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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5422_Библиотеки_им_академика_М_И_Перельмана
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7.1 History and Concepts 205
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glycosylation tree added in vivo, are deleted from the protein structure model
and rebuilt.
7.1.2.4 Systematic Integration of Structural Knowledge
Besides the use of homologous proteins to complete loops in a protein, homolog
structures are also used as an additional source of geometric restraints for the renement of models with low-resolution experimental data [29]. This information is captured by comparing hydrogen bonds in the structure model to equivalent hydrogen
bonds in close homologs (70% sequence identity or better). The mean hydrogen bond
length in the homologs is used to set a distance restraintbetween the hydrogen bonding partners in the model. The standard deviation is used to set the relative weight of
the restraints so that low standard deviations resulting from strong structural conservation and impose tight restrains, while large standard deviations cause loose
restraints. The use of such restraints improves the geometric quality of the structure models [29]. Additionally, the use of such homology-based restraints increases
the consistency of structural homologs, unless there is strong signal in the experimental data for structural dierences. This makes it easier for users to assess the
structural eect of moving a protein from one functional state to another, e.g. by
binding dierent ligands.
The addition of new structural knowledge when rening structure models in
PDB-REDO is not limited to proteins. Other specialized restraints are added for
structural zinc binding sites [30] and for base pairs in nucleic acid structures [31].
7.1.2.5 Overview of PDB-REDO Pipeline
The input for the PDB-REDO pipeline (Figure 7.2) is an atomic coordinate le, the
experimental data le, and the sequence. The pipeline checks if all required data
are provided and determines various parameters that are used for the renement
with REFMAC [2]. Next, several parallel renements of the structure model are
executed with dierent combinations of parameters, and the best parameters for
renement are chosen. Then, the new model and electron density map are used for
structure rebuilding with the tools we described above. The rebuilt model is rened
once more, while ne-tuning the parameters from the previous round to obtain the
nal structure, i.e. the PDB-REDO model. This model is validated on overall structure parameters, e.g. R-free and Ramachandran Z-score. Nucleic acids are validated
against their specic parameters and ligands are validated separately as well. The
parameters, tools and software, the PDB-REDO model, maps, and validation data
are all saved in the PDB-REDO databank for existing PDB entries. As a result of the
Model coordinates
X-ray data
Sequence
Restraints
Parameterisation
Refinement
Rebuilding
Additional
refinement
Model
validation
Figure 7.2 The fully automated decision-making PDB-REDO pipeline for optimization of
macromolecular structure models that were obtained from X-ray crystallographic
experiments. 3D boxes represent parallel computing.
PDB-REDO
model and data
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PDB-REDO pipeline, more accurate descriptions of the structure models supported
by the experimentally obtained electron density are obtained.
In order to optimize structure models in an eective and ecient manner,
all the steps in PDB-REDO are fully automated. The tools in the PDB-REDO
pipeline that enable the functionalities described above are tied together with many
decision-making algorithms that together form a so-called “expert system,” i.e. a
framework that tries to mimic what a human expert would do [32]. Of course, the
complexity of this system comes at a price in terms of speed and therefore many
steps use parallel computing. As a result, a typical PDB-REDO calculation takes less
than 30 minutes on a modern workstation whereas any manual approach might
cost hours or even days.
7.2 Structure Improvements by PDB-REDO
To showcase the benets of using PDB-REDO models, this section discusses specic
examples that illustrate how updated macromolecular structure models can change
the biological interpretation of a structure model. These cases are, therefore, interesting examples of the benets that PDB-REDO can bring to CADD projects.
7.2.1 Parametrization and Rebuilding Effects on Small Molecule
Ligands
Many macromolecular structures contain (small molecule) ligands, (metal) ions,
or cofactors that are involved in protein function or structural integrity. Also,
small molecules can be used to modulate the protein’s function or to mediate
protein–protein interactions. Such compounds are found in X-ray structure
models and are treated distinctly during parameterization and renement in
the PDB-REDO pipeline [33]. Here, we illustrate how the specic and uniform
treatment of such compounds, as well as the possible consequences of rebuilding in
their proximity, can aect biochemical conclusions and thus CADD projects.
7.2.1.1 Re-refinement Improves Ligand Conformation
Type IIA DNA topoisomerases are ATP-dependent enzymes involved in cell growth
and division by changing the coiling of DNA helices. These enzymes are the
targets for antibiotics and antitumor agents. To obtain structural insights into
the mechanism of ATP hydrolysis that is coupled to the topoisomerase function,
the crystal structure of the human type IIA DNA topoisomerase was determined
with AMP-PNP, a non-hydrolyzable ATP analogue, and with ADP [34]. The authors
describe conformational dierences of the ribose groups in AMP-PNP and ADP
leading to dierences in interactions with the protein, notably through hydrogen
bonding. However, re-renement of both structure models in PDB-REDO leads
to conformational changes in the nucleotide, particularly in the ribose of ADP
(Figure 7.3). The PDB-REDO procedure removed most of the dierences in the
ribose conformations and resulted to highly similar binding modes for ADP and
7.2 Structure Improvements by PDB-REDO 207
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(a)
(c)
PDB
PDB
(b)
(d)
PDB-REDO
PDB-REDO
Figure 7.3 PDB-REDO results of the binding site of AMP-PNP and ADP (carbon atoms in
light blue) in human type IIA DNA topoisomerase (grey, PDB entries 1zxm and 1zxn, chain
A), side chains of SER149 and ASN150 are shown (carbon atoms in grey) and hydrogen
bonds as black dotted lines. Electron density maps (blue) are oversampled at 0.5 for clarity,
contour levels: 2.5σ for 2mF
difference density (red and green). (a) Model as deposited in the PDB with AMP-PNP.
(b) Model by PDB-REDO with the improved conformation of AMP-PNP. (c) Model as
deposited in the PDB with negative difference density surrounding the O2
-DFcmap 1zxm, 2.0σ for 2mFo-DFcmap 1zxn, 3.5σ for
o
′
and O3′atoms
of ADP. The ribose has a different conformation from that in AMP-PNP. (d) PDB-REDO model
in which re-refinement has led to a change in ribose conformation removing the difference
between ADP and AMP-PNP. The negative difference density surrounding the O2
′
and O3
′
atoms disappeared. Figure and all molecular graphics figures below were made with
CCP4mg. Source: Adapted from McNicholas et al. [35].
AMP-PNP, contradicting the original interpretation of the authors. These models
show the importance of proper renement parameterization as used in PDB-REDO.
7.2.1.2 Side Chain Rebuilding Improves Ligand Binding Sites
Glycogen synthase-2 is involved in the biosynthesis of glycogen, which is one of
the most important energy sources in eukaryotes. The basal state of this enzyme
in complex with UDP was crystallized, which provided new structural insights
into the activation of glycogen synthase-2 [36]. Inspection of the binding site
in the PDB-deposited model shows that the uridine base is held in place by a
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(a)
Figure 7.4 Side chain rebuilding of Phe480 of Glycogen synthase-2 (carbon atoms in grey)
results in improved π–π stacking with UDP (carbon atoms in light blue) in the crystal
structure of the basal state (PDB entry 3o3c, chain A). Electron density maps (blue) are
oversampled at 0.5 for clarity, contour levels: 1.75σ for 2mF
density (red and green). (a) UDP binding site as in PDB model. (b) UDP binding site as in
PDB-REDO model, where π–π interactions are observed with Phe480.
PDB
(b)
PDB-REDO
-DFcmap, 3.50σ for difference
o
hydrogen bond to the protein backbone and π–π interactions with Tyr492. The
side-chain rebuilding in PDB-REDO has moved the side-chain of Phe480 such that
its contribution to UDP binding is also apparent. It has additional π–π interactions
with UDP causing the base to be sandwiched between the aromatic side-chains
(Figure 7.4). The change in π–π interactions for UDP is recorded in the ligand
validation data of PDB-REDO (3o3c_ligval.json (see Section 7.3.1 for downloading
details)). In chain A of the protein, the number of π–π interactions increased from
3 to 6, with a π–π strength improvement of 0.69 (2.75 in the PDB model, 3.44 in
the PDB-REDO model) as measured from the knowledge-based potential used
in YASARA [37].
Besides changing the rotamers of amino acid side chains, PDB-REDO also completes residues in which the side-chains were left unmodeled. This is illustrated by
the binding site of BRAF V600E mutant co-crystallized with vem-bisamide. This
kinase is an oncoprotein in the mitogen-activated protein kinase (MAPK) signaling
pathwaythat is found mutated in several forms of cancer.In melanoma for instance,
the V600E pathogenic mutant is observed regularly and is often targeted in drug discovery. Vemurafenib is one of the compounds that resulted from such studies but
can lead to so-called transactivation of wild-type BRAF. By chemical linkage of two
vemurafenib molecules, vem-bisamide was developed to overcome this transactivation by forcing BRAF into an inactive dimeric conformation. One of the key residues
in potency of inhibitors based on linked vemurafenib-moieties is Gln461 [38]. The
interaction with this residue is nicely modeled in chain A of the crystal structure of
BRAF-V600E in complex with vem-bisamide. However, in chain B the side-chain of
Gln461 is not modeled, hiding a key protein–ligand interaction (Figure 7.5). In the
PDB-REDO model, this residue Gln461 has been completed and the interaction with
the ligand is made obvious (Figure 7.5).
7.2.1.3 Histidine Flip and Improved Ligand Parameterization
The crystal structure of the E. coli autoinducer-2 processing protein LsrF
was obtained without and with the ligands ribose-5-phosphate (R5P) or
7.2 Structure Improvements by PDB-REDO 209
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(a)
Figure 7.5 Vem-bisamide (carbon atoms in light blue, partially shown) is symmetrically
bound by two copies of BRAF kinase (grey, PDB entry 5jt2). Electron density maps (blue) are
oversampled at 0.5 for clarity, contour levels: 1.25σ for 2mF
density (red and green). (a) In the PDB model, key interacting residue Gln461 (carbon atoms
in grey) is only completely placed in one of the BRAF chains. (b) The missing side chain of
the second Gln461 has been completed by PDB-REDO revealing the full interaction of
VEM-BISAMIDE with BRAF.
PDB
(b)
PDB-REDO
-DFcmap, 3.5σ for difference
o
ribulose-5-phosphate. These structures lead to the strong suggestion that LsrF
belongs to class I aldolases, which are involved in maintaining bacterial expression
of specic genes by catalyzing the formation or cleavage of C–C bonds [39]. The
HSSP multiple sequence alignment [40] of LsrF shows that the binding pocket is
highly conserved with His58 fully conserved among species. Therefore, it is most
likely that this histidine is involved in binding of R5P. However, in the crystal
structure of the autoinducer-2 as deposited in the PDB, His58 does not form any
specic interaction with the ligand (Figure 7.6). As a result of the hydrogen bond
optimization module in PDB-REDO, this histidine residue has been ipped to form
(a)
Figure 7.6 PDB-REDO improves the binding site of R5P (carbon atoms in light blue) in LsrF
(grey, PDB entry 3glc, chain A) by flipping the His58 side chain (carbon atoms in grey).
Additionally, the overall conformation of R5P is improved. Electron density maps (blue) are
oversampled at 0.5 for clarity, contour levels: 1.5σ for 2mF
density (red and green). (a) LsrF structure model as deposited in the PDB. (b) PDB-REDO
model in which His58 has flipped and forms a hydrogen bond with the ligand (black dotted
lines). The negative difference density indicates partial occupancy for ribose-5-phosphate.
PDB
(b)
PDB-REDO
-DFcmap, 3.5σ for difference
o
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a hydrogen bond with R5P in the PDB-REDO model (Figure 7.6). Additionally,
the PDB-REDO parameterization improves the overall ligand conformational
t to the density of the R5P ligand. Notably, the parameterization used in the
renement made the B-factor of atoms in R5P more similar to the surrounding
protein atoms. This has resulted in negative dierence density indicating that the
ribose-5-phosphate binding site is only partially occupied.
Although PDB-REDO can improve ligand binding sites and ligand geometry automatically, it cannot reinterpret the ligand to the level of providing an alternative
compound. However,De Souza and co-workers showed that PDB-REDO models are
a suitable starting point for manual reinterpretation of ligands [41].
7.2.2 Building of Protein Loops and Ligands into Protein Structure
Models
Loops are the more exible parts of a protein and tend to give weaker diraction
in crystallographic experiments. This results in poorer local quality of electron density maps and therefore loops are harder to model than other secondary structure
elements such as α-helices and β-sheets. Incomplete protein structure models are
deposited to the PDB, mostly for good reasons: when the experimental data do not
support the modeling of explicit atoms, those should not be added to the model.
However, the decision not to model a loop is invariably a personal one, and some
unmodeled loops can be built with reasonable reliability into poor electron density if
some prerequisites are met. PDB-REDO tries to solve this issue in two ways.First, the
renement steps in PDB-REDO typically lead to an improved atomic model, which
in turn leads to better electron density maps than previously available. Second, the
program Loopwhole reduces the vast number of possible loop conformations to the
ones observed in experimental structures of the same or closely related proteins,
which have a high probability of being correct. Combining both techniques allows
PDB-REDO to add thousands of previously missing loops to PDB models. These
more complete models can then enrich downstream functional or mechanistic interpretations of protein structure. Eventually, this could lead to a better description of
potential binding sites to be targeted in drug discovery [21].
7.2.2.1 Loop Building Completes a Binding Site Region
In the crystal structure of galactokinase from Pyrococcus furiosus,PDB-REDO
builds a substantial part of a loop surrounding the ADP binding site. While this
structure was obtained in complex with ADP, magnesium, and galactose [42],
the surroundings of the ADP binding site in the model as deposited in the PDB
were left unmodeled. There is, however, density observed for this region of the
protein (Figure 7.7). The automatic loop-building algorithm in the PDB-REDO
pipeline improved this part of the protein structure by building the missing loop
(residues 48–72) (Figure 7.7) with a good t to the experimental data. Although
new interactions between the built residues with ADP are not observed in the
PDB-REDO model, the description of the protein is more complete, which is
relevant for structure-based CADD.
7.2 Structure Improvements by PDB-REDO 211
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(a)
Figure 7.7 PDB-REDO builds loop surrounding the ADP (carbon atoms in light blue)
binding site of the Pyrococcus furiosus galactokinase (grey, PDB entry 1s4e, chain B).
Electron density maps (blue) are oversampled at 0.5 for clarity, contour levels: 1.0σ for
2mF
PDB with unmodeled density and difference density surrounding the ADP binding site.
(b) PDB-REDO model with automatically built loop (residues 48–72, salmon pink ribbons)
in the electron density to complete the chain.
PDB
-DFcmap, 3.5σ for difference density (red and green). (a) Model as deposited in the
o
(b)
PDB-REDO
7.2.2.2 Loop Building Results in Improved Binding Sites
Loop rebuilding in PDB-REDO can improve binding sites as showcased for the magnesium binding site of the geranyl diphosphate methyltransferase in complex with
geranyldiphosphate (GPP) and sinefungin. This protein was used to provide insights
in the methyl-group transfer mechanism, which is a common regulatory process in
living organisms [43]. In the original model, magnesium interacts with the phosphate groups of GPP and with Glu89. However, the magnesium ion lacks an additional coordination ligand (Figure 7.8). This missing interaction could be explained
by the unmodeled residues Val44 and Asn45, which are located in the magnesium
(a)
Figure 7.8 Addition of residues Val44 and Asn45 results in completing magnesium and
GPP (carbon atoms in light blue) binding site in geranyl diphosphate methyltransferase
(grey, PDB entry 4f86, chain H). Electron density maps (blue) are oversampled at 0.5 for
clarity, contour levels: 1.75σ for 2mF
(a) Model as deposited in the PDB with unmodeled residues 44 and 45. Magnesium is
coordinated to GPP and Glu89 (carbon atoms in grey). (b) PDB-REDO model with added
residues Val44 and Asn45 (carbon atoms in grey) resulting in more complete magnesium
coordination.
PDB
(b)
-DFcmap, 3.5σ for difference density (red and green).
o
PDB-REDO
212 7 PDB-REDO in Computational-Aided Drug Design (CADD)
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binding site. The PDB-REDO loop building adds the two missing residues, leading to a proper magnesium binding site. In addition to the interactions with Glu89
and the phosphates of GPP, the magnesium atom is now also coordinated to Asn45
(Figure 7.8).
7.2.2.3 Building new Compounds into Density
The cytochrome P450 monooxygenase enzymes (CYPs) are important in
post-polyketide modications and thereby cause molecular diversity during
metabolism. Insights into the mechanism of the CYP450 proteins provide valuable
information for drug design, given the involvement of such enzymes in many
metabolic processes, both physiological and xenobiotic [44]. Filipin is often used
as probe for cholesterol binding sites in studies regarding this enzyme. One of
such CYP450-lipin complex obtained by X-ray crystallography is the model
of CYP105P1. Besides lipin, the structure also contains SO
ions and glycerol
4
molecules that were used during the crystallization process [45]. When inspecting
the model of this structure as deposited in the PDB, some well-dened density
regions have no atoms modeled. Although this is not a feature that is employed by
default, PDB-REDO can build missing compounds if provided a list of candidates.
In the case of the CYP450-lipin complex, glycerol molecules and SO
(data not shown). Furthermore, one of the modeled water networks in the original
structure (Figure 7.9) indicates that it might be replaced by a dierent compound
present in the crystal and was indeed replaced by this compound in the PDB-REDO
model (Figure 7.9).
These results show that, provided the input model has machine-readable metadata that describes other possible compounds, a model can be made more complete
by automatically tting compounds into the density. This becomes particularly
important if a compound directly inuences the binding pose of a ligand of interest.
An example of this issue was described by Dym et al. [46], who showed that
binding position of methylene blue in acetylcholinesterase was shifted outward by
a poly-ethylene glycol (PEG) molecule sitting at the bottom of the binding pocket.
This eect was overlooked in an early experimental structure model because the
were tted
4
(a)
Figure 7.9 Original modeled water atoms (red spheres) are replaced by a buffer residue
CSX (carbon atoms in light blue) in de PDB-REDO model of CYP105P1 (grey, PDB entry 3aba,
chain A). Electron density maps (blue) are oversampled at 0.5 for clarity, contour levels: 1.0σ
for 2mF
in the PDB model. (b) PDB-REDO model in which CXS has replaced the water network.
PDB
-DFcmap, 3.5σ for difference density (red and green). (a) Water network as present
o
(b)
PDB-REDO
CXS
7.2 Structure Improvements by PDB-REDO 213
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PEG was not tted in the electron density, which caused conicting results in
downstream structural analyses.
Although crystallization additives and a buer were used as examples, this
approach can be used for ligands and fragments in experimental high-throughput
(lead) drug discovery. This is available as a feature in the PDB-REDO software,
which is currently being tested in real-life experimental settings.
7.2.3 Nucleic Acid Improvements by PDB-REDO
PDB-REDO also applies nucleic acid restraints and validation targets for nucleic
acid-containing structure models. These parameters are limited to the most common structural features: Watson–Crick base pairs [31]. Overall nucleic acids are
improved in both protein–nucleic acid complexes, as well as (mostly) nucleic acid
structures such as ribosomal subunits. One of the rst ribosomal structures that
were deposited in the PDB is the 30S subunit that was used to study its interactions
with antibiotics [47]. The antibiotic paromomycin is bound in such a way that it
is surrounded by nucleotides, among which is G1494 (Figure 7.10). PDB-REDO
restraints improve the orientation of this C–G base pair without changing the
interactions of the nucleic acid structure with the ligand (Figure 7.10). The Z
bgG
a metric describing the relative orientation of the bases, is 3.63 in PDB and 2.04
in PDB-REDO, which is closer to an “ideal” C–G base pair with Z
bpG
= 0.0.
The strongest contribution to this improvement comes from reduced shearing
between the bases. Additionally, the negative dierence density on the ligand has
disappeared.
,
(a)
Figure 7.10 G1494-C1407 base pair (carbon atoms in grey) in the 30S ribosomal subunit
(grey, PDB entry 1fjg) in complex with paromomycin (carbon atoms in light blue). Electron
density maps (blue) are oversampled at 0.5 for clarity, contour level: 1.0 σ for 2mF
map, 3.5 σ for difference density (red and green). Hydrogen bonds in the G–C base pair are
indicated with black dotted lines. (a) Structure model as deposited in the PDB with
suboptimal hydrogen bonds in the G–C base pair (2.7, 3.1, 3.3Å, shear Z-score −8.85 Å).
(b) Structure model as in PDB-REDO with improved base pair geometry (hydrogen bond
distances 2.8, 2.9, 3.0 Å, shear Z-score -4.43) and the negative difference density on the
ligand drastically reduced.
PDB
(b)
PDB-REDO
–DF
o
c
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7.2.4 Glycoprotein Structure Model Rebuilding
Glycosylation is a common post-translational modication of proteins. The modications are important in recognition of other proteins, stability, and formation of
protein complexes [48]. In PDB models, the glycosylated parts of proteins are not
always resolved properly, which indicates that there is sucient room for model
improvement. Initially, PDB-REDO worked on carbohydrates by improving model
annotation and thereby helping model renement to improve the atomic coordinates [49], but much more substantial improvements were achieved when automated (re)building of N-glycans was introduced [25]. The latteris illustrated through
the crystal structure of the binding domain of SARS-CoV-2 spike, which contains a
glycosylated Asn53 [50]. However, the electron density map suggests that the glycan tree can be extended (Figure 7.11). The PDB-REDO model indeed contains an
additional NAG (Figure 7.11).
7.2.5 Metal Binding Sites
Description of metal binding sites is challenging in X-ray modeling software, especially at low resolution. The fact that metal binding sites have an enormous variety in geometries and possible interactors is one of the underlying causes. Many
site geometries are too context-sensitive to reliably predict and restrain in model
renement, but there are common structural motifs around e.g. zinc, magnesium,
and sodium, that are amenable to automated model improvement. The PDB-REDO
pipeline includes a tool (platonyzer) that denes geometric restraints for structural
zinc sites (i.e. ZnCys
Hisysites as found in zinc ngers and other motifs) and octa-
x
hedral sodium and magnesium sites. The restraints impose regular geometry during renement, especially when the experimental data are weak. These restraints
can even recover the right conguration of initially extremely poorly modeled zinc
atoms [30]. The latter is reasonably often present in proteins that are targeted in drug
(a)
Figure 7.11 Extension of a glycan tree (carbon atoms in grey) by PDB-REDO in the
SARS-CoV-2 spike receptor-binding domain bound with ACE2 (grey, PDB entry 6m0j, chain
A). Electron density maps (blue) are oversampled at 0.5 for clarity, contour levels: 1.0σ for
2mF
-DFcmap, 3.5σ for difference density (red and green). (a) Model as deposited in the
o
PDB that shows unmodeled density close to NAG. (b) PDB-REDO model which contains an
extended glycan; no unmodeled density is observed.
PDB
(b)
PDB-REDO
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