Discovering critical residues in glutathione reductase - Gentoo

Discovering critical residues
in glutathione reductase
Donnie Berkholz
25 March 2006

Introduction
Glutathione reductase (GR) is a ubiquitous enzyme that catalyzes the
reduction of diglutathione (GSSG) to two reduced glutathione molecules (GSH)
with the concomitant oxidation of NADPH. It does so via FAD and a disulfide
linkage within the protein.
GR plays many important roles because of the importance of reducing
equivalents. It maintains the level of reduced thiols in the cell, because
glutathione can also reduce the other primary cellular thiol, thioredoxin. GR is
critical in preventing high levels of oxidative stress because its activity can
counteract oxidation. Glutathione reductase also is important in synthesis of
DNA precursors as well as proton transport across membranes.
Glutathione reductase has been suggested as a potential drug target in
malaria because the primary malarial target in humans is the red blood cell
(erythrocyte) [1]. In RBCs, 10% of produced glucose goes toward NADPH
production for glutathione reductase, so it is clearly a critical enzyme there. GR's
importance in reducing oxidative stress suggests that if the GR in Plasmodium
falciparum could be disabled while the human GR retained activity, it would
strongly impact the effect of malaria.
Much of the reaction mechanism has already been proposed [2][3], but it
has not yet been proven. Crystal structures of dead-end intermediates and nonreactive
proteins illustrated potentially important residues. But as the entire
reaction pathway has not been tracked experimentally, all the residues involved
can only be conjecture based on their proximity and likely reactivity.

To understand possible changes in GR's mechanism, one must first
comprehend our current knowledge of the mechanism. GR operates in a pingpong
fashion, meaning the NADPH binds and transfers a hydride to FAD, then
leaves, before the diglutathione ever binds. In other words, the two substrates
are mutually exclusive.
Tyr197 forms a protective shield over FAD to keep it from being oxidized
when NADPH is not bound, then swings out of the way when NADPH binds and
forms a strong hydrogen bond with Thr369. Arg291 and Asp331 form another ion
pair near FAD. In three separate cases, ion pairs exist near the flavin with the
positive residues of the pair pointed at the flavin.
Other residues known important in binding of the NADPH phosphate
include Arg218, Arg224, His219 and some integral waters. The nicotinamide ring
is where the hydride is transferred to FAD, and there are a number of residues
suspected to be critical there. Residues involved in binding the nicotinamide
include Leu337, Glu201, Lys66, Val370 and Thr369. Glu201 and Lys66 also form
a salt bridge.
In glutathione binding, residues directly hydrogen bonding to glutathione
include side chains of Ser30, Arg37, Tyr114, Arg347, His467' and Glu473' as well
as main chain atoms of Met406' and Thr469'. Tyr114 moves about 1A on GSSG
binding and fits well between the glycine moieties of the two glutathiones. It's
well positioned to be a proton donor for a leaving glutathione, but unlikely
because of its normally high pKa. It could be interesting to examine whether any
nearby conserved residues could modify its pKa. Through-water hydrogen bonds
occur with the side chains of Lys67, Tyr106, Asn117, Ser470', Glu472' and

Thr476' and the main chain of Gly55, Pro468' and Thr476'.
The first step of the reaction is the NADPH-dependent reduction of FAD.
Tyr197 may also play a role here, acting as a “spring” to force the nicotinamide
ring closer to the FAD to ease hydride transfer. In addition, the Lys66-Glu201
salt bridge is near where the hydride transfer occurs.
Next, the flavin reduces the disulfide Cys58-Cys63, likely through an
intermediary adduct with the sulfur of Cys63. Few important residues have been
proposed in this step of catalysis.
Finally, the reduced, former disulfide reduces GSSG and is reoxidized to
the disulfide. Cys63, His467' and Glu472' have been proposed to act similarly to
the catalytic triad in serine proteases – glutamate activates the histidine, which
in turn creates a highly nucleophilic cysteine. The importance of His467' as a
proton acceptor and donor has also been shown via mutagenesis. But again,
while the residues most active in catalysis have been proposed, not all of the
critical residues that enable catalysis in the region have been elucidated.
A bioinformatic approach to finding important residues in glutathione
reductase could allow detection of what must be critical to its activity or
structure. Using a combination of multiple sequence alignments, phylogenetic
trees, and tree-based calculation of conserved residues, the goal of this project is
to decipher what residues really are critical in GR and propose roles for them.
This will combine checking for amino acids previously thought vital to binding
and catalysis as well as a rational search for other, unknown conserved residues.
In addition, a short survey of available methods and program implementations
for accomplishing this goal will be made to discern which methods work the best.

Materials and Methods
Multiple sequence alignments
ClustalW [4] is a progressive, global multiple sequence alignment program.
It performs all possible pairwise alignments, uses those to create a neighborjoining
phylogenetic tree, and aligns the sequences using dynamic programming
based on the tree. The most closely related sequences are aligned first, and more
and more distant sequences are added on.
T-Coffee [5] is a more complex global MSA program that begins with
ClustalW output and a set of pairwise local alignments from LALIGN, then
creates a set of weights from those to produce a progressive MSA. The primary
downside is that T-Coffee generally takes more than 10 times longer to run than
most other MSA programs.
Dialign-T [6] is a local alignment program that excludes poorly matching
subfragments and adds sequences to the alignment based on their weight scores
in a way that removes bias from highly similar pairs.
Muscle [7] is another global MSA program that makes use of a “logexpectation”
score and again, a phylogenetic tree, to partition sequences in a
tree-based manner.
ProbCons [8] is based on a new model of alignment called probabilistic
consistency. It uses pairwise HMM-based alignments, but it does them with
three-way consistency. That means that if sequence A and B align well, and B
and C align well, then A and C must align well. In addition, rather than using a
typical arbitrary substitution matrix as most alignment programs do, it trains
itself on available sequence databases to create an experimentally supported

matrix. It performs roughly 7% better than T-Coffee in finding 100% sequence
identity at a given position, 11% better than ClustalW and 14% better than the
local alignment program Dialign.
Phylogenetic trees
ProML from the PHYLIP [9] package was used to calculate maximum
likelihood trees. However, using the best models available and an amino acid
sequence rather than a DNA sequence resulted in extensive computational time.
MrBayes [10] was used to calculate Bayesian trees. MrBayes operates
using a Markov chain Monte Carlo method, which uses a hidden Markov modelbased
random search of the available tree space. The method has a true basis in
statistics and results in probability-based trees; this precludes the need for
bootstrapping.
In both programs, the distribution model of rates was a gamma distribution
with additional invariant sites. In ProML, the gamma distribution was
approximated with 5 separate rate categories. In MrBayes, 6 rate categories
were used.
Conservation of residues
ConSurf [11] was used to evaluation evolutionarily-based residue
conservation. Version 3.0 was chosen because it implements a Bayesian method,
which was shown to be superior to the older maximum likelihood method for
smaller numbers of sequences.

Figure 1: Alignment of Arg218. From left to right, ClustaW, Dialign-T, Muscle and
ProbCons. Conservation values are below. See text for discussion.
Results and Discussion
To discover the best multiple sequence alignment program for this project,
a survey of the literature was made using Google Scholar. The search focused on
global alignment methods because the glutathione reductase sequences in the
alignment were similar through their entire lengths, rather than just having
small domains of similarity. However, one local alignment method, Dialign-T, was
included because reviews showed it comparing favorably with both local and
global alignment programs when used against databases. The compared
programs were ClustalW, Dialign-T, T-Coffee, Muscle and ProbCons.
Out of all the programs, only ProbCons managed to find a 100% conserved

arginine at position 218. All of the other programs failed to align their gaps
correctly rather than not having gaps at all, indicating that this could not be
fixed by tweaking gap penalties or gap extension penalties. In JalView, the
ProbCons alignment shows clearly higher alignment scores throughout the entire
region (Figure 1).
Figure 2: Cladistic credibility values of the Bayesian mixed-model tree. See
text for discussion.
To discover the best fixed-rate amino acid substitution matrix for these

sequences, a convenient feature of MrBayes was used called the mixed model.
This model samples from all the available matrices, and the amount of time spent
using each matrix indicates the probability of that matrix being the best fit for
the data. This is computationally much cheaper than optimizing all the variables
in even a fairly simple variable-rate model. Variable-rate models were also
attempted, but they were too computationally expensive. Even a simple variablerate
model with only 19 free variables failed to converge after a solid week of
computing. Over the course of 100,000 cycles, MrBayes spent nearly 100% of its
time using the WAG matrix, indicating its superiority over the typically used JTT
matrix for the GR sequences. The WAG matrix was created using phylogenetic
inference and maximum likelihood against large databases and is intended
primarily for globular proteins, which GR approximates.
Figure 3: The environment of NADPH. See text for discussion.
The resulting tree showed strong support for roughly the expected results,

with one exception (Figure 2). There was about 90-100% support for the entire
tree except for placement of the plants within the tree, which only had about 65-
70% support. Other than that, as expected, animals split out from plants, and
both of them split apart from prokaryotes. No further analysis of the tree itself
will be made, because it was intended as an intermediate for input into further
programs.
ConSurf is a program to calculate evolutionarily conserved residues and
map them onto a protein structure. The true power of it is in its flexibility – it will
take a list of sequences and a PDB ID as input, or you can input a precalculated
sequence alignment, or even a precalculated phylogenetic tree, along with your
own PDB. This allows for potential creation of better structural conservation
maps, because ConSurf just uses ClustalW for alignment and a simple neighborjoining
tree. ConSurf outputs a large table of conservation values, and optionally
replaces the B factors in the PDB file with conservation values, so any molecular
graphics program can be used for the analysis. However, ConSurf does not yet
allow delving into tree-determinant residues. In other words, no simple way
exists to analyze changes on smaller level than the entire tree to examine
changes in function between different Grs.

Figure 4: Ile26 in FAD binding. See text for discussion.
Initial analysis focused on the active site, where there is already a long list
of residues suspected important in binding and catalysis. Near the NADPH
(Figure 3), one can see that many of the expected residues were conserved:
Arg291, Glu201, and others. But there are more conserved residues: Ser177,
Asp178, Gln445, and interestingly, Ile198. Ser177 appears to hydrogen bond
with the nicotinamide ring, which may serve to orient it correctly for hydride
transfer. It's already known that generally the positive residue of ion pairs is
nearer to the flavin, but what grows more clear here is that there are conserved
positive residues above the flavin (Gln445 and Arg291 on the NADPH side), and
the conserved negative Asp178 below the flavin. This negative charge just below
the carbon that accepts a hydride from NADPH may serve some purpose in

assisting with reduction of the Cys58-Cys63 disulfide.
Figure 5: Arg218 binds the phosphate of NADPH. See text for discussion.
Ile198 could be involved in hydrophobic binding of NADPH, as it points
toward the nicotinamide ring. It's also in the environment of the Lys66-Glu201
salt bridge, so it could serve to lower the local dielectric constant and strengthen
the interactions of the salt bridge with the nicotinamide and flavin. In a similar
way as Ile198 may bind NADPH, Ile26 appears involved in hydrophobic binding
of the adenine moiety of FAD (Figure 4). It's about 3.8A away from the ring and
may stabilize binding.

Figure 6: The Cys58-Cys63 disulfide environment. See text for discussion.
The phosphate of NADPH must be stabilized in some way, but previous
analysis revealed no nearby positively charged residues. They hypothesized that
it was stabilized via hydrogen bonds with waters. The present analysis reveals
Arg218 with its backbone nitrogen only 4A from an oxygen of the phosphate and
its sidechain about 4.3A from the adenine moiety of NADPH (Figure 5).
Many residues are conserved near the Cys58-Cys63 disulfide loop,
including Ser30 and Thr339 (Figure 6). The threonine is only 3.5A from the
sulfur of Cys63, but its role is unclear. It may serve to stabilize a charged
reaction intermediate with a hydrogen bond. Ser30 is a bit farther away from
Cys58, 4.6A, but it could serve a similar purpose with a small conformational
change, as would happen when the disulfide bond is reduced.

Figure 7: Catalytic residues His467' and Glu472'. See text for discussion
The catalytic His467' and Glu472' are on the opposite end of the protein
from the active site, because they participate in the active site of the other
dimer. One can see that the carboxyl group of Glu472' is about 3A from the
imidazole ring of histidine, with one oxygen at 2.8A and another at 3.2A (Figure
7). Also, Pro468' is highly conserved because it allows for one of the two cis
peptide bonds in the protein, which is required for the correct conformation of
histidine and glutamate. Thr469' and Glu473' are conserved as well, but their
roles are unclear without analysis of the entire dimer with them in the active
site. Their negative charges could keep Glu472' near the histidine ring so it's
always able to polarize the imidazole.

Figure 8: Phe254, a surface hydrophobic residue. See text for discussion.
Moving away from residues involved in the active site, one can examine
where hydrophobic conserved residues fall within the protein. As Kendrew's
rules say, (1) Hydrophilic residues are on the surface, (2) Hydrophobic residues
are in the core, and (3) Any violation of the above rules indicates function.
Following this, there is an odd occurrence of a 100% conserved hydrophobic
residue on the surface of the protein away from the active site, Phe354 (Figure
8). As this is grossly energetically unfavorable, it must serve some purpose,
although what purpose exactly remains unclear. If one looks at nearby nonhydrophobic
conserved residues, one finds Ala39 and Asp22, both about 4-5A
from the phenylalanine ring. This suggests some sort of binding site for an
inhibitor or activator, because no structural stability is possible from it, and the

active site is quite far away.
Figure 9: Conserved hydrophilic surface residues near the NADPH binding site
entrance. See text for discussion.
Another, more typical occurrence of surface conserved residues is Asp316,
Thr321 and Asp22 (Figure 9). Asp316 and the threonine are 6.6A apart,
precluding a direct interaction. Asp22 is roughly 15A away from both of them.
They fall near where NADPH should enter its binding site, so they may serve as
some sort of gatekeepers or maintain the structure of the binding site's entrance.

Figure 10: Structural stabilization. See text for discussion.
The final group of conserved residues in this analysis falls at a junction of
beta sheets and an alpha helix (Figure 10). Positively charged His434 and
Lys420 extend out from the beta sheets toward the helix's Asp227 and Glu384
from the nearby loop. These 100% conserved, balanced charges suggest some
gain in structural stability. It may be that this particular part of the structure,
while nowhere near the active site, must be retained or some sort of allosteric
effect could reach into the active site and dramatically affect binding or
catalysis. Another possibility is that these residues are critical in GR's folding
process.
In conclusion, this study has used bioinformatics as a tool in analysis of
structure-function relationships. Remaining work includes checking whether the

model used for tree-building was valid, expanding this study to all known GR
sequences, creating more experimental enzymology data, and analyzing treedeterminant
residues. It found new critical residues and proposed functions for
some of them, while functions for others remain to discern. It confirmed the
importance of many catalytic residues. It determined the best alignment program
to use with this set of sequences, as well as the best amino acid substitution
matrix for use in creating phylogenetic trees.
References
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