Yilin Meng1, Yen-lin Lin, Benoît Roux. 1. Department of Biochemistry and Molecular Biology, The University of Chicago , 929 E. 57th Street, Chicago, Illinois, 60637, United States.
Abstract
Protein tyrosine kinases are crucial to cellular signaling pathways regulating cell growth, proliferation, metabolism, differentiation, and migration. To maintain normal regulation of cellular signal transductions, the activities of tyrosine kinases are also highly regulated. The conformation of a three-residue motif Asp-Phe-Gly (DFG) near the N-terminus of the long "activation" loop covering the catalytic site is known to have a critical impact on the activity of c-Abl and c-Src tyrosine kinases. A conformational transition of the DFG motif can switch the enzyme from an active (DFG-in) to an inactive (DFG-out) state. In the present study, the string method with swarms-of-trajectories was used to computationally determine the reaction pathway connecting the two end-states, and umbrella sampling calculations were carried out to characterize the thermodynamic factors affecting the conformations of the DFG motif in c-Abl and c-Src kinases. According to the calculated free energy landscapes, the DFG-out conformation is clearly more favorable in the case of c-Abl than that of c-Src. The calculations also show that the protonation state of the aspartate residue in the DFG motif strongly affects the in/out conformational transition in c-Abl, although it has a much smaller impact in the case of c-Src due to local structural differences.
Protein tyrosine kinases are crucial to cellular signaling pathways regulating cell growth, proliferation, metabolism, differentiation, and migration. To maintain normal regulation of cellular signal transductions, the activities of tyrosine kinases are also highly regulated. The conformation of a three-residue motif Asp-Phe-Gly (DFG) near the N-terminus of the long "activation" loop covering the catalytic site is known to have a critical impact on the activity of c-Abl and c-Src tyrosine kinases. A conformational transition of the DFG motif can switch the enzyme from an active (DFG-in) to an inactive (DFG-out) state. In the present study, the string method with swarms-of-trajectories was used to computationally determine the reaction pathway connecting the two end-states, and umbrella sampling calculations were carried out to characterize the thermodynamic factors affecting the conformations of the DFG motif in c-Abl and c-Src kinases. According to the calculated free energy landscapes, the DFG-out conformation is clearly more favorable in the case of c-Abl than that of c-Src. The calculations also show that the protonation state of the aspartate residue in the DFG motif strongly affects the in/out conformational transition in c-Abl, although it has a much smaller impact in the case of c-Src due to local structural differences.
Protein tyrosine kinases
are crucial functional elements of cellular
signaling pathways regulating cell growth, proliferation, metabolism,
differentiation and migration. In their active state, tyrosine kinases
catalyze the transfer of γ-phosphate of an adenosine triphosphate
(ATP) molecule covalently onto a tyrosine residue in substrate proteins
and peptides. To maintain normal regulation of cellular signal transductions,
the activity of tyrosine kinases is tightly regulated.[1−6] Mutations of certain residues can disrupt normal inhibitory mechanisms
and make tyrosine kinases constitutively active, leading to a number
of diseases, particularly cancers.[7−9] For this reason, kinases
represent attractive drug targets for certain types of cancers.[3,10−12] Designing inhibitors that are targeting specific
tyrosine kinases in the active state is, however, difficult because
they all present structurally similar catalytic pockets[13] owing to the common enzymatic function requiring
ATP binding. Inhibitors that are targeting inactive conformations
of the kinases appear to be more selective.[11] One notable example of inhibitors targeting an inactive state of
tyrosine kinases is Gleevec (Novartis). Gleevec is used to treat chronic
myeloid leukemia (CML), which is caused by Bcr-Abl kinase.[14−16] It is also a potent inhibitor of receptor tyrosine kinasePDGFR
and c-Kit.[11,17]As is observed in the X-ray
crystallographic structures of c-Abl
in complex with Gleevec, the conformation of a three-residue motif
comprising Asp381-Phe382-Gly383 (DFG, c-Abl 1a numbering) near the
N-terminus of the activation (A-) loop covering the catalytic side
is critical for Gleevec binding.[16,18,19] Gleevec only binds a particular conformation called
DFG-out in which the DFG motif is flipped by almost 180° relative
to the standard active conformation (DFG-in). The conformation change
alters the local shape of the binding pocket, creating more space
to accommodate Gleevec. The conformation of the DFG motif is also
an important component of the overall regulatory mechanisms for c-Abl
kinase.[6,20,21] In the active
state, the DFG motif is involved in catalysis by coordinating the
binding of magnesium ions through its aspartate residue.[5] In the DFG-out conformation, the aspartate residue
points away from the active site, resulting in a loss of coordination
with magnesium ions. Furthermore, the DFG-out conformation also correlates
with a disruption of the structural integrity of the hydrophobic spines,
which are critical element of an active catalytically competent kinase.[12,22,23] In the DFG-out conformation,
the side chain of Phe382 occupies the active site, which disrupts
ATP binding. Hence, DFG-flip not only disassembles the regulatory
(R-) spine but also breaks the catalytic (C-) spine. The X-ray crystallographic
structure of the down-regulated state of c-Abl kinase displays a DFG
motif in the out conformation.[20,21] Besides being observed
in protein tyrosine kinases, the conformational change has also been
noted in serine/threonine kinases as well (e.g., in B-Raf[24]), which highlights its importance in the protein
kinase domain activation/deactivation.The remarkable effectiveness
of Gleevec raised the hope that one
might be able to develop novel cancer treatments by designing a variety
of specific kinases inhibitors. However, the situation is complicated
by the fact that Gleevec displays a much lower inhibitory effect on
c-Src, even though these two kinases display a high level of sequence
identity (47%) and similar structural scaffolds (active conformation
of the kinase domains shown in Figure S1).[25] A simple conformational selectivity
mechanism was proposed to account for the difference in Gleevec binding
based on the assumption that c-Src cannot adopt the DFG-out conformation.
Indeed, unlike c-Abl kinase, the X-ray crystallographic structure
of the down-regulated (autoinhibited) state demonstrates that c-Src
still adopts the DFG-in conformation.[26] The autoinhibition in c-Src kinase domain comes from the outward
rotation of the αC-helix, which breaks the R-spine and a catalytically
important salt-bridge, and from the partially folded (“closed”)
conformation of the A-loop which occludes both binding of substrates
and exposing tyrosine 416 (chickenc-Src numbering). However, a subsequent
discovery of c-Src kinase structures in complex with Gleevec and several
other inhibitors in which the DFG motif is in the “out”
conformation clearly demonstrates that this state is accessible.[25,27,28] Therefore, it seems likely that
the inactive DFG-out conformation is a genuine aspect of the regulatory
mechanism for these kinases. Then, interesting questions such as what
is (are) the difference(s) between DFG-flips in c-Abl and c-Src, whether
DFG-flip is a competing mechanism that controls the activation of
c-Src, and whether there are multiple pathways for DFG-flip that would
naturally arise. A better understanding of DFG-flips in c-Abl and
c-Src kinases may improve our understanding of kinase regulations
and may guide the design of novel kinase inhibitors.The DFG-flip
conformational transition has been the subject of
several computational studies.[29−36] Shan et al. investigated the DFG-flip in c-Abl kinase using long
unbiased molecular dynamics (MD) simulations.[32] A notable result from these simulations was the suggestion that
the protonation state of Asp381 in the DFG motif could serve to promote
the in/out conformational transition. Experiments designed to test
this idea showed that the binding kinetics of Gleevec to Abl was indeed
pH dependent, in apparent accord with the proposed mechanism. However,
the equilibrium binding free energy of Gleevec measured experimentally
appeared to remain unaffected by pH, in contradiction with the computational
results. It was concluded that the protonation state of Asp381 serves
as a switch that controls the transition rate without affecting the
thermodynamics of Gleevec binding. In another study, Simonson and
Aleksandrov calculated the relative binding free energies of Gleevec
to DFG-out conformations of c-Abl, c-Src, and other kinases using
alchemical free energy perturbation molecular dynamics (FEP/MD) simulations
and the molecular mechanics Poisson–Boltzmann with surface
area (MM/PBSA) method.[29] By observing similar
relative binding free energies for c-Abl and c-Src, they inferred
that the relative stability of the DFG-out conformation in c-Abl and
c-Src should be responsible for the difference in Gleevec binding
specificity. Subsequently, Lovera et al. calculated a free energy
landscape of the DFG-flip transition in c-Abl and c-Src using meta-dynamics
MD simulations with explicit solvent.[31] The free energies for the DFG-flip from these simulations based
on the AMBER force field were 4.0 and 6.0 kcal/mol in Abl and c-Src,
respectively. Combining computational investigation with isothermal
titration calorimetry, they concluded that the better inhibitory effect
of Gleevec on c-Abl was mainly caused by an easier accessibility of
the DFG-out conformation in c-Abl compared to c-Src. In addition,
their free energy landscape of c-Abl demonstrated large conformational
flexibility and hence supported a conformational selection mechanism
for Gleevec binding. They also estimated the pKa values for c-Abl and c-Src for both the DFG-in and DFG-out
by extracting protein snapshots taken from the meta-dynamics trajectories
and feeding the latter into the program PROPKA (solvent molecules
were discarded).[31] This mixed MD/PROPKA
approach yielded pKa values of 3.4, for
c-AblDFG-in, 4.4 for c-AblDFG-out, 4.0 for c-SrcDFG-in, and 2.6
for c-SrcDFG-out. More recently, Lin et al. reported a complete calculation
of the binding affinity of Gleevec for Abl and c-Src based on methodology
combining alchemical free energy perturbation (FEP) and potential
of mean force (PMF) umbrella sampling simulations with explicit solvent
molecules.[36] The free energies for the
DFG-flip from these simulations based on the CHARMM force field were
1.4 and 5.4 kcal/mol in Abl and c-Src, respectively. Although considerable
efforts have been devoted to understand the conformational transition
of the DFG motif, the impact of the protonation state of the aspartic
residue on the free energy surface associated with the conformational
transition has not been elucidated.In the present study, we
try to address these questions by determining
the conformational transition pathways of the DFG motif in c-Abl and
c-Src kinase domain and characterizing the effect of protonation of
Asp381 (Asp404) on DFG-flips. A special attention is given to the
existence of multiple transition pathways. In order to evaluate the
role of DFG-flip in the activation/deactivation of c-Src kinase domain,
we put these results within the broader context of the conformational
changes involving the αC-helix and the A-loop in c-Src. Free
energy landscapes for c-Abl (with Asp381 unporotonated and protonated)
and c-Src (with Asp404 unprotonated and protonated) were calculated
using two-dimensional (2D) umbrella sampling (US) simulations. As
a comparison, we also calculated the free energy landscape associated
with the movement of the αC-helix and the A-loop. To facilitate
the convergence of US simulations and to reduce the computational
cost, the string method with swarms-of-trajectories calculations,
was carried out prior to US calculations. With the help of the minimum
free energy pathways (MFEPs) determined by the string method, US windows
can be initiated in well-relaxed starting configurations for optimal
computational efficiency.
Theory and Methods
Simulation Systems
DFG-in and DFG-out conformations
of c-Abl kinase domain were prepared based on PDB entry 2F4J(37) and 1OPK,[21] respectively. For the sake of simplicity,
only the kinase domain was considered and the regulatory domains were
not included in any of the simulation conducted in this paper. Both
crystal structures contain one mutation to the wild-type protein.
The mutated residue in each structure was mutated back to the corresponding
wild-type sequence. Hydrogen atoms were built to the crystallographic
structures using the HBUILD module of CHARMM.[38,41] The all-atom structures were then solvated in a truncated octahedral
solvent box constructed from an 86 × 86 × 86 Å3 cube with 13 688 TIP3P water molecules.[39] 45 K+ ions and 34 Cl– ions were added to the system to make it charge neutral, corresponding
to a salt concentration of approximately 150 mM. Any ligand or inhibitor
was removed from those crystal structures. No ATP or magnesium ions
were added to the active site because the DFG motif clashes with ATP
in the DFG-out conformation. The entire solvated c-Abl system comprised
about 45 000 atoms. DFG-in and DFG-out conformations of c-Src
kinase domain were prepared based on PDB entries 1Y57(40) and 2OIQ,[25] respectively. The missing part of
the A-loop in 2OIQ was built based on 1Y57. Hydrogen atoms were added to the initial structures using the HBUILD
module of CHARMM.[41] The all-atom structures
were then solvated in a truncated octahedral solvent box constructed
from a 80 × 80 × 80 Å3 cube with 11 216
TIP3P water molecules.[39] 22 Na+ ions and 19 Cl– ions were added to the system
to neutralize the total charge of the system and to simulate a salt
concentration of approximately 150 mM. As in the preparation of c-Abl
structures, any ligand or inhibitor was removed from crystal structures.
The final c-Src system contained approximately 40 000 atoms.
Figure 1 illustrates representatives of the
DFG-in active conformation and the DFG-out inactive conformation of
c-Abl. The DFG-in and DFG-out conformations of c-Src are similar to
those of c-Abl and are not shown. In the above atomic systems, the
aspartate residue in the DFG motif is deprotonated. In order to understand
how the protonation state of this specific residue affects DFG-flip,
we also protonated the aspartate residue for each existing atomic
system. One positive ion was removed from each system in order to
maintain the charge neutrality.
Figure 1
Crystal structures of c-Abl kinase domain.
(A) DFG-in conformation
(PDB code 2F4J). The side chain of Asp381 is pointing toward the active site. (B)
DFG-out conformation (PDB code 1OPK). In this conformation, the side chain
of Asp381 is pointing away from the active site. In both conformations,
the phosphate-binding (P-) loop (residues 248–257, c-Abl 1a
numbering), αC-helix (residues 280–294), and activation
(A-) loop (residues 381–402) are colored in green, yellow,
and orange, respectively.
Crystal structures of c-Abl kinase domain.
(A) DFG-in conformation
(PDB code 2F4J). The side chain of Asp381 is pointing toward the active site. (B)
DFG-out conformation (PDB code 1OPK). In this conformation, the side chain
of Asp381 is pointing away from the active site. In both conformations,
the phosphate-binding (P-) loop (residues 248–257, c-Abl 1a
numbering), αC-helix (residues 280–294), and activation
(A-) loop (residues 381–402) are colored in green, yellow,
and orange, respectively.An alternative conformational change based on the autoinhibitory
conformation of c-Src was also considered and compared with the DFG-flip.
To accomplish that, the inactive and active conformations of c-Src
kinase domain were prepared based on PDB entries 2SRC(26) and 1Y57,[40] respectively. Since the DFG motif
did not flip in this case, an ATP molecule and two magnesium ions
were added to the active site. The solvated systems contain the same
number of water molecules and ions and have the same shape and size
as described in the deprotonated c-Src system. c-Src kinase domain
in its active and inactive conformations is presented in Figure 2.
Figure 2
Kinase domain of c-Src in the down-regulated (colored
in blue,
PDB code 2SRC) and active (color in yellow, PDB code 1Y57) conformation. The E310 (chicken c-Src
numbering) in the αC helix is shown to demonstrate the movement
of the αC helix. E310 is pointing outward in the inactive conformation,
whereas it is pointing inward in the active-like conformation. The
A-loop is partially folded in the inactive kinase, but it becomes
fully extended in the active-like conformation.
Kinase domain of c-Src in the down-regulated (colored
in blue,
PDB code 2SRC) and active (color in yellow, PDB code 1Y57) conformation. The E310 (chickenc-Src
numbering) in the αC helix is shown to demonstrate the movement
of the αC helix. E310 is pointing outward in the inactive conformation,
whereas it is pointing inward in the active-like conformation. The
A-loop is partially folded in the inactive kinase, but it becomes
fully extended in the active-like conformation.All energy minimization and MD propagations (including string
method
and umbrella sampling calculations) were performed using version 2.7
of the molecular simulation package NAMD[42] and the CHARMM27 force field.[43] The isobaric–isothermal
ensemble was employed for all MD calculations. The pressure and temperature
were controlled by the Langevin piston method[44] and Langevin dynamics and kept at 1 atm pressure and 300 K, respectively.
Periodic boundary conditions were applied and particle mesh Ewald
(PME)[45] was used to treat long-range nonbonded
interactions. The short-range nonbonded interactions were truncated
at 12 Å, with a switching function turned on from 10 to 12 Å.
The nonbonded list was updated at every MD step with a cutoff distance
of 16 Å. Covalent bonds involving hydrogen atoms were constrained
at their equilibrium distances.[46]The solvated DFG-in and DFG-out systems were initially subjected
to energy minimization of 200 steps using steepest descent algorithm.
Next, they were equilibrated using the following procedures: each
system was first equilibrated with harmonic restraint (force constant
is 1 kcal/(mol·Å2)) on all the non-hydrogen atoms
for 200 ps, then only on Cα atoms for 300 ps, and further equilibrated
for another 2 ns without any restraint. The stability of each solvated
protein system was monitored by the fluctuation of the root-mean-square
deviation (rmsd) of Cα atoms relative to the corresponding crystal
structure during the 2 ns of MD equilibration process (see Figure S2). Each system had shown a plateau around
1.5 Å. Thus, our simulation protocol of equilibration was able
to maintain the overall structures. The resulting structures (final
snapshots) were used as the end-points in string method calculations.
String Method with Swarms-of-Trajectories Calculations
Even
though a direct measurement of the time-scale of DFG-flip in
either c-Abl or c-Src is lacking, nuclear magnetic resonance spectroscopy
of DFG-flip in mitogen-activated protein kinases (MAPK) p38α
suggested a time-scale of millisecond.[47] This time-scale suggests that studying DFG-flip with brute force
MD appears impractical. To overcome this time-scale gap, the string
method with swarms-of-trajectories[48] was
employed in our study. The string method with swarms-of-trajectories
aims to discover the MFEP connecting two stable conformations in a
space defined by a set of “collective variables” (CVs).[48,49] In this method, a pathway (string) is represented by a parametrized
curve z(i), where i = 0 is the starting state and i = 1 is the ending
state. In practice, the curve is discretized into a “chain
of images”, representing configurations along the transition
pathway. The average drift for an ensemble (swarm) of unbiased short
trajectories is calculated. Each image is refined until the “dynamical
propagation” is such that each image evolves only along the
pathway on average. The propagation–refinement process is iterated
until the MFEP is found. A more detailed description of the methodology,
realization, and how to compute a free energy profile along a string
with mean force calculation is given in Supporting
Information. The CVs that were utilized to characterize DFG-flip
are given in Table S1. For both c-Abl and
c-Src, two end-points obtained from the structural relaxation stage
were used to generate an initial string, via targeted MD (TMD). In
both cases, the DFG-out conformation was chosen to be the “target”.
Instead of application of a harmonic restraint on the rmsd with reference
to the DFG-out structure, a weak harmonic restraint on the non-hydrogen
atoms was used so that the TMD would converge faster. TMD simulations
were carried out for 10 ps with a force constant of 1 kcal/(mol·Å2). Twenty-nine snapshots were extracted from each TMD simulation
such that those configurations in a string were approximately equally
distant in the CV space. Therefore, each string consists of a total
of 31 images, where image 0 represents the DFG-in conformation and
image 30 is the DFG-out conformation.Using string method in
practice still requires caution because it requires an initial pathway
obtained from targeted MD or steered MD calculation. The effect of
the unphysical biasing force is always a concern for the transition
pathways generated by those methods.[50] Applying
to complicated free energy landscape, string method calculations may
not yield the global MFEP or may miss one or more important pathways.
The problem regarding multiple pathways might be especially severe
when there are competing pathways. In fact, all methods based on pathways
are susceptible to the issue of multiple pathways. To address the
issue of multiple possible pathways in string method, four pathways
were considered when studying DFG-flip in c-Abl. There were two possible
directions (clockwise or counterclockwise) to “flip”
either the aspartate or the phenylalanine residue in the dihedral
angle space. Thus, a total of four different combinations could be
found to achieve “in” to “out” transition.
Each one of the four combinations corresponds to one possible pathway.
The labels of those four possible pathways and their corresponding
rotations can be found in Table S2. Pathway
1 was obtained from the TMD calculation mentioned above. Another nine
TMD simulations were launched with different initial velocities. Those
TMD simulations could only generate one new pathway: pathway 4. Therefore,
pulling simulations in dihedral angles were required to produce initial
strings of pathways 2 and 3. In a pulling simulation, a harmonic biasing
potential with its center changing as θ(t) = θ(α=0) + [θ(α=1)
– θ(α=0)]·t/ts, where t was the actual time in simulation, ts was the total pulling time, and α was
the parameter described in the string method algorithm, was applied
on each dihedral angle. The pulling in dihedral angles were performed
for 10 ps with a force constant of 500 kcal/(mol·rad2).All strings were iterated following the five-step procedure
that
is described by Pan et al.[48] For each of
the 31 images, a swarm of 20 unbiased MD trajectories was launched
with different seed to randomize initial velocity; each lasted 5 ps
in length. Then the trajectories in a swarm were averaged to provide
an updated image. Once this averaging was completed for all the images,
the string was smoothed, reparametrized, and relaxed for 200 ps. The
resulting structures were then averaged, followed by smoothing, reparametrization,
and equilibration. Except for pathway 2 (reason explained later) of
c-Abl, each string was iterated 50 times. The convergence of string
iterations (displayed in Figure S3) was
monitored by examining the Euclidean distance in CV space of an image
relative to the corresponding image in the initial string, as a function
of iteration index. In both systems, strings gradually evolved away
from the initial one and stabilized. To further confirm convergence,
the same measure relative to the string at iteration 50 (final iteration)
was also applied. As expected, plateaus were also found near iteration
50 for each pathway. This behavior suggests that the last a few iterations
were close to convergence. The converged strings were then used to
initiate the US simulations for optimal computational efficiency.
Umbrella Sampling Calculations
The PMF along one or
more order parameters (ξ) is a central quantity when exploring
conformational transitions such as the DFG-flip. It illustrates the
free energy landscape that governs the conformational transition.
US[51] simulations are often employed to
generate PMFs. All-atom umbrella sampling simulations have been performed
previously to elucidate activation mechanisms of Src-family kinases
in the view of free energy landscapes. Results from those calculations
indicate that utilizing umbrella sampling method to explore kinase
conformational equilibrium is feasible. In this study, we performed
2D US calculations to study the DFG-flip conformational transition
in c-Abl and c-Src kinases. Two dihedral angles were utilized as order
parameters in order to characterize the flip of aspartate and phenylalanine
residues. A harmonic biasing potential with a force constant of 0.02
kcal/(mol·deg2) and a uniform spacing of 5° was
applied on each order parameter.In the case of c-Abl, dihedral
angles Cβ(Ala380)–Cα(Ala380)–Cα(Asp381)–Cγ(Asp381) and Cβ(Ala380)–Cα(Ala380)–Cα(Phe382)–Cγ(Phe382) served as order parameters in the
US calculations. A graphical representation of the two order parameters
is given in Figure 3A. In order to probe the
effect of multiple pathways, the entire range (from −180°
to 180°) of each dimension should be covered. Hence, a total
of 5184 (72 for each dimension) umbrella windows were employed. Strings
from the last iterations were utilized to provide a starting structure
for each umbrella window in such a way that the chosen image was closest
to that window.
Figure 3
2D PMF of the DFG-flip conformational transition in c-Abl.
All
units of the 2D PMFs are in kcal/mol. (A) Graphical representation
of the order parameters used in 2D PMF. (B) Asp381 deprotonated. (C)
Asp381 protonated; US windows are focused on pathway 1 in order to
reduce the computational cost because only the thermodynamic properties
are considered when investigating the impact of Asp381 protonation.
The free energy basin to the left corresponds to the DFG-out conformation.
2D PMF of the DFG-flip conformational transition in c-Abl.
All
units of the 2D PMFs are in kcal/mol. (A) Graphical representation
of the order parameters used in 2D PMF. (B) Asp381 deprotonated. (C)
Asp381 protonated; US windows are focused on pathway 1 in order to
reduce the computational cost because only the thermodynamic properties
are considered when investigating the impact of Asp381 protonation.
The free energy basin to the left corresponds to the DFG-out conformation.Dihedral angles Cβ(Ala403)–Cα(Ala403)–Cα(Asp404)–Cγ(Asp404) and Cβ(Leu407)–Cα(Leu407)–Cα(Phe405)–Cγ(Phe405) were the order parameters
in the US simulations of c-Src.
Figure 4A illustrates both order parameters
in this set of umbrella sampling calculations. In order to save the
computational cost, US windows only populated the vicinity of the
converged strings. By integration with string method calculations,
computational resource can be focused on sampling the low free energy
valley along the transition pathway rather than on exploring the high
free energy region. The same strategy can be extended to studying
conformational transitions with other enhanced sampling method, such
as metadynamics. Therefore, 401 umbrella windows were employed to
patch the “in” and “out” conformations
in the case of c-Src. The starting structure of an umbrella sampling
window was taken from the final string, based on the same manner as
used in c-Abl. To directly address the effect of protonation of Asp381(Asp404)
on the free energy difference between DFG “in” and “out”
conformations, we carried out another set of US calculations in which
Asp381(Asp404) became protonated. 1481 umbrella windows were used
in the case of c-Abl, while the same 401 windows were employed for
c-Src.
Figure 4
2D PMF of the DFG-flip conformational transition in c-Src. All
units of the 2D PMFs are in kcal/mol. (A) Graphical representation
of the order parameters used in 2D PMF. (B) Asp404 deprotonated. (C)
Asp404 protonated. The free energy basin on the lower right corner
corresponds to the DFG-out conformation.
2D PMF of the DFG-flip conformational transition in c-Src. All
units of the 2D PMFs are in kcal/mol. (A) Graphical representation
of the order parameters used in 2D PMF. (B) Asp404 deprotonated. (C)
Asp404 protonated. The free energy basin on the lower right corner
corresponds to the DFG-out conformation.We also launched 2D self-learning adaptive US calculations[52] to explore the free energy landscape of conformational
transition involving the αC helix and the A-loop in the case
of c-Src. The difference between Glu310–Arg409salt-bridge
distance (d1) and Glu310–Lys295salt-bridge distance (d2) was used to
characterize the rotation of αC helix during the activation
process, while the average of three distances (d3) was used to reflect the opening of A-loop in the process.
Those three distances are between O(Asp413) and N(Thr417), O(Asn414)
and N(Ala418), and O(Glu415) and N(Arg419). A self-learning adaptive
US approach was employed to concentrate sampling to a region where
the free energy is less than 7.2 kcal/mol and is within 1 Å distance
to the projection of the converged string. A harmonic biasing potential
with a force constant of 20 kcal/(mol·Å2) and
a uniform spacing of 0.25 Å were applied on each order parameter.
A total of 1101 umbrella windows were used in this set of umbrella
sampling calculations. A total of 4.5 ns of MD propagation was carried
out per US window for all US calculations. Thus, approximately 30.0
and 8.6 μs of aggregate sampling time was spent on the c-Abl
and c-Src US calculations, respectively. The time series generated
during the last 4 ns of simulations were used by the weighted histogram
analysis method (WHAM)[53,54] to generate 2D PMFs. To evaluate
the convergence of the free energy landscape, 2D PMFs generated using
the last 3 and 4 ns of simulation data (as shown in Figure S4) are compared. The root-mean-squared error (rmse)
between the 2D PMFs is 0.16 and 0.59 kcal/mol for c-Abl and c-Src,
respectively. Such small rmse values suggest that adding one more
nanosecond of sampling time for each window yielded almost identical
PMFs, indicating that converged 2D PMFs have been obtained.
Results
and Discussion
Free Energy Landscape of DFG-Flip in c-Abl
The 2D-PMF
of DFG-flip in c-Abl with Asp381 deprotonated is shown in Figure 3B. The PMF is representative of a two-state equilibrium
between DFG-in and DFG-out conformations. The free energy basin around
(60°, −100°) corresponds to the DFG-in conformation,
while the basin around (−100°, 10°) corresponds to
the DFG-out conformation. The lowest free energy barrier separating
the “in” and “out” conformations is ∼7
kcal/mol, which reflects that DFG-flip in c-Abl is unlikely to be
a fast transition. To the best of our knowledge, no direct measurement
of the time-scale of DFG-flip is available for c-Abl from experiments.
Vogtherr et al.[47] have shown that the
DFG-flip in MAPK p38α takes place on a millisecond time scale
using NMR. Although a direct simulation of such a slow process by
brute-force MD is almost becoming feasible, the combination of string
method and umbrella sampling offers an effective computational strategy
to explore the microscopic mechanism underlying the DFG-flip process.
Thermodynamically, the conformational change can be characterized
through the free energy difference ΔGin→out ≡ Gout – Gin. This free energy difference can be computed by integrating
the Boltzmann-weighted probabilities built from the 2D PMF. We chose
Cβ(Ala380)–Cα(Ala380)–Cα(Asp381)–Cγ(Asp381) = −30°
to define a separator between the two conformations. Regions to the
left belong to the DFG-in conformation, while those to the right are
categorized as the DFG-out conformation. After integration, ΔGin→out(c-Abl) is 1.4 kcal/mol. This free
energy difference is consistent with the view that the DFG-in and
DFG-out in c-Abl are in near balance when Asp381 is deprotonated.[32] According to the calculations, the DFG-out conformation
accounts for approximately 9% of the total population. This non-negligible
population implies that the DFG-out conformation is accessible even
in the absence of type II inhibitors, as pictured by a conformational
selection mechanism. However, the positive ΔGin→out indicates that the active conformation of
c-Abl kinase domain is dominant. Other conformational changes as well
as myristoylated N-terminal cap binding are necessary to properly
control the catalytic activity of c-Abl.[6,20,21,55,56] One should also note that the positive ΔGin→out was calculated from a protein construct
comprising only the kinase domain. Whether the ΔGin→out is still positive in the c-Abl when the
SH2 and SH3 regulatory modules are present, especially in the down-regulated
state, is an interesting question that is not addressed by the present
computations.The minimum free energy pathway (MFEP) obtained
from the string method provides an advantageous set of starting configurations
for the biased US window simulation. The configurations from the string
method ought to nicely lie along the “reaction tube”
in the space of the collective variables, and US simulations would
be expected to converge rapidly. To illustrate this point, we projected
the initial transition path generated from TMD, as well as the string
1 at iterations 39 and 49 onto the 2D-PMF of c-Abl (Figure S5). The transition path from TMD clearly moves through
high free energy regions, while the MFEPs from the string method move
through low free energy regions. Mapping the MFEP onto free energy
landscape confirms the idea that the string method with swarms-of-trajectories
relaxes the initial transition path from high to low free energy regions.
It also supports the idea that the converged paths provide optimal
starting configurations for US calculations.In recent years,
methodologies aimed at extracting kinetic information
(e.g., the mean first passage time) of conformational changes from
MD simulations have reached a high level of maturity.[50,57−59] One example is provided by a recent study based on
Markov state models (MSM) of the activating/deactivating conformational
changes in the c-Src kinase domain.[60] In
studies of conformational changes, the issue of multiple pathways
is almost always a concern. Not accounting for some pathways can lead
to an incomplete picture of the mechanism as well as an underestimation
of the transition rate. In the case of the DFG-flip in c-Abl, the
2D-PMF from umbrella sampling can help to address such issues. According
to the 2D-PMF, there are three MFEPs and they correspond to calculated
strings 1, 3, and 4. As illustrated in Figure 3B, the energy barrier of pathway 1 is approximately the same as that
of pathway 4, while the barrier of pathway 3 is slightly higher than
that (2.4 kcal/mol higher). Pathways 1 and 4 have almost the same
barrier height, suggesting that those two pathways are competing with
each other. Using a single pathway (such as pathway 1 only) would
lead to an incorrect estimation of the transition rate for the DFG-flip
in c-Abl, even though a converged pathway and an accurate model to
calculate the rate are employed. It is also interesting to note that
TMD, used to initiate the string method iteration, was able to generate
the two pathways that have the lowest barriers (pathways 1 and 4)
but failed to discover pathway 3. To avoid such problems, it would
be desirable to have a robust method to generate multiple pathways
to initiate the string method.
Protonation of Asp381 Inverts
the Population of DFG-In/Out Conformation
in c-Abl
Shan et al. proposed that protonation of aspartic
acid 381 in the DFG motif of c-Abl serves as an energetic switch that
controls the DFG conformation.[32] A ΔGin→out of −1.1 kcal/mol when Asp381
is protonated was estimated on the conformational populations extracted
from unbiased MD simulations. In this model, the DFG-motif flipped
conformation spontaneously only when Asp381 is protonated.[32] Lovera et al.[31] also
addressed the issue in their meta-dynamics investigations of the DFG-flip
by feeding protein snapshots (solvent molecules discarded) extracted
from the MD trajectories into the empirical PROPKA program. This mixed
MD/PROPKA approach suggested that protonation of Asp381 in c-Abl stabilizes
the DFG-out conformation by 1.4 ± 0.9 kcal/mol (though the DFG-in
conformation remains dominant). Although both studies shed light on
the impact of the protonation state of the aspartate residue could
affect the conformational equilibrium of the DFG motif, quantitative
results obtained directly from explicit solvent free energy simulations
are still lacking.To address this issue, we repeated the US
calculations on the DFG flip in c-Abl with Asp381 protonated. Because
of the difficulty in defining a reaction coordinate associated with
the DFG-flip transition occurring in a concerted fashion with a protonation
event, we did not attempt to estimate the kinetic aspects of the process
and only investigated the effect of protonation on equilibrium properties.
To reduce the computational cost, US windows in the simulation of
c-Abl were concentrated near pathway 1 in the 2D subspace of order
parameters. Figure 3C displays the 2D-PMF of
DFG-flip when Asp381 is protonated. The location of DFG-out conformation
in the free energy landscape is almost unchanged, while the location
of the DFG-in energy basin shifts ∼30° to the left along
the Cβ(Ala380)–Cα(Ala380)–Cα(Asp381)–Cγ(Asp381) coordinate. Another
feature of Figure 3C is that the low free energy
region (region colored in dark blue) corresponding to the DFG-out
conformation broadens and occupies a larger area than that of the
DFG-in conformation. This calculation shows that protonation of Asp381
significantly affects the underlying free energy landscape of DFG-flip
in c-Abl. By use of the same criterion to distinguish DFG-out conformation
from DFG-in conformation, the ΔGin→out becomes −0.9 kcal/mol after integrating the 2D PMF with Boltzmann
weights. Once Asp381 becomes protonated, the DFG-out conformation
becomes dominant, ∼82% of the total population. Our results
are in excellent agreement with the hypothesis previously inferred
by Shan et al.[32] that the protonation
state of Asp381 acts as an energetic switch on the DFG flip. The two
2D-PMFs shown in Figure 3 indicate a four-state
model for c-Abl in which (i) DFG-in, Asp381 deprotonated; (ii) DFG-out,
Asp381 deprotonated; (iii) DFG-in, Asp381 protonated; and (iv) DFG-out,
Asp381 protonated are at equilibrium and transition from DFG-in to
DFG-out can occur at either protonation state of Asp381. In this model,
the population of the DFG-out conformation can be expressed as a function
of pH. The ΔGin→out of c-Abl
when Asp381 is protonated and deprotonated and the pKa value of Asp381 in DFG-in conformation are parameters.
A more detailed explanation of the four-state model is given in the Supporting Information.
Thermodynamics of Gleevec
Binding to c-Abl and pH-Independence
Isothermal titration
calorimetry (ITC) indicates that the binding
thermodynamics of Gleevec to c-Abl is not pH-dependent.[32] At first, this observation may appear inconsistent
with the protonation effects of Asp381 presented above. Nevertheless,
this must be interpreted with caution because various pH-dependent
effects may cancel out in the overall binding process. To address
this issue, one could in principle recompute the absolute binding
free energy of the ligand using a constant-pH dynamical algorithm[61−63] to account for the possible changes in protonation states of the
ionization groups during the binding process. However, when only a
small number of ionizable groups are involved as in the present situation,
pH effects can be assessed by computing the relative free energies
between the relevant ionization states using alchemical FEP/MD simulations.
Here only two moieties, Asp381 and Gleevec, are likely to be affected
by pH. Formally, the binding free energy of Gleevec can be expressed
into two contributions: the free energy for the DFG-flip and the binding
free energy of Gleevec to the kinase in the DFG-out apo conformation.
For the first contribution, our US calculations yield a ΔGin→out of 1.4 and −0.9 kcal/mol
for c-Abl with Asp381 deprotonated and protonated, respectively. The
difference in ΔGin→out, defined
asis
−2.3 kcal/mol. To cancel this value
and maintain the appearance of an overall pH-independent binding,
a positive free energy, defined as,of
2.3 kcal/mol is thus needed. To evaluate
the binding of Gleevec to the DFG-out conformation of c-Abl with Asp381
protonated, we performed alchemical free energy perturbation (FEP)
calculations, following the protocol described in Lin et al.[36] The force field parameters of Gleevec are given
by Aleksandrov and Simonson.[64] In our alchemical
FEP calculations, Gleevec stays positively charged so that the piperazinyl
group can form hydrogen bonds with Glu258.[65] The ΔΔGbinding as a function
of alchemical free energy calculation cycles (Figure S6) demonstrates that Gleevec binding to c-Abl with
Asp381 protonated is penalized, compared with c-Abl with Asp381 deprotonated
by about 1.3 kcal/mol (averaging over the last seven cycles of the
alchemical FEP). By combination of the ΔΔG values from DFG-flip and binding, the total change with pH is thus
about −1.0 kcal/mol. Taking into consideration the various
inaccuracies of the force field and the overall uncertainty of the
alchemical FEP calculations (3.3 ns per λ), it is reasonable
to infer that the present results for c-Abl are consistent with the
observation from ITC experiments. According to our calculations, both
the DFG-flip and Gleevec binding to the DFG-out conformation in c-Abl
are affected by changing the protonation state of Asp381 but in an
opposite manner. The apparent pH-independence of the binding thermodynamics
of Gleevec, according to this analysis, results from the cancelation
of the two pH-dependent processes. This conclusion is consistent with
our result that the binding specificity of Gleevec is governed by
both conformational selection and binding affinity. Therefore, both
factors need to be considered in the process of designing type II
kinase inhibitors. One should note that a different pH range was used
in the ITC equilibrium binding affinity and kinetic experiments. The
ITC experiments were performed at a pH ranging from 5.5 to 7.5, while
the binding kinetics measurements were performed at a pH ranging from
7.0 to 9.0.[32] As the pKa value of the piperazinyl group in Gleevec is 7.7, the
change in pH in ITC is expected to affect the protonation state of
the Asp381 side chain of c-Abl (rather than that of Gleevec), whereas
the change in pH in the kinetic experiments is likely to affect the
protonation state of Gleevec (rather than that of Asp381). Thus, the
pH-dependence in the kinetic experiments should reflect the impact
on the binding process in c-Abl rather than on the DFG-flip. The present
simulations are aimed at examining the effect of protonation of Asp381
on the DFG-flip and the equilibrium binding process.
Free Energy
Landscapes of DFG-Flip in c-Src
In the
2D-PMF of c-Src (Figure 4B), the DFG-in conformation
is around (−100°, 20°), while the DFG-out conformation
is around (20°, −160°). A small free energy barrier
of about 2 kcal/mol separates the two conformations. The resulting
ΔGin→out is 5.4 kcal/mol
after integrating the Boltzmann-weighted probability from the 2D PMF.
A large ΔGin→out and a very
small barrier imply that the DFG-out conformation of c-Src is only
marginally stable. Even if a DFG-flip transition occurs, the DFG-out
conformation would be expected to quickly interconvert back to the
more stable DFG-in conformation. This large free energy difference
is consistent with the difficulty of designing inhibitors that are
targeting the DFG-out conformation (type II inhibitors) in c-Src,
as those must overcome a large ΔGin→out in order to bind with high affinity. Nonetheless, such inhibitors
can exist. For example, the G6G molecule designed by Seeliger et al.[28] can bind to c-Src with a fairly high affinity
(IC50 ≈ 2.8 nM) by forming sufficiently strong interactions
to overcome the cost of the DFG-flip.[66]To quantify the impact of the ionization state of aspartic
acid of the DFG motif on the conformational flip transition in c-Src,
the US calculations were repeated with Asp404 protonated. The 2D PMF
is shown in Figure 4C. Comparison with Figure 4B shows that protonation of Asp404 has little impact
on the free energy landscape underlying DFG-flip in c-Src. The ΔGin→out(c-Src) is 5.5 kcal/mol with Asp404
protonated, which is also very close to 5.4 kcal/mol yielded from
simulation with Asp404 deprotonated. Unlike the DFG-out conformation
that becomes dominant in c-Abl when Asp381 is protonated, the DFG-out
conformation in c-Src is still marginally stable. The large impact
of protonation observed in the case of c-Abl is not reflected in c-Src,
which suggests that the impact of protonation is not universal. One
possible reason for the lack of impact is that Asp404 lies in a different
environment from that Asp381 is in. Comparing the DFG-out conformation
in c-Abl and c-Src, one could see that Asp381 is buried in a hydrophobic
pocket and protonation will stabilize Asp381 in that state. The free
energy landscape presented in Figure 3 is consistent
with this model. In contrast to the situation in c-Abl, Asp404 in
c-Src is solvent accessible. The protein does not clearly provide
a favorable environment for the protonated state.
Importance
of the CDK/Src-like Inactive State for c-Src Kinase
The X-ray
crystallographic structures of the down-regulated (autoinhibited)
c-Src reveal a different type of deactivation from DFG-flip.[26,67] The conformational change from the active conformation to the inactive
one mainly involves the motion of the αC-helix and the A-loop.
Similar inactive configurations are also observed in many other kinases
such as the serine/threonine kinase cyclin-dependent kinase 2 (CDK2),[68] Src-family kinase Hck,[69] tyrosine kinases ZAP70[70] and EGFR,[71] highlighting the importance of this type of
inactivation mechanism in the general regulation of kinases. Because
this inactive configuration was first observed in the CDKs and Src
kinases, it is commonly referred to as the “CDK/Src-like inactive
state”.[72] The structural details
of both the DFG-out and CDK/Src-like inactivated states are of consequence
in the design of potent and selective kinase inhibitors. In order
to evaluate the relative importance of these two mechanisms with regard
to the overall activation/deactivation of c-Src kinase, 2D US calculations
were carried out to characterize the free energy landscape associated
with the transition to the CDK/Src-like inactive state. Figure 5 illustrates the free energy landscape underlying
the conformational change associated with the αC-helix and the
A-loop. In Figure 5, the free energy basin
around (2.5, −12.0) is the inactive state in which the A-loop
is closed and partially folded, preventing substrate from entering
active site. Moreover, the αC helix is rotated outward and Glu310
in the αC helix makes a salt-bridge with Arg409 (in the A-loop).
In this inactive state, the DFG motif adopts the “in”
conformation. The free energy basin around (11.0, 12.0) corresponds
to the same DFG-in active conformation as shown in Figure 4. In contrast to the DFG-flip conformational transition,
the conformational transition involves movements of the αC helix
and the A-loop favors the inactive state. The free energy difference
from the inactive state to the active state is 3.9 kcal/mol. Combining
the two pathways, one can see that the DFG-out conformation is very
unlikely to be observed in c-Src. The DFG-flip is not a dominant step
in the normal regulation of c-Src. The activation/deactivation in
c-Src kinase domain is achieved through the conformational changes
in the αC helix and the A-loop. But when the normal regulation
is hijacked, the DFG-flip pathway can be exploited by potent inhibitors
to reduce the kinase activity. Of particular significance regarding
the activation of the c-Src kinase domain is the trans-phosphorylation
reaction. Although the inactive conformation of c-Src kinase domain
is the most populated in Figure 5, the active
conformation can still be visited (albeit rarely) and the trans-phosphorylation
reaction can proceed. The active conformation will be stabilized by
the phosphorylation of the A-loop, and the catalytic activity will
increase. Our simulations agree with the experimental observation
that the isolated c-Src kinase domain is intrinsically active (i.e.,
displays high catalytic activity).[73] Figure 5 also suggests that compounds that stabilize the
inactive and the intermediate conformations of the kinase domain can
be used as c-Src inhibitors, as they can prevent c-Src kinase domain
visiting the active conformation. Currently, inhibitors that bind
to the vicinity of the αC-helix are also under development.[74] This type of inhibitor (type III) aims to prevent
the αC-helix from adopting an active conformation. Both type
II and type III inhibitors avoid binding to the structurally highly
similar active site and intend to achieve specificity.
Figure 5
2D PMF underlying the
motion of the αC-helix and the A-loop
in c-Src. The unit of this PMF is in kcal/mol. d1 is the distance between E310 Cδ atom and R409 Cζ
atom. d2 is the distance between E310
Cδ atom and K295 Nζ atom. d3 is the average of the following three distances and is used to reflect
the opening of the A-loop in the process. Those three distances are
between O(Asp413) and N(Thr417), O(Asn414) and N(Ala418), and O(Glu415)
and N(Arg419). The free energy basin that is located at the lower
left corner is the inactive conformation, while that at the top right
corner corresponds to the active conformation.
2D PMF underlying the
motion of the αC-helix and the A-loop
in c-Src. The unit of this PMF is in kcal/mol. d1 is the distance between E310 Cδ atom and R409 Cζ
atom. d2 is the distance between E310
Cδ atom and K295 Nζ atom. d3 is the average of the following three distances and is used to reflect
the opening of the A-loop in the process. Those three distances are
between O(Asp413) and N(Thr417), O(Asn414) and N(Ala418), and O(Glu415)
and N(Arg419). The free energy basin that is located at the lower
left corner is the inactive conformation, while that at the top right
corner corresponds to the active conformation.
Hydrophobic Regulatory Spine (R-Spine) in c-Abl
Protein
kinases have evolved to be dynamic molecular machines that are toggling
between the catalytically “on” and “off”
states.[12,75] The discovery of hydrophobic spines in protein
kinases has introduced an important structural marker for the occurrence
of a competent catalytic machinery. Two spines,[12,22,23,76] an R-spine
and a C-spine, are formed in active kinases. Both spines consist of
conserved and noncontiguous amino acids in kinases. They both can
be dynamically assembled and broken, switching the kinase activity
on and off. The R-spine consists of four residues extending from the
N-lobe to the C-lobe: L301, M290, F382, and H361 (see Figure 6A) in c-Abl.[22,77] Among those four residues,
M290 comes from the αC helix, F382 from the DFG motif, and H361
from the HRD motif. In the DFG-out conformation, the flip of Phe382
disrupts the integrity of the R-spine. The conformational transition
mechanism that is governed by the landscape shown in Figure 5 also correlates with the breaking of the R-spine:
the outward rotation of the αC-helix deforms the R-spine. Both
conformational changes are consistent with the view that the αC
helix and the A-loop can be mobile, and hence, the R-spine can be
dynamically assembled and disassembled.[12,23] Figure 6B, showing the 1D PMFs as a function of the rmsd
of the R-spine relative to the DFG-in active conformation, demonstrates
the free energy profile of the stability of the R-spine before and
after Asp381 is protonated. Both 1D PMFs were calculated on the basis
of the existing umbrella windows (no additional US calculation were
performed to obtain those PMFs). Two stable conformations of the R-spine
are present, regardless of the protonation state of Asp381. The conformation
that is around 1.2 Å corresponds to the conformation in which
the R-spine is formed (“on” conformation). The stable
conformation around 3.5 Å associates with the conformation where
the R-spine is broken (“off” conformation). However,
as illustrated in Figure 6B, the free energy
basin corresponding to the “off” conformation of the
R-spine is broader and lower in energy when Asp381 is protonated than
that in c-Abl with Asp381 is deprotonated. This observation reveals
that protonation of Asp381 destabilizes the assembly of the R-spine
in c-Abl. However, protonation of Asp381 does not change the barrier
height significantly, suggesting that toggling between inactive and
active conformations remains a slow process under those conditions.
The brute-force MD simulations performed by Shan et al. are also consistent
with this view.[32] In their simulations,
protonation of Asp381 alone did not enable barrier crossing. M290,
which is one component of the R-spine, needed to be substituted with
an alanine residue to observe DFG-flip in their MD simulations. Mutating
a methionine residue to the shorter alanine residue weakens the interaction
between that residue and F405 and hence accelerates the flipping of
the DFG motif. One interesting question is whether replacing M290
with an alanine alone (i.e., M290A and Asp381 will be kept deprotonated)
should alter the free energy landscape underlying DFG-flip.
Figure 6
(A) Representative
structure of the R-spine. (B) 1D PMFs as a function
of the rmsd of the regulatory spine (R-spine) relative to the DFG-in
conformation, in which the R-spine is formed. All heavy atoms in the
R-spine are used in the calculation of rmsd.
(A) Representative
structure of the R-spine. (B) 1D PMFs as a function
of the rmsd of the regulatory spine (R-spine) relative to the DFG-in
conformation, in which the R-spine is formed. All heavy atoms in the
R-spine are used in the calculation of rmsd.
Interactions Affecting DFG-Flip in c-Abl and c-Src When Asp381(Asp404)
Is Deprotonated
Residues that affect DFG-flip significantly
could be identified by analyzing their interaction energies with the
DFG motif. Therefore, van der Waals (vdW) and electrostatic energies
between DFG motif and the rest of the protein as well as water molecules
that are within 5 Å of it were computed for DFG-in and DFG-out
conformations of both c-Abl and c-Src kinases. The sum of the electrostatic
and vdW terms is utilized to represent the overall interaction between
a particular residue and the DFG motif in a given conformation. Once
the interaction energy values were obtained, ΔEin→out was then computed as ΔEin→out ≡ E(DFG-out) – E(DFG-in). The effect of a residue upon DFG-flip can be
evaluated by ΔEin→out. By
its definition, a positive ΔEin→out means that DFG-flip will raise the interaction energy between a
residue and the DFG motif, making that residue less stable. Therefore,
that residue prefers DFG-in conformation and destabilizes DFG-flip.
A negative ΔEin→out value
means the opposite. ΔEin→out and its two components, as a function of residue index, are illustrated
in Figures 7, S7, and S8. The values of ΔEin→out are essentially zero for those residues after the A-loop and thus
are not shown in the figures. Table 1 displays
the ΔEin→out and its two
components of all residues, the phosphate-binding loop (P-loop, residues
248–257, c-Abl 1a numbering), the αC-helix (residues
280–294, c-Abl 1a numbering), and the A-loop (residues 381–402,
c-Abl 1a numbering). The overall ΔEin→out indicates that DFG-flip is unfavored in both c-Abl and c-Src. The
overall ΔEin→out also reveals
that DFG-flip is penalized (in energy) more in c-Src than in c-Abl.
This qualitatively agrees with our results from umbrella sampling
calculations.
Figure 7
Differences in interaction energies between DFG-in and
DFG-out
conformations: (A) c-Abl with Asp381 deprotonated; (B) c-Abl with
Asp381 protonated; (C) c-Src.
Table 1
Energy Decomposition Results of DFG-Flipa
ΔEin→out
all residues
P-loop
αC-helix
A-loop
c-Abl
6.4
–2.7
4.7
0.4
c-Src
10.3
–1.5
12.5
2.2
Asp381(Asp404) is deprotonated.
All values are in kcal/mol.
Differences in interaction energies between DFG-in and
DFG-out
conformations: (A) c-Abl with Asp381 deprotonated; (B) c-Abl with
Asp381 protonated; (C) c-Src.Asp381(Asp404) is deprotonated.
All values are in kcal/mol.The conformation of the P-loop was proposed to be essential for
the high selectivity of Gleevec. A kinked (W-shaped; see Figure S9) conformation of the P-loop in c-Abl
was believed to be critical in Gleevec binding. This W-shaped conformation
makes the P-loop stabilize Gleevec in the pocket. Our residual decomposition
results shows that the P-loop also plays an important role in the
conformational transition. The P-loop stabilizes DFG-flip in both
c-Abl and c-Src, mainly through vdW interactions. In the DFG-out conformation
of c-Abl, Phe382 moves to the vicinity of the W-shaped P-loop and
resultes in a stabilizing dispersive interaction. In c-Abl, the stabilizing
interaction provided by the P-loop is dominated by the contribution
from Tyr253, which forms a contact with Phe382 (as displayed in Figure S9A). In c-Src, the P-loop is in an extended
conformation (see Figure S9) and thus is
not as close to the phenylalanine in the DFG motif as that in c-Abl.
Therefore, this stabilizing effect is much less significant in c-Src.
According to Figure 7C, the counterpart of
Tyr253-Phe382 interaction is missing in c-Src because of the extended
conformation possessed by the P-loop. The αC-helix and the A-loop
provide a destabilizing effect on DFG-flip in both kinases. Among
those residues in the αC-helix, one could see Glu286 contributed
the most to ΔEin→out. For
the A-loop, our calculation reveals that only the residues that are
next to DFG motif have nontrival interactions. In c-Abl, the impact
of residue 384 and 385 is almost canceled, which makes the overall
ΔEin→out from the A-loop
residues only slightly greater than zero. Lys271 is another residue
that interacts with the DFG motif strongly. The positively charged
side chain of Lys271 forms a salt-bridge with the carboxylic group
of Asp381 in the DFG-in conformation. Although the vdW component favored
DFG-out conformation, the “flip” is heavily penalized
by breaking the salt-bridge.
Key Segments and Residues Affecting DFG-Flip
in c-Abl When Asp381
Is Protonated
Table 2 demonstrates
the ΔEin→out and its two
components of c-Abl with Asp381 protonated. The overall ΔEin→out indicates that DFG-flip is favored
in c-Abl with Asp381, which qualitatively agrees with our results
from umbrella sampling calculations. However, if only considering
the nonsolvent interactions, the net ΔEin→out is 0.4 kcal/mol: DFG-flip is unfavored by the
rest of the protein even with Asp381 protonated. This small destabilizing
factor is balanced by a possibly overnegative interaction energy with
solvent. Therefore, the aqueous environment is vital for DFG-flip
after Asp381 is protonated.
Table 2
Energy Decomposition
Results of DFG-Flip
in c-Abla
all residues
P-loop
αC-helix
A-loop
ΔEin→out
–10.4
2.0
1.1
–1.7
ΔEin→out,ele
–8.2
–0.1
3.1
–1.5
ΔEin→out,vdW
–2.2
2.1
–2.0
–0.2
Asp381 is protonated. All values
are in kcal/mol.
Asp381 is protonated. All values
are in kcal/mol.Protonation
of Asp381 alters the role of the P-loop and the A-loop
on DFG-flip. Contrary to the stabilizing/destabilizing effect that
is exerted by the P-loop/A-loop in c-Abl with Asp381 deprotonated,
Table 2 demonstrates that the P-loop/A-loop
acts as a destabilizing/stabilizing factor on DFG-flip in c-Abl with
Asp381 protonated. As shown in Figure 7B, many
interaction energies from the P-loop and the A-loop change signs after
Asp381 is protonated. However, the αC-helix still provides a
destabilizing effect on DFG-flip. Out of all residues in the P-loop,
Tyr253 still has the largest contribution to ΔEin→out, even though it is an opposite effect now.
Likewise to the Glu286 in c-Abl with Asp381 deprotonated, Glu286 still
has the largest positive ΔEin→out among residues in the αC-helix. To display the counteraction
of Asp381 being protonated on DFG-flip in c-Abl, Figure S10 plots the ΔΔEin→out as a function of residue index, using the ΔEin→out shown in Figure 7A as a reference. A negative sign in ΔΔEin→out indicates that the counteraction
favors DFG-flip. According to Figure S10, the effect of protonation is disbuted among multiple residues.
There are nine residues whose absolute values of ΔΔEin→out are greater than 2 kcal/mol. Four
residues possess ΔΔEin→out that are larger than 4 kcal/mol in absolute value. Among all the
actions on DFG-flip in c-Abl, the one from Lys271 is affected the
most by the protonation of Asp381 (see Figure
S10). Protonation of Asp381 completely eliminates the large
destabilizing interaction between the DFG motif and Lys271 which can
be seen in Figure 7A. When Asp381 becomes protonated,
the large electrostatic interaction between side chains of Asp381
and Lys271 is greatly reduced in the DFG-in conformation such that
it does not have a significant influence on DFG-flip.Residual
decomposition analysis also sheds light on how the R-spine
(excluding Phe382) influences DFG-flip after Asp381 is protonated.
Among those three residues, ΔEin→out is 1.1, 0.0, and −3.1 kcal/mol for Met290, Leu301, and His361,
respectively. Three residues have three different impacts on DFG-flip.
Leu301 has no impact because it is the farthest away from the DFG
motif. Met290 unfavors the DFG-flip even with Asp381 is protonated.
Our residual decomposition results of Met290 agree with what was observed
in the brute-force MD simulations:[32] Met290
still needed to be mutated to alanine in order to facilitate DFG-flip
to occur even after Asp381 is protonated. Compared with methionine,
alanine is a less obstructing residue because of its smaller size.
His361 favors the DFG-out conformation when Asp381 is protonated.
It stabilizes both Asp381 and Phe382 in the DFG-out conformation.
The total ΔEin→out from the
R-spine is −2.0 kcal/mol. The negetive sign suggests that the
R-spine is even internally less stable (components of the R-spine
prefer the DFG-flip to occur and consequently disassemble the R-spine)
when Asp381 becomes protonated.
Conclusions
The
string method combined with the umbrella sampling technique
was utilized to determine the free energy cost associated with the
conformational transition converting the DFG motif of the (apo) c-Abl
and c-Src tyrosine kinases from the active “in” to the
inactive “out” state. The calculated free energy landscapes
describing the DFG-flip conformational change show that the DFG-out
conformation can be stable in c-Abl even in the absence of Gleevec,
whereas it corresponds to a state of high free energy in c-Src. The
impact of protonation of the aspartic residue of the DFG motif (Asp381
in c-Abl and Asp404in c-Src) was also quantified. The calculated free
energy landscapes show that protonation of Asp381 has a considerable
impact on the DFG-flip in c-Abl but that protonation of Asp404 has
very little impact on the DFG-flip in c-Src. The calculated free energy
difference between DFG-in and DFG-out conformations reveals that the
DFG-out conformation becomes dominant once Asp381 becomes protonated.
However, the protonation of Asp381 also reduces the binding affinity
of Gleevec to the DFG-out conformation, resulting in a very small
change in the overall binding affinity. This result explains why the
experimentally measured binding affinity of Gleevec to c-Abl is not
sensitive to pH. Protonation of Asp381 also has a considerable effect
on the stability of the hydrophobic R-spine. After Asp381 is protonated,
the disassembled form of the R-spine is greatly favored as a consequence
of the DFG-out conformation becoming more energetically favorable.It is instructive to use the DFG-flip in c-Abl as an example of
a computational exploration of system with multiple transition pathways.
The existence of the latter is explicit when considering the 2D PMF
of c-Abl (pathways with comparable free energy barriers). This necessarily
becomes an important issue for a complete investigation of the kinetics
aspects of the DFG-flip transition. The present results suggest that
the free energy landscape underlying a conformational transition should
be characterized thoroughly before tackling the task of calculating
kinetic factors. Moreover, the unphysical biasing potential that is
used in targeted MD calculations affects the initial pathway generations.
Thus, a systematic way of generating starting conditions for the string
method should be employed when multiple pathways need to be considered.The conformation of P-loop (residues 248–257, c-Abl numbering)
was proposed to be essential for the high selectivity of Gleevec.[28] This W-shaped conformation makes P-loop stabilize
Gleevec in the pocket. Our residual decomposition analysis shows that
the P-loop also stabilizes DFG-flip in both c-Abl and c-Src, mainly
through vdW interactions, when Asp381(Asp404) is deprotonated. However,
the P-loop in c-Abl exerts an opposite action on DFG-flip after Asp381
becomes protonated. Despite a destabilizing effect on DFG-flip from
the P-loop, our residual decomposition analysis reveals an overall
favorable effect on DFG-flip after Asp381 is protonated. The counteraction
of Asp381 being protonated on DFG-flip is distributed among many residues
with the largest from Lys271.
Authors: Sandra W Cowan-Jacob; Gabriele Fendrich; Paul W Manley; Wolfgang Jahnke; Doriano Fabbro; Janis Liebetanz; Thomas Meyer Journal: Structure Date: 2005-06 Impact factor: 5.006
Authors: Bhushan Nagar; Oliver Hantschel; Matthew A Young; Klaus Scheffzek; Darren Veach; William Bornmann; Bayard Clarkson; Giulio Superti-Furga; John Kuriyan Journal: Cell Date: 2003-03-21 Impact factor: 41.582
Authors: Oliver Hantschel; Bhushan Nagar; Sebastian Guettler; Jana Kretzschmar; Karel Dorey; John Kuriyan; Giulio Superti-Furga Journal: Cell Date: 2003-03-21 Impact factor: 41.582
Authors: Ryan H B Smith; Zaigham M Khan; Peter Man-Un Ung; Alex P Scopton; Lisa Silber; Seshat M Mack; Alexander M Real; Avner Schlessinger; Arvin C Dar Journal: Biochemistry Date: 2021-01-13 Impact factor: 3.162
Authors: Brajesh Narayan; Arman Fathizadeh; Clark Templeton; Peng He; Shima Arasteh; Ron Elber; Nicolae-Viorel Buchete; Ron M Levy Journal: Biochim Biophys Acta Gen Subj Date: 2019-12-27 Impact factor: 3.770