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Protein-tyrosine phosphatases (PTP) are signaling
enzymes that regulate a wide variety of cellular processes,
including cell growth, differentiation, metabolism, progression
through the cell cycle, cell-cell communication, cell migration,
genetranscription, ion channel activity, the immune
response, and apoptosis/survival decisions. Defective or
inappropriate regulation of PTP activity can lead to aberrant
tyrosine phosphorylation, which contributes to the
development of many human diseases, including cancers and
diabetes. PTP1B is regarded as a major negative regulator of
both insulin- and leptin-stimulated signal transduction
pathways, which suggests that specific PTP1B inhibitors
may enhance insulin and leptin sensitivity and act as
effective therapeutics for the treatment of type 2 diabetes, insulin
resistance, and obesity. Thus, PTP1B is an attractive
candidate for the design of drugs for the treatment of type 2
diabetes and obesity.
The development of PTP1B inhibitors began in the early
1990s and continues today[1-11]. PTP1B contains one
high-affinity catalytic aryl phosphate binding site and, adjacent
to it, one low-affinity noncatalytic aryl phosphate binding
site. The active site of PTP1B is defined by residues
214-221 (P-loop, His-Cys-Ser-Ala-Gly-Ile-Gly-Arg), which binds
the aryl phosphate and contains the catalytic Cys (Cys215).
The noncatalytic aryl phosphate binding site is demarcated
by Arg24 and Arg254. It has been suggested that a
compound that simultaneously occupies both aryl phosphate
binding sites may be a potent and selective inhibitor of
PTP1B[12]. Recent results from Novo
Nordisk[13] and Abbott
Laboratories[14] demonstrated that this is indeed a viable
approach to obtaining potent and selective PTP1B inhibitors.
Other efforts aimed at targeting both the active site and the
second aryl phosphate binding site have yielded numerous
bis-aryl difluorophosphonate inhibitors that have low
mmol/L affinity and reasonable selectivity for
PTP1B[15-17]. However, some bis-aryl difluorophosphonates do not bind to PTP1B
as expected; instead, the distal phosphonate does not bind
to the second aryl phosphate-binding site but rather extends
into the solvent and is involved in water-mediated ionic
interactions with the guanidinium group of
Arg47[18]. Zhang¡¯s group acquired a highly potent and selective PTP1B
inhibitor (Figure 1; compound 1), which has a
Ki value of 2.4 nmol/L for PTP1B and exhibits several orders of magnitude of
selectivity in favor of PTP1B against a panel of
PTP[4]. Compound 1 is the most potent and selective PTP1B inhibitor
reported to date. In order to gain further insight into the
structural basis of the potency and selectivity of compound 1 for PTP1B, Zhang and colleagues intended to determine
the crystal structure of PTP1B with another compound
(Figure 1; compound 2, Ki=1.8 nmol/L), which has almost the
same potency and selectivity as compound 1. Yet the final
model (Figure 2; the complexed structure and the compound
SNA) for the PTP1B-2 complex included PTP1B residues
2-298 and all atoms in compound 2 except the
1-carbamonyl-2-mercaptoethylcarbamoyl portion in the C-terminal extension.
However, this does not affect the investigative results,
because this missing portion did not affect the affinity of ligands
for PTP1B[19].
The objective of the present study was to investigate
the structural factors responsible for the high inhibitory
potency and selectivity of inhibitor SNA using molecular
dynamics simulations. In the present paper, we simultaneously
present the 3 ns conventional molecular dynamics
simulations of PTP1B in complex with a bidentate inhibitor SNA, as
well as an uncomplexed PTP1B, with the purpose of
analyzing the interactions between target protein and ligand, and
revealing the possible mechanisms of ligand recognition and
inhibition. Most importantly, we intend to find the residues
beyond the catalytic aryl phosphate binding site that are
crucial to increasing inhibitory potency and selectivity.
Materials and methods
Simulation model For comparison, the X-ray crystal
structures of PTP1B at 2.80 Å
resolution[20] and the PTP1B complexed with a bidentate inhibitor SNA at 2.15 Å
resolution[19] were used to construct the structural models for
simulations, respectively. Both structures were obtained
from the Protein Data Bank at
Brookhaven[21]. The entry codes are 2HNP and 1PXH for the uncomplexed and
complexed PTP1B crystal structures, respectively. For the
uncomplexed PTP1B model, the residue Met1 was added by
using the molecular modeling software Sybyl
6.8[22]. By this means, the missing residues Met1-Glu4 and Gly283-Asp298
were also added to the PTP1B-SNA complex according to
the crystal structure of the uncomplexed PTP1B. The
repaired residues were subjected to energy minimization in
Sybyl 6.8, using the steepest descent method up to a
gradient tolerance of 0.05 kcal/(mol·Å) to relieve possible steric
clashes and overlaps of the side chains by fixing the
remaining part of the complex. The ionization states of all the
residues of the 2 models are set as their standard protonation
states.
Molecular dynamics simulation The molecular
dynamics (MD) simulations were performed in periodic boundary
conditions using the GROMACS program (version
3.1.4)[23,24]
with the GROMACS force field[25,26]. The molecular
topology file and force field parameters except the charges for the
inhibitor SNA were generated by the program
PRODRG[27]. The partial atomic charges of SNA were determined by using
the CHELPG method[28] implemented in the Gaussian 98
program[29] at the level of HF/6-31G*. Before MD simulations,
the uncomplexed and complexed models were solvated with
the explicit SPC water[30] embedded in 7.0 nm×6.5 nm×6.8 nm
or 7.3 nm×6.4 nm×7.2 nm boxes, respectively, in which the
minimum distance between the protein surface and the box
face was 0.8 nm in both cases. To neutralize the systems, 9
sodium ions were added to replace 9 water molecules in the
boxes. The simulation systems were composed of 29525
(2HNP) and 31969 (1PXH) atoms in total. The systems were
then subjected to a steepest descent energy minimization
until a tolerance of 100 kJ/mol, step by step. At first, all water
molecules and ions, with the whole fixed protein and inhibitor,
were energy minimized, followed by the minimization for the
protein by fixing the main-chain and Ca atoms. Finally, the
entire systems were minimized. Afterwards, the solvent
molecules were equilibrated with fixed protein at 300 K for 100
ps, taking the initial velocities from a Maxwellian distribution.
Subsequently, the equilibrations of the protein and inhibitor
were carried out for 20 ps at 10, 50, 100, 200, and 300 K. It
should be pointed out that the protein and the ligand were
fixed during the process of heating up. So the solute (ie,
protein and inhibitor) was subsequently relaxed step by step
and heated up to 300 K by using several 20 ps MD simulations. Finally, the 3 ns molecular dynamics
simulations were performed under normal temperature (300 K) and
pressure (1 bar), using a temperature coupling time constant
of 0.1 ps and a pressure coupling time constant of 1.0
ps[31]. The value of the isothermal compressibility was set to 4.5×10-5 bar-1 for water simulations. All bond lengths
including hydrogen atoms were constrained by the LINCS
algorithm[32]. The electrostatic interactions were calculated
by using the Particle-mesh Ewald (PME)
algorithm[33], with interpolation order of 4 and a grid spacing of 0.12 nm. The
cutoff for van der Waals interactions was 0.9 nm.
Simulations were performed with a time step of 2 fs, and
coordinates were saved every 1 ps.
Examinations and repairs of the molecular structures were
achieved using the Sybyl modeling program. All
simulations were carried out using the GROMACS program on a
128-processor SGI Origin3800 server. Analyses were
preformed using the features within the GROMACS package.
Results and discussion
MD trajectories Molecular dynamics simulations of the uncomplexed PTP1B structure and the PTP1B-inhibitor
complex (Figure 2) were performed using explicit SPC water and
applying periodic boundary conditions. The total energies
of both simulation models versus simulation time are shown
in Figure 3A, 3B, which gives an indication of the overall
stability of the MD trajectory. In general, the total energy of
the system decreases slightly but does not change too much
during the simulation except that the energy of the
uncomplexed structure decreases more sharply than the
complexed one in the first 80 ps. The root mean square
deviation (RMSD) from the starting structure is an important
criterion for the convergence of the protein system. The
RMSD values of all protein atoms of PTP1B and
PTP1B-inhibitor structures are shown in Figure 4, showing that the
2 simulation systems appear to have been stabilized after
1700 ps and 500 ps equilibrations, respectively. Furthermore,
as shown in Figure 4, the RMSD for the uncomplexed PTP1B
is larger than that for the complexed structure, which
indicates that the flexibility of PTP1B decreases upon binding
the ligand. This can also be confirmed by the larger
fluctuation in the radius of gyration (Figure 5) of the uncomplexed
structure relative to that of the complexed one.
Principal component analysis To support our results
and investigate the most significant collective modes of
motion occurring during the simulations of the uncomplexed
PTP1B and complexed PTP1B, the covariance matrix
corresponding to the Ca-atom coordinates was calculated and
principal component analysis (ie, essential dynamics
analysis) was performed. By diagonalizing the covariance
matrix, the anharmonic and large-scale motions of the
protein are isolated from the mostly harmonic and small-scale
motions. Because the large-scale anharmonic motions in the
essential subspace are often correlated to the vital functions
of the protein, we only focus on these movements.
The 3N eigenvalues (894 eigenvalues) of the covariance
matrix were ranked in a decreasing order of magnitude as
shown in Figure 6. As is shown, ~80% of the total positional
fluctuations are described by the first 50 eigenvectors of
both models, which is similar to the simulation result of
Peters et al[34], but different from the usual case, in which the
first 10 eigenvectors represent ~95% of the total motion for
the other protein. This indicates that the fluctuations in
PTP1B are more complicated. Although the first 50
eigenvectors account for ~80% of eigenvectors, the first 4
eigenvectors alone represent about 40% (40.5% and 36.7% for
uncomplexed and complexed PTP1B, respectively) of the
fluctuations. Thus, the displacements of the components of
the first 4 eigenvectors for uncomplexed PTP1B and
complexed PTP1B are shown in Figure 7.
It is obvious that the fluctuations of the residues of the 4
eigenvectors appear similar for uncomplexed PTP1B or the
complexed PTP1B independently. For uncomplexed PTP1B,
the significant fluctuations are localized on the residues
113-120, 128-132, 162-168, 178-185, and 234-242, as well as the
N-terminal and C-terminal regions. It is not surprising that
the significant fluctuations occur in these regions, because
they are generally located in the loop regions of the protein.
Similarly, there also exist the fluctuations in these regions
for the complexed PTP1B. But the fluctuations in residues
162-168 and 178-185 decrease. Because the WPD-loop
(178-185) moves toward the inhibitor and interacts with the
inhibitor, the fluctuation in this region decreases.
Corres-pondingly, the loop (162-168) next to the WPD-loop
fluctuates less. In contrast, the fluctuations in residues 234-242 of
the complexed PTP1B are slightly more intense than those of
the uncomplexed PTP1B. Additionally, a significant
fluctuation in residues 59-65, which are contained in a long loop far
from the ligand binding site, appears in the complexed PTP1B.
For comparing the fluctuations between uncomplexed and
complexed PTP1B more clearly, we displayed the
displacements of residues of eigenvector 1 for uncomplexed and
complexed PTP1B in one plot (Figure 8A), and those of
eigenvector 2 for both systems were drawn in another plot (Figure
8B), because the fluctuations of eigenvectors 1 and 2 are the
major motions. It can be seen from Figure 8A that ligand
binding reduces motion in residues 128-135, 162-168 and
178-185 (WPD-loop), whereas increases in fluctuations are
observed in segments 59-65 and 234-242. It is not
surprising that the fluctuation in the WPD-loop reduces once the
ligand binds, because the WPD-loop moves toward the ligand
and forms hydrophobic interactions with it, and the
flexibility of the WPD-loop reduces accordingly. Visualization of
the motions along the simulation revealed that the
WPD-loop of the complexed PTP1B remained close all the way.
Although the fluctuations in the WPD-loop of the uncomplexed PTP1B were oscillatory in nature, it was
generally open, but closed once in a while, a finding that is
consistent with previous
experimental[35] and
theoretical[34] results. This may be explained by the flexibility of the WPD-loop of
the uncomplexed PTP1B, and it may be another reason that
typical motions of peptide loops occur on a much longer
time scale (10-9 to 10-1
s)[36-41]. Compared with the fluctuations of the components of eigenvector 1, those of
eigenvector 2 have similar fluctuations, except for 2 relatively
evident differences, specifically, the decreased fluctuation in
region 114-120 and an increased fluctuation in residues 28
and 29 (Figure 8B).
General interaction between compound SNA and
PTP1B
To explore the interaction between the inhibitor SNA and the
target protein PTP1B, we calculated the energy
contributions of van der Waals and electrostatic energies. The van
der Waals and short-range electrostatic energies between
PTP1B and the inhibitor SNA and those between SNA and
the solvent during the simulation are shown in Figure 9A
and 9B, respectively. As indicated in Figure 9A (black curve),
the van der Waals energy between SNA and PTP1B during
the simulation is approximately -170 kJ/mol on average.
However, the average short-range electrostatic energy
between the SNA and PTP1B is approximately -794 kJ/mol
(Figure 9A, red curve). Because the overall electrostatic
energy between the ligand and the receptor comprises both
short-range and long-range electrostatic energy, the overall
electrostatic energy between SNA and PTP1B is doubtless
lower than -794 kJ/mol. Thus it can be concluded that the
electrostatic interaction plays a more important role in the
PTP1B-SNA interactions than the van der Waals interaction.
Indeed, previous studies have revealed that the field
surrounding the binding pocket is positive and therefore PTP1B
prefers negatively charged ligands[42]. Similarly, the
short-range electrostatic energy (average -749 kJ/mol) is lower than
the van der Waals energy (average -19 kJ/mol) between the
inhibitor SNA and the solvent (Figure 9B). Both the
ligand-solvent interaction energies are slightly higher than those
between the ligand and the protein. The comparatively
strong ligand-solvent electrostatic energy can be explained
by the ligand being partly exposed to the solvent. Our
calculated van der Waals and electrostatic energies between
SNA and the protein/solvent are basically in agreement with
those of a previous theoretical
study[42].
Yet, from Figure 9A it can be seen that there is a sudden
decrease in PTP1B-SNA electrostatic energy between 2789
ps and 2944 ps of the simulation time. What is the reason for
such a change? For the purposes of explaining this
pheno-menon, we investigated the hydrogen bonding interaction
between SNA and PTP1B.
Figure 10 shows the number of hydrogen bonds between
PTP1B and SNA during the 3 ns simulation. In general, the
number of hydrogen bonds mostly fluctuates between 14
and 17 within the simulation time, which indicates that there
are always 14-17 hydrogen bonds between SNA and PTP1B.
Figure 11 shows which hydrogen bonds exist between PTP1B
and SNA every 15 ps during the simulation. The hydrogen
bonds with indexes 1-9 are those of Lys41-SNA. Indexes
10-22 correspond to the hydrogen bonds between Arg47
and SNA. Indexes 23 and 39-43 are the hydrogen bonds
between Asp48 and SNA, and indexes 24-38 correspond to
the hydrogen bonding interactions between the residues of
PTP1B and the F2Pmp moiety of SNA. As is shown in Figure
11, the lines with indexes 25-28, 30-32, and 34 always appear
with the simulation time, indicating that the hydrogen bonds
between F2Pmp of the inhibitor and the residues of PTP1B
exist all along. Also, 2 hydrogen bonds (indexes 10 and 20)
between Arg47 and the distal phosphate of the inhibitor
exist all along. As for the hydrogen bonding interactions
between Asp48 and the linker Asp of SNA, 2 hydrogen bonds
with indexes 39 and 41 form before 1850 ps, after which
another 2 with indexes 40 and 42 appear. These hydrogen
bonds play a crucial role in determining the orientation and
configuration of ligands in binding to PTP1B. Although the
number of hydrogen bonds between the F2Pmp of SNA and
PTP1B is more than those between other regions of SNA
and PTP1B, the latter still exert fairly important roles in
locating the remaining parts of SNA. Other hydrogen bonds arise
once in a while due to the flexibilities of both the ligand and
the receptor.
From Figure 11, it can be seen that between 2789 ps and
2944 ps simulation time, the hydrogen bonds with indexes 32
and 34, which correspond to 2 hydrogen bonds between
residue Arg221 and the F2Pmp of SNA, disappear.
Meanwhile, 3 new hydrogen bonds (indexes 35, 36, and 37)
form between residue Ser222 and the F2Pmp of SNA.
Furthermore, the lengths of other hydrogen bonds become
short. All these may be the reasons for the reduction in
electrostatic energy between PTP1B and inhibitor SNA
between 2789 ps and 2944 ps. After 2944 ps, the situation
reverts as it was before 2789 ps. The interacting models
derived by the LIGPLOT program[43] of the inhibitor SNA
with PTP1B are illustrated in Figure 12A, 12B, and 12C, which
were taken from the structures with the average electrostatic
energy of each stage.
Interactions in the active site
F2Pmp of the inhibitor SNA occupies the active site of PTP1B. By visualizing the
structures of the MD simulation and monitoring the distances
of some atoms along the MD trajectory of complexed PTP1B,
we gained an insight into the interactions between
F2Pmp of the inhibitor SNA and the residues in the active site.
It can be seen clearly from the 2-dimensional
representations of the interaction model of SNA with PTP1B (Figure 12)
that the terminal phosphonate oxygens of
F2Pmp form hydrogen bonds with the backbone amides of the
phosphate-binding loop (residues 215-221) and the guanidinium side
chain of Arg221. Also, the phenyl ring of
F2Pmp is sandwiched between the side chains of Tyr46 and Phe182 and
makes the hydrophobic and van der Waals interactions with
the side chains of Ala217, Ile219, and Gln262. The
interactions described here are similar to those between the Pmp-containing inhibitor and the active site. Unique to
F2Pmp are the hydrogen bonds formed between the 2 benzylic fluorines
and the residues in the active site, which are thought to be
the reason that F2Pmp-containing inhibitors bind PTP better
than Pmp-containing inhibitors. Based on our MD trajectory,
we monitored the distances between the 2 benzylic fluorines
and the residues of PTP1B. We found that the distances
between the 2 benzylic fluorines and the main chain nitrogen
of Phe182, as well as the distance between one benzylic
fluorine (F6) and one nitrogen atom (NH2) of the guanidinium
group of Arg221, were in general smaller than 0.4 nm, except
at the starting stage of the MD simulation and at 2789-2944
ps (Figure 13). These results indicate that there exist
hydrogen bonds between the 2 benzylic fluorine atoms of SNA
and the main chain nitrogen of residue Phe182, and a third
hydrogen bond is also formed between one benzylic
fluorine (F6) and the NH2 atom of the guanidinium group of
Arg221.
Interactions between SNA and PTP1B beyond the active
site Because the interactions between the
F2Pmp of an inhibitor and the active site of PTP1B have been extensively
investigated previously and, moreover, because the
interactions between the remainder of SNA and PTP1B (Figure 12)
beyond the active site appear crucial in increasing inhibitory
potency and selectivity, we therefore put emphasis on
discussion of the interactions of SNA with PTP1B beyond the
active site. From the interaction modes at 3 particular times
(Figure 12), we know that the residues Lys41, Arg47, and
Asp48 are important. To confirm which interactions exist all
along and which are the most important, we monitored the
distances of atoms of SNA from residues Lys41, Arg47, and
Asp48 as a function of simulation time.
According to the distances between Arg47 and SNA
atoms, it was found that a hydrogen bond between the main
chain nitrogen of Arg47 and the carbonyl of the distal 4-phosphonodifluoromethylphenylacetyl group always exists during the simulation, which can also be confirmed by
previous results (index 10 of Figure 11 and 12). Also, the
nitrogen atoms of the guanidinium group of Arg47 form
hydrogen bonds with the Asp side chain of SNA. In addition,
there is a polar interaction between a fluorine atom of the
distal difluorophosphonate group and the guanidinium group
of Arg47. It should be noted that because of the high
flexibility of the side chain of Arg47, the bond CD-CG (Figure 12)
rotates at 2030 ps and thus the Arg47NH1-F polar
interaction disappears and the Arg47NH2-F polar interaction arises.
All these interactions of Arg47 with SNA are consistent with
the experimental results[19]. Furthermore, due to the rotation
of the CD-CG bond, the guanidinium group turned, and the
NH2 atom of the guanidinium group approached one
oxygen atom of the distal phosphate of SNA, forming a
hydrogen bond after 2030 ps (Figure 14).
As is shown in Figure 12, there exists a hydrogen bond
between one oxygen atom of the side chain of Asp48 and the
main chain nitrogen of F2Pmp of SNA, a finding that is in
agreement with experimental data[19]. However, another
hydrogen bond, which was proposed to form between Asp48
and the C-terminal amide of F2Pmp, is not present in Figure
12. In order to determine if the second hydrogen bond exists,
we monitored the distance between the side chain oxygen of
Asp48 and the C-terminal amide of F2Pmp. The distances
between the OD1 or OD2 of Asp48 and N18 of the C-terminal
amide of SNA are shown in Figure 15A and 15B, respectively,
which indicate that such a hydrogen bond does not exist,
because the distances are mostly larger than 0.4 nm during
the simulation.
As for the third important surface residue of PTP1B,
Lys41, 2, or 3 hydrogen bonds are present between the amino
group of Lys41 and the phosphonate oxygen atoms. The
number of hydrogen bonds based on our simulation is more
than that (one hydrogen bond) suggested by experimental
data[19]. On the other hand, the polar interaction suggested
by the experiment was not found in our simulation.
Considering the number and distribution of hydrogen
bonds for Lys41, Arg47, and Asp48, we predict that Arg47
plays the most important role in inhibitory potency and
selectivity. However, to evaluate these contributions, a
detailed calculation of the free energy change during binding
has to be performed, which may be carried out later.
In addition to the hydrogen bonding interactions and
polar interactions, there are also some hydrophobic
interactions that are shown in Figure 12. It is evident that the
hydrophobic interactions are less strong than the other
interactions, so we will not describe them in detail, because
they do not predominate. However, we should comment on
the hydrophobic interactions associated with the aliphatic
chain of SNA, which are the only interactions with that chain.
These come from the aliphatic portions of the side chains of
Asp48 and Gln262. They are too weak to restrict the location
of the aliphatic chain of SNA. Therefore, the aliphatic chain
of SNA swings acutely during the simulation, which causes
other parts of SNA to move to some extent.
Conclusion
The 3 ns molecular dynamics (MD) simulations on
uncomplexed and complexed PTP1B were carried out with
the aim of revealing the possible mechanisms of ligand rec
ognition and inhibition. Based on our dynamics simulation
and conformation analysis, many useful results were
obtained. First, upon binding the ligand, the flexibility of the
entire PTP1B molecule decreases. The most notable change
is the movement of the WPD-loop, which moves toward the
inhibitor and forms hydrophobic interaction with it, and the
flexibility of the PTP1B molecule reduces accordingly.
Second, according to our calculated van der Waals and
electrostatic energies between PTP1B and the inhibitor SNA, it
is evident that the electrostatic interaction contributes more
to PTP1B-SNA complex conformation than the van der Waals
interaction. This result is consistent with those of previous
studies. Third, by analyzing the interactions between PTP1B
and the high-affinity inhibitor SNA, it was found that the
residues adjacent to the active site, including Lys41, Tyr46,
Arg47, and Asp48, might be partially responsible for the high
inhibitory activity and selectivity of SNA. Moreover, the
residue Arg47 may be the most important determinant for
PTP1B potency and selectivity among these 4 surface
residues. Our results confirmed the experimental data,
although the details of several PTP1B-SNA interactions
beyond the active binding site are not completely in agreement
with the experimental findings.
Our simulation results suggest that potent and selective
PTP1B inhibitors may be designed by targeting the surface
residues, for example the region containing Lys41, Arg47,
and Asp48, instead of the second phosphate binding site
(besides the active phosphate binding site). Perhaps the
strategy of developing inhibitors by targeting not only both
of the phosphate binding sites but also the adjacent
peripheral sites is also feasible if the inhibitors are not too large to
be absorbed.
References
1 Ripka WC. In: Doherty AM, editor. Annual Reports in
medicinal chemistry, volume 35. San Diego, CA: Academic Press; 2000.
p 231-50.
2 Johnson TO, Ermolieff J, Jirousek M. Protein tyrosine
phosphatase 1B inhibitors for diabetes. Nat Rev Drug Discovery
2002; 1: 696-709.
3 Blaskovich MA, Kim HO. Recent discovery and development of
protein tyrosine phosphatase inhibitors. Expert Opin Ther Pat
2002; 12: 871-905.
4 Shen K, Keng YF, Wu L, Guo XL, Lawrence DS, Zhang ZY.
Acquisition of a specific and potent PTP1B inhibitor from a
novel combinatorial library and screening
procedure. J Biol Chem 2001; 276: 47311-9.
5 Xie J, Seto CT. Investigations of linker structure on the potency
of a series of bidentate protein tyrosine phosphatase inhibitors.
Bioorg Med Chem 2005; 13: 2981-91.
6 Dixit M, Tripathi BK, Srivastava AK, Goel A. Synthesis of
functionalized acetophenones as protein tyrosine phosphatase
1B inhibitors. Bioorg Med Chem Lett 2005; 15: 3394-7.
7 Shim YS, Kim KC, Lee KA, Shrestha S, Lee KH, Kim CK,
et al. Formylchromone derivatives as irreversible and selective
inhibitors of human protein tyrosine phosphatase 1B. Kinetic and
modeling studies. Bioorg Med Chem 2005; 13: 1325-32.
8 Ockey DA, Gadek TR. Discovery of novel PTP1b inhibitors.
Bioorg Med Chem Lett 2004; 14: 389-91.
9 Zhao HY, Liu G, Xin ZL, Serby MD, Pei ZH, Szczepankiewicz
BG, et al. Isoxazole carboxylic acids as protein tyrosine
phosphatase 1B (PTP1B) inhibitors. Bioorg Med Chem Lett 2004;
14: 5543-6.
10 Patankar SJ, Jurs PC. Classification of inhibitors of protein
tyrosine phosphatase 1B using molecular structure based
descriptors. J Chem Inf Comput Sci 2003; 43: 885-99.
11 Zhang ZY, Lee SY. PTP1B inhibitors as potential therapeutics
in the treatment of type 2 diabetes and obesity. Expert Opin
Investig Drugs 2003; 12: 223-33.
12 Puius YA, Zhao Y, Sullivan M, Lawrence DS, Almo SC, Zhang
ZY. Identification of a second aryl phosphate-binding site in
protein-tyrosine phosphatase 1B: a paradigm for inhibitor design.
Proc Natl Acad Sci USA 1997; 94: 13420-5.
13 Iversen LF, Andersen HS, Moller KB, Olsen OH, Peters GH,
Branner S, et al. Steric hindrance as a basis for structure-based
design of selective inhibitors of protein-tyrosine
phosphatases. Biochemistry 2001; 40: 14812-20.
14 Liu G, Trevillyan JM. Protein tyrosine phosphatase 1B as a
target for the treatment of impaired glucose tolerance and type
II diabetes. Curr Opin Investig Drugs 2002; 3: 1608-16.
15 Taing M, Keng YF, Shen K, Wu L, Laqrence DS, Zhang ZY.
Potent and highly selective inhibitors of the protein tyrosine
phosphatase 1B. Biochemistry 1999; 276: 3793-803.
16 Taylor SD, Kotoris CC, Dinaut AN, Wang Q, Ramachandran C,
Huang Z. Potent non-peptidyl inhibitors of protein tyrosine
phosphatase 1B. Bioorg Med Chem 1998; 6: 1457-68.
17 Desmarais S, Friesen RW, Zamboni R, Ramachandrn C.
[Difluro(phosphono)methyl]phenylalanine-containing peptide inhibitors
of protein tyrosine phosphatases. Biochem J 1999; 337:
219-23.
18 Jia Z, Ye Q, Dinaut AN, Wang Q, Waddleton D, Payette P,
et al. Structure of protein tyrosine phosphatase 1B in complex with
inhibitors bearing two phosphotyrosine
mimetics. J Med Chem 2001; 44: 4584-94.
19 Sun JP, Fedorov AA, Lee Y, Guo XL, Shen K, Lawrence DS,
et al. Crystal structure of PTP1B complexed with a potent and
selective bidentate inhibitor. J Biol Chem 2003; 278: 12406-14.
20 Barford D, Flint AJ, Tonks NK. Crystal structure of human
protein tyrosine phosphatase 1B. Science 1994; 263:
1397-404.
21 Bernstein FC, Koetzle TF, Williams GJB, Meyer EF, Brice MD,
Roger JR, et al. The Protein Data Bank: a computer based
archival file for macromolecular structure. J Mol Biol 1977;
112: 535-42.
22 Sybyl [molecular modeling package], version 6.8. St Louis, MO:
Tripos Associates; 2000.
23 Berendsen HJC, van der Spoel D, van Drunen R. GROMACS: a
message-passing parallel molecular dynamics implementation.
Comp Phys Commun 1995; 91: 43-56.
24 van der Spoel D, van Buuren AR, Apol E, Meulenhoff PJ,
Tieleman DP, Sijbers AL, et al. Gromacs User Manual, Version
3.1. Nijenborgh, The Netherlands: Groningen University; 2002.
25 van der Spoel D, van Buuren AR, Tieleman DP, Berendsen HJ.
Molecular dynamics simulations of peptides from BPTI: a closer
look at amide-aromatic interactions. J Biomol NMR 1996; 8:
229-38.
26 van Gunsteren WF, Berendsen HJ. Gromos-87 manual.
Nijenborgh, The Netherlands: Biomos BV; 1987.
27 Van Aalten DMF, Bywater R, Findlay JBC, Hendlich M, Hooft
RWW, Vriend G. PRODRG, a program for generating molecular
topologies and unique molecular descriptors from coordinates of
small molecules. JCAMD 1996; 10: 255-62.
28 Breneman CM, Wiberg KB. Determining atom-centered
monopoles from molecular electrostatic potentials. The need for high
sampling density in formamide conformational analysis. J Comp
Chem 1990; 11: 361-97.
29 Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA,
Cheeseman JR, et al. Gaussian 98, revision A.3. Pittsburgh, PA:
Gaussian Inc; 1998.
30 Berendsen HJC, Postma JPM, van Gunsteren WF, Hermans J.
Interaction models for water in relation to protein hydration.
In: Pullman B, editor. Intermolecular forces. Dordrecht, The
Netherlands: D Reidel Publishing Company; 1981. p 331-342.
31 Berendsen HJC, Postma JPM, DiNola A, Haak JR. Molecular
dynamics with coupling to an external bath. J Chem Phys 1984;
81: 3684-90.
32 Hess B, Bekker H, Berendsen HJC, Fraaije JGEM. LINCS: a
linear constraint solver for molecular simulations. J Comp Chem
1997; 18: 1463-72.
33 Darden T, York D, Pedersen L. Particle mesh Ewald: an
N·log(N) method for Ewald sums in large systems. J Chem Phys 1993;
98: 10089-92.
34 Peters GH, Frimurer TM, Andersen JN, Olsen OH. Molecular
dynamics simulations of protein-tyrosine phosphatase 1B. I.
ligand-induced changes in the protein motions. Biophys J 1999;
77: 505-15.
35 Lohse DL, Denu JM, Santoro M, Dixon JE. Roles of aspartic
acid-181 and serine-222 in intermediate formation and
hydrolysis of the mammalian protein-tyrosine-phosphatase PTP1.
Biochemistry 1997; 36: 4568-75.
36 Wade RC, Davis ME, Luty BA, Madura JD, McCammon JA.
Gating of the active site of triose phosphate isomerase:
Brownian dynamics simulations of flexible peptide loops in the enzyme.
Biophys J 1993; 64: 9-15.
37 Wade RC, Luty BA, Demchuk E, Madura JD, Davis ME, Briggs
JM, et al. Simulation of enzyme-substrate encounter with gated
active sites. Nature Struct Biol 1994; 1: 63-67.
38 Kempner ES. Movable lobes and flexible loops in proteins. FEBS
Lett 1993; 326: 4-10.
39 Philippopoulos M, Xiang Y, Lim C. Identifying the mechanism
of protein loop closure: a molecular dynamics simulation of the
Bacillus stearothermophilus LDH loop in solution. Protein Eng
1995; 8: 565-73.
40 Falzone CJ, Wright PE, Benkovic SJ. Dynamics of a flexible
loop in dihydrofolate reductase from Escherichia
coli and its implication for catalysis. Biochemistry 1994; 33: 439-42.
41 Williams JC, MacDermott AE. Dynamics of the flexible loop of
triosephosphate isomerase: the loop motion is not ligand gated.
Biochemistry 1995; 34: 8309-19.
42 Peters GH, Frimurer TM, Andersen JN, Olsen OH. Molecular
dynamics simulations of protein-tyrosine phosphatase 1B. II.
Substrate-enzyme interactions and dynamics. Biophys J 2000;
78: 2191-200.
43 Wallace AC, Laskowski RA, Thornton JM. LIGPLOT: a
program to generate schematic diagrams of protein-ligand
interactions. Protein Eng 1995; 8: 127-34.
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