase DC1 Protein
The
physicochemical
properties
such
as
molecular mass, theoretical pI, amino acid
composition,
atomic
composition, extinction
coefficient,
estimated
half-life,
instability
index, aliphatic index, and grand average of
hydropathicity (GRAVY) were calculated by
ProtParam
from
EXPASy
server
(http://www.expasy.org/ ). The TargetP1.1 was used
to analyze the subcellular localization of DOPA [15].
In order to know the key residues responsible for
catalytic activity of
the
enzyme,
multiple
sequence alignment of DOPA with other closely
related protein of decarboxylase family having
known crystallographic structures was done
on
ClustalW2
program
(http://www.ebi.ac.uk/Tools/msa/clustalw2/ )
2.3 Secondary structure prediction
The secondary structure prediction was done by
SOPMA and PsiPred servers [16], [17].
The
predicted secondary structural information of
the enzyme was considered to improve the
target-template alignment and for building
conformations for 3D model of the DOPA.
2.4 Model building by Homology Modeling
Homology modeling or comparative modeling is the
one of the most robust method for protein structure
prediction. This method was supplemented for
protein structure prediction based on the
experimentally determined structure of another
homologous protein [18]. The position specific
iterated BLAST (PSI-BLAST) against Protein Data
Bank (PDB) was carried out to identify their
homologous structures based on the maximum
identity with high score and lower e-value [19], while
3D structure was predicted using automated
Swiss-Model server [20], [21].The modelled 3D
structure of DOPA was visualized using UCSF
CHIMERA 1.10 [22].
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2.5 Structure validation by SAVES
The Ramachandranplot of the modeled structure was
calculated by analyzing phi (Φ) and psi (ψ) torsion
angles using PROCHECK available on SAVES
server (htttp://nihserver.mbi.ucla.edu/SAVES/) [23],
[24]
, Molprobity, and PSVS server [25], [26]. Further, the
ProSA
(https://prosa.services.came.sbg.ac.at/prosa.php
)
verified the modeled structure (DOPA) structure
from X-ray analysis, NMR spectroscopy and other
theoretical calculations. The energy criteria of the
modeled structures were compared with large set of
known protein structures.
3. Results and Discussion
3.1 Sequence Retrieval and Functional
Domain Analysis
DOPA/tyrosine decarboxylase DC1 from M.
pruriens was extracted from the Protein sequence
database of NCBI (GI: ABK97629) having 164
amino acids in length. Conserved domains analysis
carried by CDD revealed that DOPA protein belongs
to Aspartate aminotransferase (AAT) superfamily
(Pssm-ID: 276217) with conserved domain length
164, bit score: 224.02 and e-value: 4.89e-71.
3.2 Characterization of DOPA Protein
Physiochemical properties of DOPA by ProtParam
tools are presented in (Table 1). Results show that
DOPA protein has a molecular weight of 17261.1
Daltons and an isoelectric point of 6.78. The
computed isoelectric point will be useful for
separating the protein on a polyacrylamide gel
by
isoelectric
focusing.
The
extinction
coefficient can be used to calculate the
concentration of a protein in solution. Stability of
DOPA was studied by analyzing the values for
instability index, aliphatic index and Grand
average of hydropathicity (GRAVY) index .
The value of instability index was 27.38
hence it could be safely predicted as a stable
protein. The aliphatic index refers to the relative
volume of a protein that is occupied by
aliphatic side chains and contributes to the
increased thermo stability of protein. Aliphatic
Laxman Nagar et al
2015
index of DOPA was 106.52. GRAVY index indicates
the solubility of proteins, GRAVY index of DOPA
was 0.896. GRAVY value for DOPA describes it to
be hydrophilic in nature. Subcellular localization
was predicted by TargetP1.1 revealed that DOPA
found in the cytoplasm.
Table 1. Physicochemical properties of DOPA/
tyrosine decarboxylase DC1predicted by ProtParam
program
Sr.No
1
2
3
Parameters
Molecular Weight
Theoretical PI
Extinction coefficient*
Values
17261.1Dalton
6.78
15720 at Abs
0.1% 0.896
4
Instability Index
27.38
5
Aliphatic index
106.52
6
Grand
average
of 0.392
hydropathicity(GRAVY)
* Extinction Coefficient units M-1cm-1 at 260 nm
3.3 Multiple Sequence Alignment
The identification of catalytic residues is a key to
understanding the function of proteins. With the
information from other functionally similar
sequences with known crystallographic structures we
can identify the key catalytic residues. ClustalW2
server was used for multiple sequence alignment of
DOPA with other decarboxylases from human
(PDB Id: 3RBF_A), Human aromatic L- amino acid
decarboxylase (PDB Id: 3RCH_A) and Human
histidine decarboxylase (PDB Id: 4E1O_A) shown
in (Fig.1).The compared sequences varied in
length but essentially conserved the key
catalytic residues which have been highlighted
with an asterisk (*) symbol.
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2015
Fig.2. Predicted secondary structure of DOPA
protein by using PsiPred Server.
Fig.1. Multiple Sequence Alignment (MSA) of
DOPA and templates proteins structure using
CLUSTAL 2.1.
3.4 Secondary Structure Prediction
Secondary structure was predicted by PsiPred and
SOPMA servers (Fig.2). The results from SOPMA
are shown in (Table 2).
Table 2. Secondary structure elements as predicted
by SOPMA for DOPA/ tyrosine decarboxylase DC1
Secondary
No of amino Percentage
structure
acid involved
Element
Alpha helix
76
46.34%
Extended
29
17.68%
strand
Beta turn
10
6.10%
Random coil
49
29.88%
3.5 Homology modeling of DOPA Protein
We selected a template from Protein data bank (PDB)
as a result of PSI BLAST which showed 56%
similarity (PDB ID: 1JS3, Chain A, Crystal structure
of DOPA decarboxylase in complex with the
inhibitor carbiDOPA, X-ray, Minimized Mean
Structure, Resolution: 2.25Å) to build 3D structure of
M. pruriens DOPA using automate homology
modeling server Swiss-Model (Biasini et al. 2014).
Generated model showing the closest Cα RMSD
(root-mean-square deviation) with respect to their
template upon superposition were selected for further
structural characterization. Generated model was
visualized by UCSF CHIMERA 1.10. (Fig. 3 (A))
High percentage of helices in the structure
makes the protein more flexible for folding,
which might increase protein interactions.
Moreover the predicted secondary structural
information
of DOPA was
considered
to
improve the target-template alignment and for
building 3D model of the DOPA.
Fig.3. Structure to validation: (A): Predicted 3D
model of DOPA protein; (B): Ramachandran plot for
predicted DOPA 3D model; and (C): ProSA plot of
DOPA protein
Laxman Nagar et al
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3.6 Structure Validation
Ramachandran dihedral statistics for DOPA revealed
a total of 88.7%, 9.2 %, 0.7% and 1.4% residues in
most favored, additionally allowed, generously
allowed and disallowed regions, respectively. The
Ramachandran plot generated by PROCHEK showed
the satisfactory geometry of the predicted model (Fig.
3 (B)), (Table. 3). PSVS predicted G- factor score (all
dihedral angles) -0.11 revaled that model was
2015
acceptable. Verified3D Z-score was -2.85 suggested
that generated model have good quality. ProsaII (-ve)
and MolProbity predicted. The Z-score -2.15 and
-9.27 also suggested a good model. S. Similar
studies were performed by Anuj et al. has shown that
the predicted models can be used for further research
[27. 28]. ProSA predicted Z-score value was -5.00,
evidencing highly reliable structure (Fig.3 (C)).
(Table. 3)
Table 3. Summary of structure quality factors of DOPA predicted by using SAVES and PSVS 1.5 server
Algorithm
Mean
SD
Z-score g
score
Procheck G-factor e(phi / psi -0.14
N/A
-0.24
only)
Procheck G-factor e(all dihedral -0.11
N/A
-1.65
angles)
Verify3D
0.28
0.0000
-2.89
ProsaII (-ve)
0.13
0.0000
-2.15
MolProbity clash score
Ramachandran Plot Summary
from Procheck
Most favoured regions
Additionally allowed regions
Generously allowed regions
Disallowed regions
62.91
0.0000
-9.27
88.7%
9.2%
0.7%
1.4%
f
Residues selected based on: Dihedral angle order parameter, with S(phi)+S(psi)>=1.8
Selected residue ranges: 1A-163A
g
With respect to mean and standard deviation for a set of 252 X-ray structures < 500 residues, of resolution <=
1.80 Å, R-factor <= 0.25 and R-free <= 0.28; a positive value indicates a 'better' score
4. Conclusion
In this present study, we have used sequence
analysis, secondary structure analysis, functional
domain prediction and structure prediction to assign
to DOPA protein from M. pruriens. L-DOPA is the
drug of choice in the treatment of Parkinsonism
disease. This study will lead for further research in
optimizing the functionality of DOPA which has
large implications in treatment of various human
diseases. Experimental validation through X-ray
crystallography and / or any other spectroscopic
techniques can provide more insight into the actual
function of this protein.
Laxman Nagar et al
Acknowledgment
Authors acknowledge DST for the Ramanujan
fellowship award SRN/S2/RJN-22/2011.
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