Jimin Wang1, Mikhail Askerka2, Gary W Brudvig2, Victor S Batista2. 1. Department of Molecular Biophysics and Biochemistry, Yale University , New Haven, Connecticut 06520-8114, United States. 2. Department of Chemistry, Yale University , New Haven, Connecticut 06520-8107, United States.
Abstract
Understanding structure-function relations in photosystem II (PSII) is important for the development of biomimetic photocatalytic systems. X-ray crystallography, computational modeling, and spectroscopy have played central roles in elucidating the structure and function of PSII. Recent breakthroughs in femtosecond X-ray crystallography offer the possibility of collecting diffraction data from the X-ray free electron laser (XFEL) before radiation damage of the sample, thereby overcoming the main challenge of conventional X-ray diffraction methods. However, the interpretation of XFEL data from PSII intermediates is challenging because of the issues regarding data-processing, uncertainty on the precise positions of light oxygen atoms next to heavy metal centers, and different kinetics of the S-state transition in microcrystals compared to solution. Here, we summarize recent advances and outstanding challenges in PSII structure-function determination with emphasis on the implementation of quantum mechanics/molecular mechanics techniques combined with isomorphous difference Fourier maps, direct methods, and high-resolution spectroscopy.
Understanding structure-function relations in photosystem II (PSII) is important for the development of biomimetic photocatalytic systems. X-ray crystallography, computational modeling, and spectroscopy have played central roles in elucidating the structure and function of PSII. Recent breakthroughs in femtosecond X-ray crystallography offer the possibility of collecting diffraction data from the X-ray free electron laser (XFEL) before radiation damage of the sample, thereby overcoming the main challenge of conventional X-ray diffraction methods. However, the interpretation of XFEL data from PSII intermediates is challenging because of the issues regarding data-processing, uncertainty on the precise positions of light oxygen atoms next to heavy metal centers, and different kinetics of the S-state transition in microcrystals compared to solution. Here, we summarize recent advances and outstanding challenges in PSII structure-function determination with emphasis on the implementation of quantum mechanics/molecular mechanics techniques combined with isomorphous difference Fourier maps, direct methods, and high-resolution spectroscopy.
Photosystem II (PSII) is the
only known protein complex capable of catalyzing direct solar water-splitting
into O2, protons, and electrons.[1−4] Understanding its structure–function
relations can provide fundamental insights, essential for the design
of artificial photosynthetic systems. The oxygen-evolving complex
(OEC) of PSII is a CaMn4O5 oxo-manganese cofactor
that binds substrate water and splits it into O2, protons,
and electrons through a stepwise catalytic cycle (Figure ). During each turn of the
cycle, the OEC evolves through five “storage” states,
S (n = 0–4),
where S1 is the dark stable state while S0 and
S4 are the most reduced and oxidized forms, respectively.[5,6]
Figure 1
Catalytic
cycle of water oxidation, driven by solar light absorption.
Each cycle is initiated by light absorption by the chlorophylls P680, followed by a charge separation. On the donor side, the
electron sequentially reduces the special pheophytin and the pair
of quinones QA and QB. After accepting two electrons,
QBH2 is replaced by an oxidized quinone from
a plastoquinone (PQ) pool. On the donor side, the hole oxidizes tyrosine
Y, which in turn oxidizes the oxygen-evolving
complex. In each turn of the cycle, the OEC of PSII evolves through
“storage” states, S (n = 0–4), catalyzing water splitting, as follows:
2H2O → O2 + 4H+ + 4e–. The water supply and proton release are likely happening through
the water channels (labeled Large, Narrow and Broad) surrounding the
OEC on the luminal side.
Catalytic
cycle of water oxidation, driven by solar light absorption.
Each cycle is initiated by light absorption by the chlorophylls P680, followed by a charge separation. On the donor side, the
electron sequentially reduces the special pheophytin and the pair
of quinones QA and QB. After accepting two electrons,
QBH2 is replaced by an oxidized quinone from
a plastoquinone (PQ) pool. On the donor side, the hole oxidizes tyrosine
Y, which in turn oxidizes the oxygen-evolving
complex. In each turn of the cycle, the OEC of PSII evolves through
“storage” states, S (n = 0–4), catalyzing water splitting, as follows:
2H2O → O2 + 4H+ + 4e–. The water supply and proton release are likely happening through
the water channels (labeled Large, Narrow and Broad) surrounding the
OEC on the luminal side.The detailed analysis of the catalytic reaction has been
challenging
and benefited from an interdisciplinary approach, including computational
modeling, crystallography, and spectroscopy,[7] combined with mutagenesis and kinetic studies. Major breakthroughs
in protein X-ray crystallography have resolved the PSII crystal structure
from 3.8 Å, to the highest 1.9 Å resolution (PDB accession
number 3ARC/3WU2),[8,9] establishing
the architecture of the OEC and its ligation scheme. A challenge has
been that even at the highest resolution, the X-ray dose used for
X-ray data collection caused reduction of the OEC,[8b] consistent with previous studies based on extended X-ray
absorption fine structure (EXAFS) spectrometry.[10−12]In recent
years, X-ray free electron laser (XFEL) pulses with different
approaches applied to serial femtosecond crystallography (SFX)[13−17] have enabled collection of PSII diffraction data on the femtosecond
scale before the onset of significant radiation damage. Several developments
emerged from the analysis of XFEL data, and direct comparisons were
made to computational structural models. Here, we focus on insights
into the PSII machinery obtained from isomorphous difference Fourier
methods in crystallography combined with direct methods and quantum
mechanics/molecular mechanics (QM/MM) calculations.[18−22]Isomorphous Difference Fourier Methods:
The S. A fundamental
limitation of
X-ray crystallography is that only the intensity of the scattered
radiation is measured, I(h) = |F(h)|2, with the structure factordescribing the total radiation diffracted
by the plane of atoms specified by the Miller indices h = (h, k, l).
The phases α = 2πh·r must be modeled
or inferred from the intensity data. The radiation scattered from
each atom j is described by a complex number, f exp(2πih·r), defined
by the atomic fractional coordinates r (coordinates expressed as fractions of the unit cell vectors),
scattering indices h, and tabulated atomic scattering
factors f.[23] The overall pattern of intensities is evaluated
to obtain the crystal structure (unit cell) and symmetry (space group),
and the atomic coordinates r of a proposed structural model are refined to match the calculated
intensities to the experimental values at a given resolution.Tracking subtle changes due to chemical transformations, such as
those induced by the S-state transitions of PSII, requires the analysis
of electron density differences. Here, we consider the electron density
difference due to the S1 [model (I)] to S2 state
[model (II)] transition:Equation requires calculation of phases
αII and αI for both models and gives
the difference of electronic densities
as obtained from the refined models. The difficulty with such an approach
when applied to very similar structures is that real features in the
observed intensity data are not sufficiently distinct from those due
to the model bias inherent in the calculation of the phases.Isomorphous difference Fourier methods[24,25] have important
advantages relative to calculations of electronic
density differences obtained from refined structural models, allowing
for analysis of small changes between an isomorphous pair of structures,
i.e., structures with the same cell parameters, orientation, and overall
conformation of the system in the unit cell, except for small differences
deliberately introduced such as the light-induced S1 to
S2 transition. Contrary to eq , isomorphous difference methods compute electron density
difference maps (as the Fourier transform of the difference of observed
amplitudes) with calculated phases for only one of the models:Remarkably, such an approximation over the
phases gives a very accurate description of the exact map of electron
density differences, even when the phases dominate the Fourier transform.The isomorphous difference Fourier method was initially developed
to analyze small ligand binding (comparable in size to a water ligand)
such as azide or cyanide binding to heme proteins even when direct
Fourier maps were unable to identify the underlying subtle structural
changes at relatively low resolution.[25−30] In its original application, experimental phases were available.[25−28] In the absence of experimental phases, model phases are used (eq ) as in the study of Kern
et al. where structural changes in the OEC during the S1 to S2 transition were explored for XFEL data obtained
at 5.9 Å resolution.[14,15] We used high-resolution
model phases followed by 3-crystal 6-fold noncrystallographic symmetry
(NCS) averaging,[18] as described in the
Supporting Information of ref (18), using model phases from two high-resolution structures
of the same protein (3ARC and 3BZ1).[8a,31] NCS averaging utilizes a more accurate bulk solvent density from
high-resolution models where the bulk solvent correction is more reliable
than low-resolution models and allows for accurate modeling of the
side chains of surface residues that would otherwise influence the
bulk solvent correction and thus the model phases. This approach has
recently allowed us to enhance the intensity of weak signals and raise
them to a statistically significant level for direct observation of
structural changes associated with the S1 to S2 transition[18] not visible in calculations
of electronic density differences obtained from refined structural
models.[14] The density differences are fully
consistent with those observed in QM/MM structural models (Figure ).[18]
Figure 2
Comparison of the difference Fourier maps calculated using QM/MM
S1 and S2 models and using corresponding SFX
data sets. (a) Simulated S2-minus-S1 difference Fourier maps calculated using the QM/MM S1 and S2 models. The highest peak near the OEC results
from the displacement of Mn4. (b) Comparison of the simulated S2-minus-S1 (from panel a) and the
observed S2-minus-S1 (from panel c) difference
Fourier maps using SFX data sets with color codes according to panels
a and c. (c) Observed S2-minus-S1 difference Fourier maps contoured at +3σ (green mesh). Adapted
from ref (18). Copyright
2014 American Chemical Society.
Comparison of the difference Fourier maps calculated using QM/MM
S1 and S2 models and using corresponding SFX
data sets. (a) Simulated S2-minus-S1 difference Fourier maps calculated using the QM/MM S1 and S2 models. The highest peak near the OEC results
from the displacement of Mn4. (b) Comparison of the simulated S2-minus-S1 (from panel a) and the
observed S2-minus-S1 (from panel c) difference
Fourier maps using SFX data sets with color codes according to panels
a and c. (c) Observed S2-minus-S1 difference Fourier maps contoured at +3σ (green mesh). Adapted
from ref (18). Copyright
2014 American Chemical Society.The isomorphous difference analysis provided valuable physical
insights on changes in the coordination sphere of the dangling Mn
center (Mn4, Figure ), induced by the S1 to S2 state transition
of the OEC. According to control calculations based on QM/MM models,
the S1 to S2 state transition involves oxidation
of the dangling Mn (Mn4) in the OEC,[18] from
Mn(III) to Mn(IV), inducing a contraction of the octahedral coordination
sphere of Mn(IV) that results from loss of the Jahn–Teller
distortions present for Mn(III). Such a contraction and the decrease
of the Mn1–Mn4 distance produce a distinct positive peak in
the simulated FModel(S2) – FModel(S1) difference Fourier map
next to the dangling Mn. This peak is detectable at the resolution
corresponding to the experimental data, in good agreement with the
results of the experimental isomorphous difference map obtained from
the SFX data sets reported for 4IXR and 4IXQ(14) (Figure ). We note that the
contraction due to the Jahn–Teller distortion is in fact fairly
small (i.e., the Mn(III) coordination distance is typically 2.1 Å
instead of 1.9 Å). Nevertheless, they can be detected even at
5.9 Å resolution because they involve movement of the Mn center,
with the negative component of the density change compensated by displacement
of the D170 (Figure ) ligand.The structure of PSII in the dark stable S1 state solved
at 1.95 Å resolution using femtosecond XFEL pulses represents
a significant development.[17] These SFX
experiments enabled collection of PSII diffraction data at the highest
resolution before the onset of significant radiation damage. However,
simulations of EXAFS spectra based on the coordinates of the model
show that they are not fully consistent with EXAFS data for the S1 state because of lack of accuracy in the position of the
O atoms of μ-oxo bridges next to the strongly scattering Mn
and Ca ions.[20] Historically, accurate detection
of light O atoms next to metal centers has been challenging. The absence
of the O4 μ-oxo bridge in the 3.3 Å resolution structure
of PSII[32] is an example analogous to the
missing carbon atom in the MoFe center of nitrogenase at 1.55 Å
resolution prior to the 1.16 Å resolution structure. The difficulty
is partly due to ripple effects induced by premature Fourier series
termination for data with insufficient (nominal and spatial) resolution.
In hindsight, once the presence of the ligand is established, the Fo–Fc maps
can be used to confirm the location of light ligands, although the
accuracy of this method is still limited by the tailing effect of
heavier metal ion centers.Isomorphous Difference Fourier
Maps Modified for a Varying
Unit Cell: S. The S3 state of
PSII has been studied by some of the most recent XFEL experiments[16] because it is one of the most important intermediates
in the catalytic cycle, detectable right before O–O bond formation
and reduction of the OEC. The comparative analysis of the S1 and S3 electron density maps has been challenging, with
the two states obtained at different nominal resolution of 5.0 and
5.5 Å, respectively. The challenges are due to (i) the different
kinetics between aqueous solution and individual microcrystals, which
may have prevented PSII in crystals from fully achieving the S3 state, and (ii) changes in the crystallographic unit cell
that may have increased the extent of nonisomorphism.It has
been necessary to modify the isomorphous difference Fourier
method and apply it by computing two sets of electron density maps,
because the original method was not applicable to analyze structures
with different unit cells. Only paired and intensity-scaled reflections
were used in reciprocal space for each unit cell, with only one set
of model phases.[33,34] The resulting maps were realigned
using least-squares procedures (LSQ), as implemented in the Rave package,
and back Fourier-transformed to generate new sets of observed amplitudes
(FobsLSQ) for calculation of difference Fourier map as follows:[19]To minimize the Fourier series termination
effect, only the reflections present in both data sets with 5.0 and
5.5 Å resolution were included in the analysis. The resulting
spatial resolution was limited by the lowest resolution of the compared
structures.The analysis based on realigned difference Fourier
maps provided
valuable insights on the expansion of the CaMn4O5 cluster (Figure ), during the S1 to S3 transition, likely induced
upon binding of substrate water molecule to the dangling Mn as shown
by QM/MM calculations.[19]Figure shows the difference Fourier
maps, obtained according to eq , based on the rescaling to SFX data sets from the S1 and S3 states of PSII.[19] It
reveals significant changes in the Fourier maps localized at the OEC.
The electron density differences at the OEC are consistent with the
QM/MM models, as corresponding to an expansion of the CaMn4O5 cluster during the S1 to S3 transition.[19,22]
Figure 3
Comparison
of QM/MM-derived S3 model and SFX data sets.
(a) QM/MM-optimized structure of the OEC in the S3 state
(Mn oxidation states: IV, IV, IV, IV), including coordination of water
ligands as well as D1-D61, D1-His337, and CP43-R357. (b) Simulated
S3-minus-S1 difference Fourier maps based on
the QM/MM-derived S3 and S1 models. (c) Observed
S3-minus-S1 modified difference Fourier maps
contoured at +3σ (green) and −3σ (red) after map
least-squares superposition. Adapted from ref (19). Copyright 2016 American
Chemical Society.
Comparison
of QM/MM-derived S3 model and SFX data sets.
(a) QM/MM-optimized structure of the OEC in the S3 state
(Mn oxidation states: IV, IV, IV, IV), including coordination of water
ligands as well as D1-D61, D1-His337, and CP43-R357. (b) Simulated
S3-minus-S1 difference Fourier maps based on
the QM/MM-derived S3 and S1 models. (c) Observed
S3-minus-S1 modified difference Fourier maps
contoured at +3σ (green) and −3σ (red) after map
least-squares superposition. Adapted from ref (19). Copyright 2016 American
Chemical Society.The QM/MM rearragement
is consistent with binding of a water molecule
through a “carousel” mechanism,[16,19] suggesting that some fraction of the PSII in microcrystals must
have advanced beyond the S2 state.[35] Considering that the S1 to S2 conversion resulted
in a positive peak inside the OEC near Mn4 (Figure ), the net negative peak observed during the S1 to S3 transition suggestes that the S3 fraction must
have overcompensated whatever fraction of the S2 was formed.
Interestingly, because the metal cluster expands upon S2 to S3 oxidation and the cluster contracts during the
S1 to S2 conversion, it is conceivable that
the S2 to S3 oxidation might indicate binding
of a water molecule, as suggested by various computational models.[19,22,36−39]Computational Noise in XFEL Data Sets. Approximations
and statistical inferences of the algorithms used for data reduction
often introduce nonrandom noise to the experimental data. The analysis
of how the resulting computational noise affects the distribution
of X-ray scattering intensities is important because noise can scramble
weak structural signals of crystallographic data sets (Figures and 5).
Figure 4
L-test plots for selected SFX data sets. (a) L-test results for
data sets of PSII XFEL data are compared for 4PBU (processed with
CrystFEL), 4TNJ (cctbx.xfel), and 4UB8 (mosflm/scala). (b) L-test results for data sets obtained for proteins
other than PSII. Data processed using cctbx.xfel (4QX0 and 4QX2) appear to be maximally
twinned, whereas data processed from the same crystals using CrystFEL
(4QX1 and 4QX3) do not. (c) The
cctbx.xfel-processed 4QX0 data set is divided into three resolution
ranges for L-test: (i) below 5 Å (orange), (ii) between 5 and
4 Å (blue), and (iii) between 4 and 3 Å (black). (d) Comparison
of the Wilson plots (logarithm mean intensity versus inverse resolution
squared) obtained from two cctbx.xfel processed data sets (black/4QX0
and green/4QX2) and two otherwise similar data sets processed using
CrystFEL (red/4QX1 and blue/4QX3) from similar crystals.
Figure 5
An analysis of Young et al. (2016) data sets.[52] (a) L-test for 5TIS (green), 5KAF (gold), and
5KAI (blue)
data sets. Untwinned line is shown in black, and theoretically twinned
curve is in red. (b) Wilson plot for 5TIS (green), 5KAF (gold), and
5KAI (gold) data sets after all data sets were scaled to 5KAF and
placed on the same absolute scale, i.e., logarithms of mean intensity
as a function of reciprocal resolution squared. For comparison, the
corresponding plot for all protein data sets in the PDB is shown in
black. (c) Amplitude differences as a function of reciprocal resolution
between 5KAI and 5KAF (red),
between 3ARC and 4IL6 (black),
between 5KAI and 5TIS (green),
and between 5KAF and 5TIS (blue).
(d) Isomorphous difference Fourier maps between Sr and Ca data set
contoured at +2σ (cyan), + 4σ (green), and −2σ
(magenta) show the largest features for the replacement of a glycerol
(b738) by DMSO (DMS/b628) and a water molecule (d567).
L-test plots for selected SFX data sets. (a) L-test results for
data sets of PSII XFEL data are compared for 4PBU (processed with
CrystFEL), 4TNJ (cctbx.xfel), and 4UB8 (mosflm/scala). (b) L-test results for data sets obtained for proteins
other than PSII. Data processed using cctbx.xfel (4QX0 and 4QX2) appear to be maximally
twinned, whereas data processed from the same crystals using CrystFEL
(4QX1 and 4QX3) do not. (c) The
cctbx.xfel-processed 4QX0 data set is divided into three resolution
ranges for L-test: (i) below 5 Å (orange), (ii) between 5 and
4 Å (blue), and (iii) between 4 and 3 Å (black). (d) Comparison
of the Wilson plots (logarithm mean intensity versus inverse resolution
squared) obtained from two cctbx.xfel processed data sets (black/4QX0
and green/4QX2) and two otherwise similar data sets processed using
CrystFEL (red/4QX1 and blue/4QX3) from similar crystals.An analysis of Young et al. (2016) data sets.[52] (a) L-test for 5TIS (green), 5KAF (gold), and
5KAI (blue)
data sets. Untwinned line is shown in black, and theoretically twinned
curve is in red. (b) Wilson plot for 5TIS (green), 5KAF (gold), and
5KAI (gold) data sets after all data sets were scaled to 5KAF and
placed on the same absolute scale, i.e., logarithms of mean intensity
as a function of reciprocal resolution squared. For comparison, the
corresponding plot for all protein data sets in the PDB is shown in
black. (c) Amplitude differences as a function of reciprocal resolution
between 5KAI and 5KAF (red),
between 3ARC and 4IL6 (black),
between 5KAI and 5TIS (green),
and between 5KAF and 5TIS (blue).
(d) Isomorphous difference Fourier maps between Sr and Ca data set
contoured at +2σ (cyan), + 4σ (green), and −2σ
(magenta) show the largest features for the replacement of a glycerol
(b738) by DMSO (DMS/b628) and a water molecule (d567).A classic example of computational noise concerned
the treatment
of negative and weak intensity measurements that concluded with a
Bayesian statistical solution formulated by French and Wilson (1978).[40] The probability of measuring the intensity of
any reflection as negative is known,[41] although
sometimes disregarded.[42] Proper processing
of negative intensities, however, is critical for the quality of the
data and XFEL maps produced from microcrystals. Discussions on negative
intensities can be found elsewhere.[43] Here,
we limit the presentation to the simplest example showing why it is
important to include negative intensity measurements during an intensity
merging process. If one measures a systematically absent Bragg reflection (with null average intensity) several times, it
is likely that after background subtraction half of the measurements
will be positive and half negative. If the five negative measurements
are disregarded, arguing that the intensity (i.e., amplitude square) must be positive, the mean value of the reflection would
be positive instead of null. Thus, this reflection would be no longer absent.Improper treatment of negative and weak intensity
measurements
could lead to various skewed intensity distributions, detectable by
statistical tests. With properly processed data sets, the probability
density of any given acentric Bragg reflection with intensity between I and I + dI follows the
single exponential function, exp[−I/⟨I⟩], known as the Wilson intensity distribution,
where ⟨I⟩ is the mean intensity of
all noncentric Bragg reflections.[44] The
probability density of fractional intensity differences between pairs
of Bragg reflections selected locally in reciprocal space, L ≡ (I1 – I2)/[(I1 + I2)/2], provides the L-test because the first
and second moments ⟨|L|⟩ and ⟨L2⟩ are 1/2 and 1/3 for untwinned acentric
data, respectively. If twinning occurs, as observed in crystal lattices
where the unit cell can adopt more than one orientation, the L moments are lowered and reach a value of 3/8 and 1/5 for
fully twinned data.[45]When twinning is physically
impossible, as for the PSII crystals
with P212121 symmetry,
the skewed intensity distribution identified by the L-test quantifies
the level of computational noise introduced in the data sets. Figures and 5 shows that an outstanding challenge in the field is the reduction
of computational noise in the XFEL data sets of PSII structures.[45] In particular, Figure analyzes data sets processed with the CrystFEL,
cctbx.xfel, and mosflm XFEL-specific programs, which have been used
to process the XFEL PSII data deposited in the PDB.[42,46−49]Figure a shows that
the 4TNJ PSII
data set has a much higher level of computational noise than the 4PBU (or other PSII)
data sets, processed using the CrystFEL program (or other programs).[13−17] When the same L-tests are extended to XFEL data sets from other
proteins, it is clear that the problem is not related to the PSII
crystals but rather to a data-processing artifact specific to cctbx.xfel
(Figure b).[42,50]Figure analyzes
the cctbx.xfel-processed data as divided into three resolution ranges:
(i) below 5 Å, (ii) 5–4 Å, and (iii) 4–3 Å.
The L-tests were performed on each of the three blocks of data, independently.
The 4–3 Å range exhibits the highest level of computational
noise because the average intensities are the lowest (Figure c). Consistently, Wilson plots
(i.e., logarithm of mean intensity in a given resolution shell versus
the reciprocal resolution squared for this shell) for data sets processed
with cctbx.xfel are displaced upward, at higher resolutions, relative
to those obtained with CrystFEL from the same crystals (Figure d). It is thus concluded that
cctbx.xfel has systematically overestimated the intensities of weak
reflections, as also acknowledged by the authors of cctbx.xfel.[51] In fact, recent inclusion of negative intensities
after background subtraction by reprocessing XFEL data sets of the
synaptotagmin-1/SNARE complex has partly alleviated the unusual behavior
of the L-test and made the XFEL data set comparable to that of the
synchrotron data set.[51]Analysis
of the Most Recent XFEL Structures. Shortly
after submission of this manuscript, a new XFEL experiment was reported
with the analysis of PSII in the dark stable S1 state (5KAF, 3.0 Å resolution),
the S3 state (5TIS, 2F or two-flashes state, at 2.25 Å), and ammonia-bound
S3 (5KAI, 2F-NH3 state at 2.8 Å),[52] because NH3 is analyzed as an analog of water. The corresponding 5KAF and 5KAI data sets were collected
using the same wavelength and experimental setup, having practically
the same unit cell parameters (i.e., the maximal cell parameter difference
between them is 0.5 Å or 0.25%, smaller than the variations of
cell parameters of about 3 Å reported for the two structures).[52] Thus, the 5KAF and 5KAI isomorphous pair is suitable for analysis
based on the classic isomorphous difference Fourier method. As a control,
we calculated isomorphous difference Fourier maps at 2.1 and 3.0 Å
resolution between the 4IL6 and 3ARC/3WU2 data
sets, using the model-derived phases of 3ARC/3WU2,[8a,53] where 4IL6 represents the data set of the Sr-substituted OEC in
the presence of dimethyl sulfoxide (DMSO or DMS) and 3ARC/3WU2 represents
the structure of wild-type Ca-containing enzyme in the presence of
glycerol. The 3ARC/4IL6 pair is ideally suited for a control experiment
because it has amplitude differences as a function of reciprocal resolution
that are similar to those of the 5KAF/5KAI pair (Figure c). The 3ARC/4IL6 has an overall
amplitude difference of 31.3% at 3.0 Å resolution (and 35.9%
at 2.1 Å resolution), while that for the 5KAF/5KAI pair is 28.7%
at 3.0 Å resolution (Figure c). The maximal change in fractional unit cell parameters
for the 3ARC/4IL6 is 0.33%, which is only slightly larger than the
5KAF/5KAI pair (0.25%).In the 3ARC/4IL6 difference-Fourier
maps, the largest positive
peak observed at +7.4σ pinpoints the replacement of a glycerol
molecule (GOL/b738) with a DMSO (DMS/b628) molecule plus an ordered
water molecule (d567) (Figure d). Corresponding 2Fo(Sr/DMSO)-Fo(Ca/GOL)
maps and 2Fo(Ca/GOL)-Fo(Sr/DMSO) have also unambiguously
confirmed this replacement.The second largest peak is associated
with the substitution of
Ca by Sr at the OEC (Figure c) because Sr is larger and denser than Ca. Upon Sr substitution,
the OEC slightly expands, and three of the four Mn centers exhibit
significant peaks above ±4σ due to subtle displacements.
Noticeably, Cl-A680 also has a significant negative peak on it, implying
a possible loss of occupancy for this Cl– anion
(Figure c).
Figure 6
Isomorphous
difference Fourier maps in stereodiagram. (a) Between 5KAI and 5KAF contoured at ±2.5σ
(green and red). (b) At ± 4.0σ (green and red). (c) Between 4IL6 and 3ARC contoured at ±4.0σ
(green and red).
Isomorphous
difference Fourier maps in stereodiagram. (a) Between 5KAI and 5KAF contoured at ±2.5σ
(green and red). (b) At ± 4.0σ (green and red). (c) Between 4IL6 and 3ARC contoured at ±4.0σ
(green and red).In contrast to the analysis
of the Sr substituted PSII, the isomorphous
difference Fourier maps between 5KAI and 5KAF calculated at various resolutions (using
model phases retrieved from the PDB), exhibit no significant detectable
difference at the ±2.5σ contour level at the OEC site,
nor at ±4σ in its vicinity (Figure ab), suggesting no detectable NH3 binding.5TIS is the first PSII XFEL data set collected at
room temperature
with sufficiently high resolution for reliable Wilson-plot analysis
(Figure ). However,
even for this data set, the L-test (Figure a) shows significant deviations from the
expected straight line, similarly to the L-test of all of the PSII
X-ray data sets deposited in the PDB that have been analyzed by using
cctbx.xfel. Furthermore, the mean intensity (Figure b) does not exhibit the proper decay and
is higher than expected. Therefore, it remains a major challenge to
determine whether there is sufficient signal to be extracted in individual
XFEL images at high resolution, particularly when detectable X-ray
photons might be less than 1 per pixel. In that case, the proper way
to obtain accurate estimates of intensities would be to use tens of
thousands of individual images to enhance very weak signals with statistically
sound treatments of negative and weak intensity signals. Otherwise,
as the resolution increases, the mean intensity at high resolution
would approach the asymptotic value of the lowest detectable photon
numbers per pixel.[54]Direct Methods. Direct methods infer information
about phases from measured intensities,[55−58] exploiting constraints between
the phases of different Fourier components due to the atomicity of
the molecules and the fact that the electron density should be zero
or positive at any point of the unit cell. For example, phases for
small molecules and medium-sized molecular structures can be directly
retrieved from accurately measured amplitudes, using
the Hauptman–Karle algorithm.[57,58] However, that
method is often not particularly useful when applied to large proteins
because the probability of phase relationship is often too broad,
and the overall B-factor for protein data sets can be as much as 10
times larger than for small molecules, making the electron density
function for atoms very broad and phase retrieval very challenging.
To overcome the broadening of the electron density distribution around
atoms, one can use normalized structure factors, resulting in point-atoms
in maps. To alleviate the ripple effects of premature Fourier series
termination, Wilson-expected values are used to fill in missing high-resolution
terms.[59]Direct methods have suggested
that conventional X-ray diffraction
data sets, based on an analysis of the 3ARC data,[8a] exhibit extensive oxidative modifications (Figure ).[59]Figure shows, for
example, an Ala residue that has been converted into Ser (A283S).[59] Analogous changes are observed in about 10%
of the residues (i.e., at least 538 residues out of the total of 5351
have been modified). The radiation-induced oxygen insertion in amino
acids and proteins has been studied for over a century using a variety
of biophysical methods (see ref (59) for a brief historical review, including two
recent specific studies on oxidation of PSII protein residues[60,61]). Radiation splits an H2O molecule into a highly reactive
hydroxyl radical and a highly reductive hydrated electron. The hydroxyl
radical is thought to be responsible for the observed oxygen insertion
chemistry, while the hydrated electron is responsible for reduction
of metal centers such as Mn at the OEC.[8a] We note that Fe is not significantly reduced in the 5EJX crystal structure
because the Fe–O bond distance is 1.75 Å, only slightly
elongated relative to the corresponding bond length of 1.73 Å
in a low-dose synchrotron structure (code 3M23).[16] However,
while an elongated Fe–O bond distance would confirm reduction
by free electrons, the lack of elongation cannot rule out radiation
damage.
Figure 7
Direct-methods generated E-map showing conversion
of Ala to Ser in the PSII 3ARC data set. The E-map
was contoured at +8.0σ (cyan), + 5.0σ (blue), and +2.0σ
(green) followed by an interpretation of Ser residue in three different
rotameric positions (green, pink, and light red). Adapted with permission
from ref (59). Copyright
2016 Wiley.
Direct-methods generated E-map showing conversion
of Ala to Ser in the PSII 3ARC data set. The E-map
was contoured at +8.0σ (cyan), + 5.0σ (blue), and +2.0σ
(green) followed by an interpretation of Ser residue in three different
rotameric positions (green, pink, and light red). Adapted with permission
from ref (59). Copyright
2016 Wiley.We note that the peaks
interpreted as additional oxygen atoms were
relatively small because only the second half of the data set exhibits
protein modifications. These specific fingerprints, in only part of
the diffraction data, are nevertheless quite distinct relative to
nonspecific damage that usually reduces the diffraction intensity
of the entire data set.
Ongoing Challenges
Other outstanding challenges
include an ongoing debate about the
possibility of radiation damage during XFEL experiments. In addition
to room-temperature SFX, the two highest-resolution SFX data sets
for PSII have been recorded by using multiple shots per frozen crystal
at liquid N2 temperatures.[17] While the use of cryogenic temperatures has been a common methodology
for conventional crystallographic data sets (e.g., for the highest-resolution
data set of PSII reported[8a]), there is
evidence that the diffusion rate of hydroxyl radicals generated by
radiation might be faster than the rate of sample translation for
bringing unexposed parts of the sample to the exposing position. As
a consequence, oxygen atoms might be added to many of the protein
residues, as observed in cytochrome c peroxidase.[59,62]The self-amplified self-emission process represents another XFEL
challenge because the process is highly stochastic with large fluctuations.[63] Femtosecond pulses of XFEL are thus quite different
from one another, in terms of their intensity profiles. Usually, the
effect of such variation is not included in SFX modeling theories.[64−67] Therefore, it is conceivable that the SFX data might have recorded
a destruction process of molecules in the crystal lattice and that
such a destructive process may differ from one XFEL pulse to another,
partially explain why merging statistics of XFEL data sets does not
always provide significant statistical improvements.[68,69]
Conclusions
We have reviewed
recent advancements in the field of PSII structural
characterization, with emphasis on outstanding challenges and insights
from isomorphous difference Fourier maps of femtosecond X-ray diffraction
data as well as direct methods in conjunction with QM/MM structural
models. The crystal structure of PSII obtained at 1.9 Å resolution
using conventional X-ray crystallography[8a] represents a milestone achievement that has confirmed and established
many structural features of PSII. However, it is now clear that the
reported data reflect X-ray radiation-induced modifications.[8a] Similarly, the SFX structure at 1.95 Å
resolution is a significant breakthrough, although several challenges
remain to be addressed with respect to the analysis of data collected
for SFX structures. In particular, the quality of the overall data
statistics and the methods for data processing remain challenging.
We have reviewed some historical literature on statistically sound
approaches that might provide valuable solutions to improve both accuracy
and consistency of XFEL data sets.[62,69] The crystallographic
community has decades of experience on how to properly process still
diffraction images, for example, in Laue diffraction.[70] Like SFX diffraction experiments, one-shot-per-crystal
determination using Laue diffraction has also been developed.[71] In the next few years, achieving atomic resolution
of the OEC for the various S-state intermediates would also require
overcoming the variable initial S-state composition due to extensive
dark adaptation prior to data collection as well as the intrinsic
uncertainty in the positions of oxygen atoms due to weak diffraction
of oxygen atoms next to the heavier manganese centers. The resulting
structural information should be particularly valuable for understanding
structure–function relations of PSII that could inform the
development of biomimetic photocatalytic systems.
Authors: Junko Yano; Jan Kern; Klaus-Dieter Irrgang; Matthew J Latimer; Uwe Bergmann; Pieter Glatzel; Yulia Pushkar; Jacek Biesiadka; Bernhard Loll; Kenneth Sauer; Johannes Messinger; Athina Zouni; Vittal K Yachandra Journal: Proc Natl Acad Sci U S A Date: 2005-08-15 Impact factor: 11.205