Quantitative structural insight into human variegate porphyria disease

Article abstract of DOI:10.1074/jbc.M113.459768

Defects in the human protoporphyrinogen oxidase (hPPO) gene, resulting in ～ 50% decreased activity of hPPO, is responsible for the dominantly inherited disorder variegate porphyria (VP). To understand the molecular mechanism of VP, we employed the sitedirected mutagenesis, biochemical assays, structural biology, and molecular dynamics simulation studies to investigate VP-causing hPPO mutants. We report here the crystal structures of R59Q and R59G mutants in complex with acifluorfen at a resolution of 2.6 and 2.8 A. The r.m.s.d. of the Cα atoms of the active site structure of R59G and R59Q with respect to the wild-type was 0.20 and 0.15 A, respectively. However, these highly similar static crystal structures of mutants with the wild-type could not quantitatively explain the observed large differences in their enzymatic activity. To understand how the hPPO mutations affect their catalytic activities, we combined molecular dynamics simulation and statistical analysis to quantitatively understand the molecular mechanism of VP-causing mutants. We have found that the probability of the privileged conformations of hPPO can be correlated very well with the k_cat/K_m of PPO (correlation coefficient, R² > 0.9), and the catalytic activity of 44 clinically reported VP-causing mutants can be accurately predicted. These results indicated that the VP-causing mutation affect the catalytic activity of hPPO by affecting the ability of hPPO to sample the privileged conformations. The current work, together with our previous crystal structure study on the wild-type hPPO, provided the quantitative structural insight into human variegate porphyria disease.

Full text of DOI:10.1074/jbc.M113.459768

THE JOURNAL OF BIOLOGICAL CHEMISTRY VOL. 288, NO. 17, pp. 11731–11740, April 26, 2013
© 2013 by The American Society for Biochemistry and Molecular Biology, Inc. Published in the U.S.A.
Quantitative Structural Insight into Human Variegate
□
S
Porphyria Disease*
Received for publication, February 5, 2013, and in revised form, February 18, 2013 Published, JBC Papers in Press, March 6, 2013, DOI 10.1074/jbc.M113.459768
Baifan Wang‡1, Xin Wen‡1, Xiaohong Qin§, Zhifang Wang‡, Ying Tan‡, Yuequan Shen§, and Zhen Xi‡2
From the ‡State Key Laboratory of Elemento-Organic Chemistry, Department of Chemical Biology, College of Chemistry, Nankai
University, Tianjin 300071, China and the §College of Life Science, Nankai University, Tianjin 300071, China
Background: Defects in the human protoporphyrinogen oxidase (PPO) causes the variegate porphyria (VP) disease.
Results: The activity of 44 clinically reported VP-causing mutants have been accurately predicted.
Conclusion: A quantitative understanding into the molecular basis of VP by PPO mutation was established.
Significance: The quantitative insight into VP should be helpful for the diagnosis, precaution, and treatment of this disease.
Defects in the human protoporphyrinogen oxidase (hPPO)
gene, resulting in ϳ50% decreased activity of hPPO, is responsible
for the dominantly inherited disorder variegate porphyria (VP). To
understand the molecular mechanism of VP, we employed the site-
directed mutagenesis, biochemical assays, structural biology, and
molecular dynamics simulation studies to investigate VP-causing
hPPO mutants. We report here the crystal structures of R59Q and
R59G mutants in complex with acifluorfen at a resolution of 2.6
catalyzes the oxidation of protoporphyrinogen IX (protogen) to
protoporphyrin IX (porphyrin) in the presence of cofactor FAD
and molecular oxygen (Fig. 1) (2–4). In humans, defects in the
PPO gene, resulting in ϳ50% decreased activity of PPO, is
responsible for the dominantly inherited disorder variegate
porphyria (VP) (5–8). VP is a type of acute hepaticporphyria
(9–11), which is characterized by an abnormal pattern of por-
phyrin excretion. VP has been found worldwide (12–15) and is
particularly prevalent in the white population of South Africa
(ϳ3 in 1000), especially VP caused by the R59W founder muta-
tion (16, 17).
˚
and2.8A. Ther.m.s.d. oftheC␣atomsoftheactivesitestructureof
˚
R59G and R59Q with respect to the wild-type was 0.20 and 0.15 A,
respectively. However, these highly similar static crystal structures
of mutants with the wild-type could not quantitatively explain the
observed large differences in their enzymatic activity. To under-
stand how the hPPO mutations affect their catalytic activities, we
combined molecular dynamics simulation and statistical analysis
to quantitatively understand the molecular mechanism of
VP-causing mutants. We have found that the probability of the
privileged conformations of hPPO can be correlated very well with
the kcat/Km of PPO (correlation coefficient, R2 > 0.9), and the cat-
alytic activity of 44 clinically reported VP-causing mutants can be
accurately predicted. These results indicated that the VP-causing
mutation affect the catalytic activity of hPPO by affecting the abil-
ity of hPPO to sample the privileged conformations. The current
work, together with our previous crystal structure study on the
wild-type hPPO, provided the quantitative structural insight into
human variegate porphyria disease.
Inhibition of PPO in plants leads the accumulation of proto-
gen, which exports to the cytoplasm and forms porphyrin
through nonenzymatic oxidation. The photosensitizing por-
phyrin can lead to singlet oxygen, which can cause peroxidation
of membrane lipids and cell death (18, 19). In human, because
the deficiency of PPO leads to the tissue accumulation and
excessive excretion of porphyrin, it is hypothesized that the
sensitivity of VP patients to light should be similar to the con-
dition in plants (20, 21).
Though the study of VP has been performed for more than
half a century (8, 17, 21, 22), the detailed molecular mechanism
of VP is still unclear. To address this important issue, we have
resolved the crystal structure of human PPO in a resolution of
1.9 Å and characterized 44 VP-causing mutations in vitro (22).
Based on this high-resolution structure of hPPO and the kinetic
data, we attempted to explain the defects of 44 missense
mutants. The mapping of these 44 mutations on the hPPO crys-
tal structure indicated these mutants distributed on all of the
three structure domains of hPPO. However, our understanding
of the molecular mechanism of VP-causing mutants was lim-
ited because our insights mostly depend on structural analysis
and in silico docking (22); the detailed information of molecular
motion on substrate binding was especially lacking. In this
work, the site-directed mutagenesis, biochemical assays, struc-
tural biology, and molecular dynamics simulation studies have
been carried out to understand molecular mechanism of VP-
causing mutants. We report here the crystal structures of R59Q
and R59G mutants in complex with acifluorfen at a resolution
of 2.6 and 2.8 Å. However, these highly similar static crystal
structures of mutants with the wild-type could not quantita-
tively explain the observed large differences in their enzymatic
Protoporphyrinogen oxidase (PPO)3 (EC 1.3.3.4) is the
penultimate enzyme in the heme biosynthetic pathway (1) and
* ThisworkwassupportedbyMinistryofScienceandTechnologyofthePeople’s
Republic of China Grants 2010CB126102 and 2011BAE06B05 and National
Natural Science Foundation of China Grants 20932005 and 21172122.
The atomic coordinates and structure factors (codes 4IVO and 4IVM) have been
deposited in the Protein Data Bank (http://wwpdb.org/).
□
S
This article contains supplemental Tables S1–S7 and Figs. S1–S7.
1 Both authors contributed equally to this work.
2 To whom correspondence should be addressed: State Key Laboratory of
Elemento-Organic Chemistry, Dept. of Chemical Biology, College of Chemis-
try, Nankai University, No. 94, Weijin Rd., Tianjin, China. Tel.: 86-022-23504782;
Fax: 86-022-23504782; E-mail: zhenxi@nankai.edu.cn.
3 The abbreviations used are: PPO, protoporphyrinogen IX oxidase; MD,
molecular dynamics; VP, variegate porphyria; protogen, protoporphyrino-
gen IX; CPDF, conformation probability density function; PC, privileged
conformations; r.m.s.d., root mean square deviation.
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Quantitative Insight into Variegate Porphyria
FIGURE 1. Protoporphyrinogen IX oxidase reaction.
activity. We further combined molecular dynamics simulation phyrin IX from protoporphyrinogen IX using a 96-well plate
and statistical analysis to quantitatively understand the molec-
ular mechanism of VP-causing mutants. We have found that
the VP-causing mutations affect the catalytic activity of hPPO
by affecting the ability to sample privileged conformations. The
effects of 44 clinically important mutations on the catalytic
activity of hPPO have been accurately predicted with R2 ϭ 0.94
in this work.
with the continuous fluorometric methods at 25 °C (23–25).
The product has a maximum excitation wavelength at 410 nm
and a maximum emission wavelength at 630 nm. The total vol-
ume of the reaction mixture was 200 ␮l consisting of 0.1 M
potassium phosphate buffer (pH 7.4), 5 ␮M FAD, 5 mM DTT, 1
mM EDTA, 0.2 M imidazole, and 0.03% Tween 80 (v/v). The
enzymatic reaction was started by the addition of substrate.
The autoxidation rates were determined concomitantly and
were subsequently subtracted. Kinetic parameters, including
the Michaelis-Menten constant (Km), the maximal velocity
(Vmax), and the catalytic constant (kcat), were determined by a
Lineweaver-Burk plot.
EXPERIMENTAL PROCEDURES
Plasmid Construction of hPPO Mutants—The recombinant
plasmid (pHPPO-X) was a generous gift from Dr. H. A. Dailey
(University of Georgia). All mutations of hPPO described here
were generated from the recombinant plasmid (pHPPO-X)
using DpnI-mediated site-directed mutagenesis methods and
confirmed by DNA sequencing.
Crystallization and Data Collection—Crystals of the mutant
hPPOsꢀacifluorfen complexes were grown using the same
method as the wild-type protein described previously (22). Dif-
fraction data were collected on beam station BL17U1 of the
Shanghai Synchrotron Radiation Facility. The data of R59Q and
R59G were processed and scaled to 2.6 and 2.8 Å, respectively,
using the HKL2000 software package (26). The crystals of the
complex of mutant hPPO with acifluorfen belong to the space
group R3.
Expression and Purification of Mutant hPPO—Plasmids of
wild-type and various hPPO mutants were initially transformed
into BL21(DE3)pLysS Escherichia coli cells. The single colony
of resulting cells was grown in 10 ml of 2ϫYT medium with 100
␮g/ml ampicillin at 37 °C overnight. Total culture were then
inoculated into one liter of 2ϫYT medium containing 100
␮g/ml ampicillin and grown with shaking at 37 °C to A600 of 0.6.
The expression of the recombinant hPPO wild-type enzyme
and its mutants were induced by adding isopropyl 1-thio-␤-D-
galactopyranoside to a final concentration of 1 mM. Cells were
grown for an additional 4 h at 25 °C.
Structure Determination and Refinement—The initial phases
were obtained by molecular replacement using the structure of
PPO enzyme from Homo sapiens (Protein Data Bank code
3NKS (22)) as a template. The program PHASER was able to
locate one molecule in the asymmetric unit (27). The models
were built manually using the program COOT (28) and refined
using the program CNS (29) and Phenix. The final structure of
R59Q mutant had an Rcryst value of 17.9% and an Rfree value of
24.3%. The Ramachandran plot calculated by the program
PROCHECK (30) showed that 90.3% of the residues were in
their most favored regions, 9.7% of the residues were in addi-
tionally allowed regions, and no residues were in generously
allowed regions and disallowed regions. The structure of R59G
mutant had an Rcryst value of 17.5% and an Rfree value of 24.4%.
The Ramachandran plot calculated by the program PRO-
CHECK (30) showed that 89.2% of the residues were in their
most favored regions, 10.5% of the residues were in additionally
allowed regions, 0.3% of the residues were in generously
allowed regions, and no residues disallowed regions. Detailed
data collection and refinement statistics are summarized in
supplemental Table S1.
E. coli cells were harvested by centrifugation at 5000 ϫ g for
15 min, and the cell pellet was suspended in lysis buffer (20 mM
Tris-HCl, pH 8.0, 500 mM NaCl, 10 mM imidazole, 0.5% Triton
X-100 (v/v), and 10% glycerol) and disrupted by sonication and
lysozyme (0.1 mg/ml). Cellular debris was removed by centrif-
ugation at 20,000 ϫ g for 50 min. The supernatant was loaded
directly onto a Ni2ϩ nitrilotriacetic acid column, which was
pre-equilibrated in lysis buffer, and left at 4 °C for 2 h. The Ni2ϩ
nitrilotriacetic acid column was then washed with four column
volumes of wash buffer (50 mM NaH2PO4 (pH 7.0), 100 mM
NaCl, 50 mM imidazole, 0.03% Triton X-100 (v/v) and 10% glyc-
erol). Proteins were eluted with three column volumes of elu-
tion buffer (50 mM NaH2PO4 (pH 7.0), 100 mM NaCl, 200 mM
imidazole, 0.03% Triton X-100 (v/v), and 10% glycerol). The
eluted proteins were concentrated to 2.5 ml and loaded onto
Superdexs200 size-exclusion column (GE Healthcare) with
running buffer (20 mM Tris-HCl, pH 7.0, 200 mM NaCl, 5 mM
DTT, 5 mM EDTA, and 0.02% Tween 80 (v/v) (Anatrace)) at a
flow rate of 0.3 ml/min. Protein concentration was determined
using Bradford method (Bio-Rad).
Molecular Dynamics Simulations—MD simulations for wild-
type and mutant hPPO in complexes with substrate protogen
were carried out to generate the equilibrium conformations for
each of the studied systems. The crystal structures of the wild-
Enzyme Assay for Kinetic Analysis—PPO activity was assayed
by measuring the constant velocity of formation of protopor- type hPPO (Protein Data Bank code 3NKS (22)) and R59G and
11732 JOURNAL OF BIOLOGICAL CHEMISTRY
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Quantitative Insight into Variegate Porphyria
eters were used to describe the reactant conformational space.
Each conformation of the reactants was represented by a pair of
D
C5-N5-AC5-N5-N10. For each of the studied systems, conforma-
tional ensemble of the reactants was represented by a set of
D
C5-N5-AC5-N5-N10 pairs, corresponding to a set of discrete data
points in a DC5-N5-AC5-N5-N10 plane.
Construction of Conformation Probability Density Function
(CPDF)—To calculate the probability of the reactant conforma-
tion in any given interval of DC5-N5 and AC5-N5-N10, for each of
the studied systems, we converted the sets of discrete data
points of DC5-N5-AC5-N5-N10 pairs to the CPDF, denoted as
Z(A,D). The conversion was performed in the following steps:
(i) dividing the DC5-N5-AC5-N5-N10 plane into square bins with
0.1 Å width and 5° length; (ii) taking count of the number of data
points for each bin; (iii) calculating the density of each bin by
FIGURE 2. A schematic description of the DC5-N5 and AC5-N5-N10 used as a
set of geometry parameters to represent the conformation of reactants
protogen and FAD. FAD was shown on the isoalloxazine plane only.
R59Q mutants were taken as the starting point for MD simula- the number of DC5-N5-AC5-N5-N10 data points fall in the corre-
tions of the complexes. All missing residues of the structure sponding bin being divided by the total number of the angle-
were added using InsightII (Accelrys, Inc., San Diego, CA). The distance data points; (iv) fitting the data with the two-dimen-
hydrogen atoms were added to hPPO structure using leap mod- sional Gaussian function to construct Z(A,D) by the non-linear
ule of AMBER (version 9) (31). The structures of other hPPO surface fitting methods implemented in Origin Lab (version
mutants were generated from the structure by mutation of cor- 8.0, Northampton, MA). The general form of the CPDF can be
responding residues using InsightII (Accelrys, Inc.). A 3000- presented as follows in Equation 1,
step minimization was performed on the mutated residues and
2
2
1 A Ϫ ␮
1 D Ϫ ␮
D
the adjacent residues within 4.0 Å from the mutated residue to
remove the steric clash. The optimization were performed with
SANDER module of AMBER (version 9) (31) and AMBER (ver-
sion 03) force fields (32, 33).
A
Z͑ A,D͒ ϭ Cexp
Ϫ
Ϫ
(Eq. 1)
ͩ ͪ ͩ ͪ
ͭ
ͮ
2
␴
2
␴
D
A
where Z denotes the conformation probability density in
DC5-N5 and AC5-N5-N10 for the observing systems. The factor C
The coordinates of protogen were taken from the previous
docking studies where protogen was docked into the crystal in this expression ensures that the total area under the curve
structure of hPPO (22). The force field parameters of cofactor Z(A,D) is equal to one. The parameter ␮ is called the mean of
FAD and protogen were generated with the Gaussian 03 (34) the normal distribution, and it determines the coordinate of
and AMBER (version 9).
highest point of the Gaussian surface. The parameter ␴ is called
Each of the complex systems was immersed in a truncated the S.D. and describes how concentrated the distribution is
octahedral box of explicit TIP3P water molecules and was neu- around its mean.
Ϫ
ϩ
tralized by adding counter ions (Cl or Na ). All MD simula-
Calculation of the Probability of PC—The probability of any
tions were carried out with the SANDER module of AMBER conformation of the reactants at equilibrium was calculated by
(version 9) (31). Prior to MD simulations, the molecular sys- taking the integral of the CPDF over the given integration inter-
tems were subjected to a series of energy minimizations to relax vals. Based on the x-ray structures of the flavoenzyme com-
the system. In MD simulations, particle mesh Ewald (35) and plexes with substrate analogues (38), we defined the conforma-
periodic boundary condition were employed to deal with the tions with DC5-N5 within 3.0–3.8 Å and AC5-N5-N10 within
long range electrostatic interactions. The SHAKE method (36) 96–117° as the privileged conformations (PC). For each studied
was used to constrain bonds involving hydrogen atoms to tol- system, the probability of PC, denoted PPC, was calculated by
erate 2-fs time steps. The system was gradually heated from 0 to the bivariate integration of corresponding CPDF over the inter-
300 K over 50 ps. Equilibrating calculation was executed at 1 val (96, 117) for AC5-N5-N10, and (3.0, 3.8) for DC5-N5 (Equation
atm and at 300 K for 50 ps. Then, 5-ns MD simulations were 2) using Matlab software (The Math Works, Natick, MA). The
performed under 300 K and 1 atm. The snapshot of the system general integral form was expressed as follows,
was taken every 1 ps. Trajectories of reactants protogen and
2
2
A1 D1
FAD after the initial 2 ns of equilibration were considered for
analysis; thus, 3000 MD structures, collected during the time
period of 2001–5000 ps, were generated for each of the systems
using the ptraj module of AMBER (version 9). To test the con-
sistency of data from MD simulations, the simulation of wild-
type hPPO system was extended to 44 ns.
1 A Ϫ ␮
1 D Ϫ ␮
A
D
P
PC ϭ
Cexp
Ϫ
Ϫ
dAdD
ͩ ͪ ͩ ͪ
ͭ
ͮ
͵ ͵
2
␴
2
␴
D
A
A2 D2
(Eq. 2)
Correlation of the PPC with the kcat/Km of PPO Mutants—
Description of the Conformational Space of the Reactants— Nonlinear regression analyses were performed in Origin Lab
Based on the proposed PPO catalytic mechanism (4, 37) and (version 8.0) to explore whether the PPC for the studied systems
our previous study (22), the distance between C5 atom of pro- could be correlated with corresponding kcat/Km values. Best
togen and N5 atom of FAD (DC5-N5) and the angle between C5, fitting was assessed by correlation coefficient, square root of
N5 and N10 (AC5-N5-N10) (shown in Fig. 2) as geometry param- mean square error, and F-test comparisons.
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Quantitative Insight into Variegate Porphyria
FIGURE 3. Comparison of the crystal structures and activities of the wild-type hPPO and R59Q and R59G mutants. A, comparison of the overall (left panel)
and active site (right panel) of the wild-type and R59Q mutant structure. B, comparison of the overall (left panel) and active site (right panel) of the wild-type and
R59G mutant structure. Wild-type is shown in white, R59Q is shown in green, and R59G is shown in salmon. C, kinetic data and crystal structural deviation for
wild-type hPPO and Arg-59 mutants.
Accession Codes—Coordinates and associated structure fac- minor structural change in the active site residues. The r.m.s.d.
tors of solved structures for human protoporphyrinogen IX
oxidase R59Q and R59G mutants in complex with acifluorfen
have been deposited in the Protein Data Bank (codes 4IVO and
4IVM, respectively).
of the active site residues (residues within 4.0 Å distance with
acifluorfen) of R59Q and R59G mutants with wild-type was
0.20 and 0.15 Å, respectively. In addition, after being subjected
to the molecular dynamics simulation with bound substrate,
the r.m.s.d. of the active site residues of R59Q and R59G
mutants with wild-type was 0.27 and 0.39 Å, respectively. These
data suggested that the static active site architecture was not
significantly affected by the mutations (Fig. 3, A and B). These
highly similar static crystal structures of mutants with the wild-
type could not quantitatively explain the observed large differ-
ences in their enzymatic activity (Fig. 3C). To answer the ques-
tion how the hPPO mutations affect their catalytic activities,
the dynamics motion of the structure of hPPO mutants should
be considered.
RESULTS AND DISCUSSION
Crystal Structure of R59Q and R59G Mutant—The R59W
mutation is by far the most prevalent VP-causing mutation
identified, and Ͼ94% of the patients in South Africa carry this
mutation (16, 17). Biochemical studied showed that the R59W
mutation dramatically decreased the catalytic constant of
hPPO in vitro (17, 21, 41, 42). Herein, we have determined the
crystal structures of R59Q and R59G mutants in complex with
acifluorfen at a resolution of 2.6 and 2.8 Å, respectively, with 1
molecule/asymmetric unit. Data collection and refinement sta-
tistics appear in supplemental Table S1.
Conformational Distribution of the Reactants—Dynamics
simulation methods are widely used to obtain information on
the time evolution of conformations of proteins and other bio-
Overall, the structures of R59Q, R59G, and wild-type hPPO
were highly similar, with r.m.s.d. in C␣ positions of 0.26 and
0.29 Å, respectively (Fig. 3, A and B). The mutation caused logical macromolecules, which present a powerful complement
11734 JOURNAL OF BIOLOGICAL CHEMISTRY
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Quantitative Insight into Variegate Porphyria
FIGURE 4. Conformation probability analysis of the PPO mutants. A, A total of 17 mutants listed at left column were used to construct the prediction model,
and four mutants shown at the right column were the mutants constructed and measured later as the initial test set. The mutated residues, the cofactor FAD,
and the substrate protogen were shown in stick representation with gray, cyan, and green carbon atoms, respectively. B, DC5-N5 versus AC5-N5-N10 scatter plots.
The distribution of the pairs of DC5-N5-AC5-N5-N10 for wild-type hPPO from MD simulation was shown in blue, and the distributions for the mutants were shown
in red. C, probability distribution of DC5-N5 observed for wild-type hPPO. Horizontal coordinates indicate DC5-N5 value; vertical coordinates indicate probability
density. D, probability distribution of AC5-N5-N10 observed for wild-type hPPO. Horizontal coordinates indicate AC5-N5-N10 value; vertical coordinates indicate
probability density. E, conformation probability density function surface for wild-type hPPO.
to static structures of proteins and other biomolecules. Conver- were shown in supplemental Fig. S1. Other detailed data about
gence of results from simulation with experimental data pro- the MD trajectories of studied systems were provided in sup-
vides a foundation for using simulations to enhance experimen- plemental Figs. S2 and S3 and supplemental Table S2).
tal observations and study features of biomolecules that cannot
It was essential to describe conformational space of the reac-
be seen directly in experiments. Because it was difficult to study tants using a set of proper parameters for capturing the salient
the effect of the mutants only from the comparison of the crys- features of conformational distribution of the reactants at equi-
tal structures of wild-type and mutant hPPO, we have therefore librium system. The oxidation of protogen to protoporphyrin
chosen to study the molecular mechanism of how VP-causing IX catalyzed by PPO involves the rupture of C-H bond of meth-
mutants affect the activity of hPPO through molecular dynam- ylene of macrocycle in protogen, coupled to the transfer of two
ics simulations of the hPPOꢀsubstrate complex. First, we chose electrons to FAD (4). The carbon atoms involved in these C-H
wild-type hPPO and 16 hPPO mutants (including the R59G and bonds were considered as the sites of oxidative attack, and N5 of
R59Q mutants) as the studied systems (Fig. 4A), because all of the tricyclic isoalloxazine ring system of FAD was believed to
these mutations are involved in the binding of substrate or FAD take part directly in substrate dehydrogenation (37, 43–45).
and clinically found in the VP patients (7, 9–11). MD simula- In the previous studies, we also explored the binding mode of
tions for the 17 enzymes in complexes with substrate protogen protogen at the active site of hPPO based on the high-resolu-
were carried using AMBER (version 9) (31). For each of the tion crystal structure of hPPO by the molecular docking, MD
studied system, 3000 conformers extracted from the MD tra- simulation, and quantum mechanical calculations. Our studies
jectory during the time period of 2001–5000 ps were used as the indicated that the methylene bridge C5 atom of protogen (see
reduced representation of the conformational ensemble at Fig. 2) was close to the N5 atom of FAD (22). Thus, the distance
equilibrium state.
between C5 and N5 atoms (DC5-N5) and the angle between C5,
For each studied system, the fluctuations of temperature, N5, and N10 (AC5-N5-N10) (shown in Fig. 2) as a set of geometry
density, and total energy during the MD simulation were exam- parameters were used to describe the conformational space in
ined, and the r.m.s.d. of the backbone heavy atoms with respect the reaction process. In conformational ensembles, each con-
to the starting structures were reported as a function of time. formation of the reactants (protogen and FAD) was repre-
These physical quantities from the wild-type hPPO system sented by a pair of DC5-N5-AC5-N5-N10, whereas each conforma-
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Quantitative Insight into Variegate Porphyria
TABLE 1
The parameters of the conformation probability density functions, the kinetic data, and the PPC for each of the studied systems
a
Enzyme
R2
C
␮
␴
␮
␴
D
Km
␮M
kcat
min
k
cat/Km
k
cat/Km(pred)
PPC
A
A
D
Ϫ1
Ϫ1
Ϫ1
Ϫ1
Ϫ1
min ␮M
min ␮M
Wild-type
V347A
F331A
M368A
G169A
L334A
R97D
0.92
0.97
0.96
0.95
0.99
0.98
0.94
0.98
0.96
0.97
0.94
0.94
0.98
0.95
0.98
0.95
0.97
0.12
0.12
0.10
0.08
0.11
0.11
0.07
0.10
0.12
0.09
0.04
0.08
0.12
0.11
0.14
0.08
0.09
113.33
114.53
115.13
102.67
117.12
126.00
126.11
124.75
126.48
121.80
111.45
124.51
119.46
120.23
121.51
119.63
129.85
7.16
6.39
6.95
8.82
7.16
7.62
8.65
8.69
8.23
8.06
8.34
7.14
7.23
8.00
7.15
6.92
7.07
3.41
3.60
3.56
3.67
3.55
3.39
3.65
3.30
3.30
3.50
3.99
3.63
3.42
3.34
3.32
3.96
3.64
0.19
0.20
0.23
0.21
0.20
0.18
0.27
0.19
0.17
0.21
0.44
0.28
0.18
0.19
0.16
0.28
0.26
2.33
2.61
3.41
3.16
5.26
3.93
7.79
3.87
3.09
3.31
13.30
4.21
6.79
6.79
8.13
11.82
1.10
6.14
3.70
4.44
3.95
5.02
1.40
2.35
0.99
0.65
2.48
3.69
0.74
0.95
0.75
0.76
0.71
0.06
2.63
1.42
1.30
1.25
0.95
0.36
0.30
0.26
0.21
0.75
0.28
0.18
0.14
0.11
0.09
0.06
0.05
2.46
0.66
0.54
0.51
0.53
0.44
0.12
0.11
0.18
0.12
0.25
0.23
0.10
0.36
0.33
0.26
0.10
0.02
1.33
1.31
1.36
0.74
0.09
0.07
0.18
0.12
0.27
0.26
0.11
0.52
0.43
0.27
0.07
0.01
G453R
D349A
R59G
R59Q
R59W
L401F
L166N
G330R
R168H
V335G
a
kcat/Km value was predicted by Equation 3.
tional ensemble of the reactants was represented by a set of Considering that both of distribution of DC5-N5 and AC5-N5-N10
C5-N5-AC5-N5-N10 pairs, corresponding to a set of discrete data for each studied system followed Gaussian distribution, we fit-
points in a DC5-N5-AC5-N5-N10 plane. ted the binned data of DC5-N5-AC5-N5-N10 to a two-dimensional
D
In Fig. 4B, the DC5-N5-AC5-N5-N10 pairs as data points were Gaussian distribution using a nonlinear regression imple-
plotted in a DC5-N5-AC5-N5-N10 plane, in which each of the scat- mented in Origin Lab (version 8.0). For all of the 17 studied
ter plots for the mutants was superposed on the one for wild- systems, they were well approximated by Gaussian distribu-
type system to compare the conformational spaces of the reac- tions (Equation 1), and the best estimates of the mean and
tants of wild-type hPPO and mutants. The DC5-N5 versus standard deviation obtained from the fitting procedures for
A
C5-N5-N10 scatter plots for the mutants were provided in sup- each of studied systems were reported in Table 1. The CPDF
plemental Fig. S4. The ranges of DC5-N5 and AC5-N5-N10 and the surface for the wild-type and mutant hPPO were displayed in
average of the two values for each conformational ensemble Fig. 4E and supplemental Fig. S6.
were listed in supplemental Table S3.
The Probability of the PC—Based on the x-ray crystal struc-
From the pairs of DC5-N5-AC5-N5-N10 scatter plots, we tures of the flavoenzyme complexes with substrate analogues,
obtained the qualitative understanding of the conformational Fraaije and Mattevi (38) have studied the catalytic features of
distribution for each of the studied system. As seen in Fig. 4B the flavoenzymes that perform a dehydrogenation reaction.
and supplemental Table S3, despite the fact that the wild-type, The studies indicated that the geometry parameters between
V347A, and F331A system had similar regions where the data substrate and FAD corresponding to the distance DC5-N5 and
points appeared, the data pattern was different for other stud- the angle AC5-N5-N10 of hPPO were generally conserved for the
ied systems. The studied systems with higher catalytic effi- studied flavoenzymes, within 3.0–3.8 Å for DC5-N5, 96 to 117°
ciency, for example, wild-type hPPO and F331A, showed for AC5-N5-N10. Therefore, we defined the conformations with
more condensed data distribution than that of the systems with both of DC5-N5 within 3.0–3.8 Å and AC5-N5-N10 within
lower catalytic efficiency. The results suggested that the cata- 96–117° as the PC. In fact, there is widely accepted proposition
lytic efficiency may be related to the conformational distribu- that the reactant particles must collide with appropriate orien-
tion of reactants for our studied systems.
tations to achieve an enzymatic reaction, and enzymes bind to
As an estimate of the probability distribution of a continuous their substrates for the formation of a substrateꢀenzyme com-
variable, the histograms of probability of DC5-N5 and AC5-N5-N10 plex prior to the reaction step. Here, we quantify the appropri-
were investigated for each of the studied systems. Of these, the ate orientation collision probability between the reactants as
histograms for the wild-type hPPO, as an example, were dis- the PPC, which was obtained by the bivariate integration of the
played in Fig. 4, C and D, in which a bell-shaped probability CPDF over the reactable geometry ranges. Such a quantitation
distributions were observed for both of DC5-N5 and AC5-N5-N10
The same behaviors were also observed in all of the mutants.
.
may correlate with the catalytic activity of enzymes.
For each of 17 studied systems, the probability of reactant
For all of the studied systems, the probability distributions of conformation in any given interval of DC5-N5 and AC5-N5-N10
DC5-N5 and AC5-N5-N10 were well approximated by Gaussian can be calculated through the corresponding CPDF. Thus, PPC
distributions, with R2 of 0.95–0.99 for DC5-N5, and 0.99 for was calculated by the bivariate integration of the corresponding
A
C5-N5-N10, respectively (supplemental Table S4 and supple- CPDF over the interval (96, 117) for AC5-N5-N10, and (3.0, 3.8)
mental Fig. S5).
for DC5-N5 using Matlab software (supplemental Fig. S7). PPC
The scattered DC5-N5-AC5-N5-N10 data were converted for for each of the studied systems were listed in Table 1. The
each of the studied systems to a continuous function of random kinetic parameters of the wild-type hPPO and 16 mutants were
variables DC5-N5 and AC5-N5-N10, ⌮(DC5-N5, AC5-N5-N10), also listed in Table 1. It can be found that PPC of each studied
namely the CPDF, by two-dimensional histogram technique. system goes the same trend with the kcat/Km of enzyme
11736 JOURNAL OF BIOLOGICAL CHEMISTRY
VOLUME 288•NUMBER 17•APRIL 26, 2013

Quantitative Insight into Variegate Porphyria
mutants, which is in keeping with our first hypothesis that the
probability of the appropriate orientated collision between the
reactants should correlate with the catalytic activity of
enzymes.
Correlation of the Probability of PC with the Catalytic Effi-
ciency of the Enzymes—The kcat/Km values of 17 studied sys-
tems were plotted against the corresponding PPC values. Upon
inspection of Fig. 5A, we found that the PPC increased with a
nonlinear increasing of the kcat/Km. Thus, the paired data were
fitted to BoxLucas1 functions, and the best fit was assessed by
square root of mean square error values and F-test comparisons
in Origin Lab (version 8.0). Finally, the correlation equation
with R2 ϭ 0.90, square root of mean square error ϭ 0.22, and
F ϭ 140.82 was expressed as follows in Equation 3.
kcat͞KM ϭ 0.11͑e4.84P Ϫ 1͒
(Eq. 3)
PC
The predicted values of the kcat/Km from this regression were
listed in Table 1. The experimental kcat/Km values are plotted
against the predicted kcat/Km in Fig. 5B with correlation R2 ϭ
0.91. The relatively high R2 between the experimental and pre-
dicted kcat/Km indicated that a high proportion of the data can
be explained by Equation 3. Thus, these mutants affect the cat-
alytic activity of hPPO by affecting the PPC. Four more mutants
such as F331T, L334T, R59C, and V347T have thus been con-
structed, and kinetics have been measured to test our model.
Their experimental kcat/Km values again correlated very well
with the calculated values (Fig. 5C and supplemental Table S5),
which further indicated that the probability of the privileged
conformations in the PPO-catalyzed reaction process made the
major contribution. Encouraged by these results, we decided to
use this computational approach to predict the catalytic activ-
ities of all clinically reported VP-causing mutants.
The Molecular Mechanism of the VP-causing Mutants—The
mapping of these 44 VP-causing mutants on the hPPO crystal
structure indicated these mutants distributed on all of the three
structure domains of hPPO (Fig. 6A). We categorized these
mutants into five potential categories, i.e. affecting the sub-
strate binding, FAD binding, hydrophobic core, secondary
structure, and surface of hPPO. However, our understanding of
the molecular mechanism of VP-causing mutants was limited
because our insights mostly depend on the static structural
analysis and in silico docking. In this work, based on molecular
dynamics simulation and statistical analysis, we found the pos-
itive correlation of the PPC with kcat/Km of the 17 PPO variants.
We set out to further test whether the VP-causing mutants
affect the catalytic activity of hPPO by affecting the distribution
of PC. Among the 44 mutants, 36 mutants display detectable
activity, whereas eight mutants were inactive. (The catalytic
activity of the inactive mutants was designated as zero.) The
FIGURE 5. Correlating the probability of PC with the catalytic efficiency of
enzymes. A, plot of the experimental values of kcat/Km values versus the cor-
responding PPC for the 17 studied systems, the exponential correlation was
shown as a red line with the R2 of 0.90. B, plot of the experimental and pre-
dicted kcat/Km for all studied systems from the Equation 3. Black squares indi-
cate 17 studied systems that were used to generate the Equation 3; red dot
indicates four mutants for experimental validation. The diagonal red line cor-
responding to (kcat/Km)exp ϭ (kcat/Km)pred was provided for visual guidance
with the R2 of 0.91. C, comparison of the experimental (in blue) and predicted
(in red) kcat/Km value for the test mutants of hPPO.
k
cat/Km values of these mutations were then predicted using the
Equation 3, and the data were listed in supplemental Table S4.
Fig. 6B depicts a correlation plot of the predicted and experi-
mental kcat/Km values, in which the correlation coefficient (R2)
is 0.94.
Because the quantitative correlation between experimental
k
cat/Km and the computational PPC could be established, we can
therefore assess the molecular mechanism of the VP disease by
APRIL 26, 2013•VOLUME 288•NUMBER 17
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Quantitative Insight into Variegate Porphyria
FIGURE6. Predictionof thecatalyticactivityandmolecular mechanism of VP-causing mutants. A, themapping of theVP-causingmutationsonthe crystal
structure of hPPO. Mutants are indicated by colored spheres, substrate and FAD are shown in stick representation. B, plot of the experimental and predicted
k
cat/Km for the clinically reported or potential VP-causing mutants from the Equation 3. The data points are colored by their effects on the activity of hPPO. The
diagonal red line corresponding to (kcat/Km)exp ϭ (kcat/Km)pred, the correlation showed R2 ϭ 0.94. C, the average conformation of the active site from dynamics
simulation for the wild-type. D, the average conformation of the active site from dynamics simulation for R59Q. E, the average conformation of the active site
from dynamics simulation for R59G.
FIGURE 7. Prenzyme: a protocol for predicting mutant enzyme properties through MD/conformational distribution statistical analysis.
VP-causing mutants from dynamics simulation. Based on our age distance increased to 5.43 Å (Fig. 6, C and D), which indi-
molecular dynamics simulation and statistical analysis, we cated that the stacking interaction between Pro-58 and FAD is
found that the VP-causing mutations, even those far from the disrupted in the reaction process by the mutation. In the
active site and FAD could significantly impact the PPC of hPPO. dynamics simulation of R59G mutants, the average r.m.s.d. of
These mutations lead to the changes of structural and confor- 1.24 Å for the loop of Leu-56–Ile-61 of R59G respect to wild-
mational motions of the entire hPPO that alter the ability of type (higher than the overall structure r.m.s.d., 0.78 Å) indi-
sampling privileged conformations, thereby affecting the cata- cated that the loop of Leu-56–Ile-61 undergo a large structural
lytic activity of hPPO. Now we can quantitatively understand motion compared with the wild-type in the reaction process
how the catalytic activities were affected by hPPO mutations, a (Fig. 6, C and E). Because this loop locates above the isoalloxa-
result cannot come out of the static crystal structure of hPPO zine ring of FAD, the structural motion of this loop should
mutants.
affect the binding of the isoalloxazine ring of FAD and therefore
From dynamics simulation, it could be seen that in the wild- affect the activity of PPO. The detailed information from
type, the side chain of Pro-58 is stacking with the isoalloxazine molecular dynamics study about the effects of the clinically
ring of FAD, and the average distance of all simulated ternary reported mutations on enzymatic activity were provided in sup-
conformations between the side chain center of Pro-58 and the plemental Table S7. These data indicated that the VP-causing
center of ring B of isoalloxazine ring of FAD was kept at ϳ3.98 mutations affect the catalytic activity of hPPO by affecting the
Å during the simulation. While in the R59Q mutant, the aver- ability to sample privileged conformations, which is in accord-
11738 JOURNAL OF BIOLOGICAL CHEMISTRY
VOLUME 288•NUMBER 17•APRIL 26, 2013

Quantitative Insight into Variegate Porphyria
Tavazzi, D., Nascimbeni, F., Ferrari, M. C., Rocchi, E., and Cappellini,
M. D. (2009) Clinical, biochemical and genetic characteristics of variegate
porphyria in Italy. Cell. Mol. Biol. 55, 79–88
ance with the widely accepted proposition that the reactant
particles must collide with appropriate orientations to achieve
an enzymatic reaction.
14. Bonnin, A., Picornell, A., Orfila, J., Castro, J. A., and Ramon, M. M. (2009)
Clinic and genetic evaluation of variegate porphyria (VP) in a large family
from the Balearic Islands. J. Inherit. Metab. Dis. 32, S59-S66
Computational Approach for Predicting the Catalytic Effi-
ciency of Enzyme Mutants—Many reports have shown that an
enzyme activity depends on the conformational distribution of 15. Rossetti, M. V., Granata, B. X., Giudice, J., Parera, V. E., and Batlle, A.
(2008) Genetic and biochemical studies in Argentinean patients with
reactants in enzyme active site (39, 40, 46–53). In this study, we
variegate porphyria. BMC Med. Genet. 9, 54
have shown that the probability of the reactable conformations
16. Warnich, L., Kotze, M. J., Groenewald, I. M., Groenewald, J. Z., van Brakel,
of reactants could be employed to quantitatively predict the
M. G., van Heerden, C. J., de Villiers, J. N., van de Ven, W. J., Schoenmak-
catalytic efficiency of the hPPO mutants. This protocol for pre-
dicting catalytic efficiency of mutant hPPO by combining MD
simulation/statistical analysis was called Prenzyme (Fig. 7). The
protocol was based on the notion that a reaction can occur only
through the collisions by the reactants with the privileged con-
formations, and this favorable collision can be evaluated by the
probability of the privileged conformations of ternary catalytic
complex. The conformation probability density function can be
obtained from statistical analysis of the conformational distri-
bution of the ternary catalytic complex from MD and then gives
the probability value by bivariate integration over the intervals
of the corresponding geometric parameters of the privileged
conformations. The obtained probability should be correlated
with kcat/Km of enzyme mutants.
ers, E. F., Taketani, S., and Retief, A. E. (1996) Identification of three mu-
tations and associated haplotypes in the protoporphyrinogen oxidase gene
in South African families with variegate porphyria. Hum. Mol. Genet. 5,
981–984
17. Meissner, P. N., Dailey, T. A., Hift, R. J., Ziman, M., Corrigall, A. V., Rob-
erts, A. G., Meissner, D. M., Kirsch, R. E., and Dailey, H. A. (1996) A R59W
mutation in human protoporphyrinogen oxidase results in decreased en-
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Acknowledgments—The computation was carried out at National
Supercomputer Center in Tianjin, and the calculations were per-
formed on TianHe-1(A). We are grateful to the staff at beamline
BL-17U1 in the Shanghai Synchrotron Radiation Facility for excellent
technical assistance during data collection.
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11740 JOURNAL OF BIOLOGICAL CHEMISTRY
VOLUME 288•NUMBER 17•APRIL 26, 2013

Molecular Bases of Disease:
Quantitative Structural Insight into Human
Variegate Porphyria Disease
Baifan Wang, Xin Wen, Xiaohong Qin,
Zhifang Wang, Ying Tan, Yuequan Shen and
Zhen Xi
J. Biol. Chem. 2013, 288:11731-11740.
doi: 10.1074/jbc.M113.459768 originally published online March 6, 2013
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