Type II Kinase Inhibitors Show an Unexpected Inhibition Mode against Parkinson s Disease-Linked LRRK2 Mutant G219S. Min Liu@&*, Samantha A. Bender%*, Gregory D Cuny@, Woody Sherman, Marcie Glicksman@ Soumya S. Ray#@%&. @ Harvard NeuroDiscovery Center, Harvard University, 65 Landsdowne St., #452, Cambridge, MA 2139 % Department of Neurology, Brigham and Women's Hospital # Center for Neurologic Diseases, Brigham and Women's Hospital Schrodinger, 12 W. 45th Street, New York, NY
Materials and Methods: Homology Modeling and docking: The LRRK2 kinase domain, between residues 1859-2138, was modeled using Modeller. Briefly, the main criteria in homology modeling were template selection and sequence alignment between the target and the template. The top three hits based on sequence identity were the ack1 kinase (31% identity) and B-raf (33% identity). In this case, the template of B-raf kinase which had 33% sequence identity was used for homology modeling since this enzyme had higher sequence conservation around the active site region compared to the other kinases. The Cα RMSD and the backbone RMS deviations for the model and the template crystal structure were < Å and < 1.2 Å respectively. The best model was subjected to geometric evaluations using PROCHECK with an overall G-value of -4. Ramachandran plots indicated that >9% of the residues are in the allowed region of the map. Standard bond lengths and bond angles of the model were determined using WHAT IF with an RMS-Z score of.889 and.91 suggesting that the model is of high quality. In addition, we used Prime, Rosetta and SwissModel to generate models for LRRK2 kinase domain for the same set of residues. The The Cα RMSD and the backbone RMS deviations between any pair of structures was < 1.2Å. A second set of models were generated using the recently determined structure of Roco 4 (pdb code: 4FG) by Wittinghoffer and co-workers. Structural comparison between this model and the model of LRRK2 generated using B-Raf template were virtually identical. Key residue positions including the catalytic and hydrophobic spines described by Taylor and coworkers were in the expected positions. Key catalytic residues including H1994, D1996 were in
the expected positions. Comparison of the hinge region revealed that the B-raf hinge was closer in sequence compared to the Roco 4 hinge and was therefore chosen to be model for further studies. Docking of ATP molecule was performed using GLIDE v2.2 (Schrödinger inc.). A 1Å search grid was used using the center of mass of glycine rich loop and the activation loop as the point of origin. Maestro v9.2 (Schrödinger inc.) was used to interactively place the Mg2+ atom near the γ-phosphate of ATP within reasonable bonding distance and geometry based on structures of other kinases in the protein database. Superpositioning wherever necessary was carried out using the modeling software Coot v6.2. Loop modeling and preliminary MD thermalization of the DYG-in and DYG-out conformations: The conformation switch between the active and inactive conformations requires two correlated motions at a protein level. The first motion involves repositioning of the N-terminal β-sheet region and C-helix (Figure 1c) breaking a salt-bridge between K196 and E192 when the kinase switches from active to inactive form. The second motion involves a flip of the DYG-motif, where D217 and Y218 exchange positions (DYG-in to DYG-out). A two step modeling procedure was carried out using Prime and HingeProt to built a DYG-out and open kinase conformation. Briefly, loop conformation were sampled with the Prime extended sampling settings. Side chains within 7.5Å of all residues remained flexible and all structures within a 5 kcal/mol energy window were saved. Prime uses a hierarchal approach where the two major
steps are dihedral angle sampling of the backbone to generate possible loop conformations (no steric clashes with other protein parts or inhibitors is ensured) followed by side-chain optimization of loop structures further chosen for optimization. The algorithm for side-chain optimization uses sampling from a highly detailed (1 resolution) rotamer library constructed by Xiang and Honig from a database of 297 proteins. The final models were subject to MD thermalization to determine if they were stable structure. In the thermalization scheme, MD simulations of the two conformational states of the kinase (WT, G219S and I22T) described above were carried out using the Desmond 3. (D.E Shaw Research and Schrödinger inc.) and the OPLS-AA 25 force field. Water solvation was described by immersion of the DYG-in (closed) and DYG-out (open) structures in 26, TIP3P waters. Electroneutrality was ensured by adding three Na+ ions to the system. Periodic boundary conditions and the particle mesh Ewald (PME) method (to account for long-range electrostatic interactions) were used throughout. Bonds involving hydrogens were constrained using the SHAKE algorithm, and a time step integration of 2fs were used for all simulations. A steepest-descent minimization and thermalization scheme was applied to all of the initial structures. The systems were heated from to 3 K in 2ps, keeping the Cα atoms fixed in their original positions. In the next step, all of the constraints were lifted, and the equilibration was continued in the isobaric isothermal ensemble with Nose Hoover thermostats for 5. ns.
Metadynamic simulations: After MD thermalization, the DYG-in (closed) and DYG-out (open) conformations of LRRK2 were submitted to the Yale MolMov morphing server (http://molmovdb.mbb.yale.edu/molmovdb/). Starting from our initial and final structures, we obtained ten interpolated intermediates. Each of the ten morphing conformations was then hydrated and thermalized at 3 K using the scheme described above. Notably, some morphing conformations were quite stable during the thermalization, while others showed a rapid increase of the rmsd of the Cα atoms. Finally total of seven conformations (two initial and five intermediates) starting from the DYG-in (closed state) to the DYG-out (open state), and the five intermediate morphing conformers were used to generate the guess path for metadynamicsbased computations. The parameters of the Gaussians were chosen on the basis of pilot calculations as a compromise between accuracy of the simulation coinciding with the morphing path (see supporting information for details) and the computational cost. After several pilot calculations, we defined two variables, s and z, which are able to describe the position of a point in configurational space closely resembling the morphing path generated using the Prime modeled DYG-in and DYG-out states. In case of distance measurements, two sets of atoms whose center of masses were positioned on either K196 or E192 were used as one collective variable (z). The center of mass of the activation loop was calculated based on the position of the Cα atoms of residues Y218, A221, C224, R226 and M227 (s). For metadynamics simulations based on torsion angles to measure change in conformational freedom of the loop during a G219 S219 and I22 T22 mutations, the φ and ψ angles of G219 /S219 and were used
as collective variables to measure rotational conformational barriers. The weighted histogram analysis method was applied to a series of simulations in order to obtain a free-energy profile using s and z.
(a) (b) [s] [z] Y218 Inactive A221 C224 K196 E192 open R226 M227 active closed (c) [φ]/[ψ] Y218 (DYG-in) Y218 (DYG-out) Figure S1, Supporting information
(a) 1.8 1.6 1.4 1.2.8.6.4.2 WT 1.2 A D v/[e], min-1 v/[e], min-1 G219S 5 um 25 um 12.5 um 6.25 um 3.125 um um.8.6.4.2 2 4 6 8 1 12 2 4 6 8 1 12 1.8 1.6 1.4 1.2.8.6.4.2 [ATP], µ M 1.2 (kcat)atp min-1 (kcat)atp, min-1 [ATP], µ M B.8.6.4.2 1 2 3 4 5 E 6 1 25 C (kcat/km)atp min-1 (kcat/km)atp, min-1µ M-1 2 12 8 4 1 2 3 4 3 4 5 6 5 6 [Imatinib], µ M [Imatinib], µ M 16 2 5 6 [Imatinib], µ M Figure S2, Supporting information F 2 15 1 5 1 2 3 4 [Imatinib], µ M
(b) WT G219S 3. kcat, min-1 kcat, min-1 2.5 2. 1.5.5 A 1 2 3 4 5 1.6 1.4 1.2.8.6.4.2 6 D 1 kcat/km, min-1 µ M-1 kcat/km, min-1µ M-1 B 25 2 15 1 5 1 2 3 4 5 35 3 25 2 15 1 5 1 6 6 2 3 4 5 6 C.8 8 Ki,app, µ M Ki,app, µ M 5 [Sorafenib], µ M 12 6 4 2 4 E [Sorafenib], um 1 3 [Sorafenib], µ M [Sorafenib], um 3 2.6.4 F.2 5 1 15 2 25 3 [ATP], um Figure S2 (continued), Supporting information 1 2 3 4 5 6 [ATP], µ M
(c) G219S A 2. 1.5.5 1 um 5 um 2.5 um 1.25 um.6 um um.8.6.4.2 D 5 um 2.5 um 1.25 um.6 um.3 um um v/[e], min-1 v/[e], min -1 2.5 WT 1.2 3. 2 4 6 8 1 12 2 4 3. kcat, min-1 kcat, min -1 2.5 2. 1.5.5 1.5 2. 2.5 1.6 1.4 1.2.8.6.4.2 3. 2 4 6 8 1 12 [Bosutinib], um 3 kcat/km, min-1µ M-1 4 kcat/km 1 12 E [Bosutinib], um C 3 2 1 8 [ATP], um [ATP], um B.5 6 1 2 3 4 5 6 [Bosutinib], um Figure S2 (continued), Supporting information F 25 2 15 1 5 2 4 6 8 [Bosutinib], um 1 12
(a) N-terminal β-sheet domain Helix 1 Hinge loop ATP Activation loop C-lobe hydrophobic helix Figure S3, Supporting information
(b) K196 E192 ATP binding hinge ATP D217 G219S 2+ Mg C224 H1998 D1994 K1996 Figure S3 (continued), supporting information C225
(c) ATP binding pocket (DYG-out) ATP binding pocket (DYG-in) DFG in Figure S3 (continued), supporting information DFG-out
LRRK2G219 LRRK2S219 18 18 kcal/mol -18-18 -18 Figure S4, supporting information 18-18 18
Bosutinib DYG-in Imatinib DYG-in Figure S5, supporting information Sorafenib DYG-in Ponatinib DYG-in
Bosutinib DYG-out Imatinib DYG-out Figure S5 (continued), supporting information Sorafenib DYG-out Ponatinib DYG-out
Table S1: DFG-in (Ramachandran angles) Phi 79.47-69.12-72.33 Psi 31.44 24.23-23.99 LRRK2 A:ASP 217 A:TYR 218 A:GLY 219 ckit A:ASP 81 A:PHE 811 A:GLY 812 47.26-98.59-71.71 79.76 34.29-28. Aurora A:ASP 274 A:PHE 275 A:GLY 276 52.22-9.83-49.87 8.16 24.66-44.18 Src A:ASP 44 A:PHE 45 A:GLY 46 51.2-91.41-66.18 73.44 23.77-17.6 cabl A:ASP 381 A:PHE 382 A:GLY 383 46.92-11.63-54.55 83.86 25.32-28.15 B-raf A:ASP 594 A:PHE 595 A:GLY 596 62.65-116.52-45.53 94.56 2.29-44.52 EPHA A:ASP 764 A:PHE 765 A:GLY 766 64.35-15.5-63.32 72.55 56.47-27.92 LCK A:ASP 382 A:PHE 383 A:GLY 384 54.21-95.2-67 81.26 22.59-34.51 MK14 A:ASP 168 A:PHE 169 A:GLY 17 62.9-124.28-54.76 86.7 146.5 19.36
Table S1 (continued) DFG-out (Ramachandran angles) LRRK2 A:ASP 217 A:TYR 218 A:GLY 219 Phi -124.33-172.56 14.67 Psi 91.34 163.26 141.98 ckit A:ASP 81 A:PHE 811 A:GLY 812-155.33-61.58 52.44 12.83-32.2-129 Aurora A:ASP 274 A:PHE 275 A:GLY 276-12.65-141.99 72.95 14.15-158.3-8.69 Src A:ASP 44 A:PHE 45 A:GLY 46-152.96-76.34 51.64 92.87 12.49 22.22 cabl A:ASP 381 A:PHE 382 A:GLY 383-153.84-92.45 52.64 11.42 5.84 55.23 B-raf A:ASP 593 A:PHE 594 A:GLY 595-121.32-83.23 83.78 89.16 16.4 148.3 EPHA A:ASP 764 A:PHE 765 A:GLY 766-165.13-97.76 77.85 114.42 4. 179.81 LCK A:ASP 382 A:PHE 383 A:GLY 384-159.6-91.66 123.29 19.3-32.18 172.47 MK14 A:ASP 168 A:PHE 169 A:GLY 17-142.3-49.27 57.91 11.22-43.9 32.99
Figure legends: Figure S1: Animated views of the collective variables used in the metadynamics simulation (a) This shows the movement of the N-terminal ATP binding β-sheet domain bearing K196 and a slight rotation of C-helix bearing E192. In the closed form the two residues are with 2.Å of each other leading to the formation of a salt-bridge while in the open form they move away >4.Å from each other. This center of masses for this motion represents the first collective variable (z) in our metadynamic simulations. (b) The position of the activation loop shown in active (green) and inactive (red) form of LRRK2. The CPK spheres shown in green represent the atoms used to define the center of mass for the loop and the collective variable (z) when it switches between active and inactive form. (c) Flip of the DYG motif of LRRK2 mediated by rotation of φ/ψ angles of the activation loop. The figure here is generated using the model coordinates for WT LRRK2. Figure S2: (a) Inhibition of LRRK2-catalyzed LRRKtide phosphorylation by Imatinib. Initial velocities was measured for the mutant G219S (A) and WT (D) as a function of [ATP] at different [Imatinib] as shown in the panel and at a fixed LRRKtide concentration of 5 µm. B & C (for G219S) or E & F (for WT): Imatinib concentration dependencies of (kcat)atp and (kcat/km)atp apparent values derived from analysis of the data of panel A & D. (b) Inhibition of LRRK2-catalyzed LRRKtide phosphorylation by Sorafenib. A & B (for G219S) or D & E (for WT): Sorafenib concentration dependencies of (kcat)atp and (kcat/km)atp apparent values derived from analysis of the initial velocity data. C (for the mutant) & F (for WT): Ki,app values were plotted against [ATP]. Due to the apparent partial inhibition of Sorafenib at higher ATP concentration, it is difficult to determine the inhibition mechanism using the replot methods for WT. Instead, the shape of the plot of Ki,app vs. [ATP] was used. The Ki,app values of Sorafenib linearly increases with [ATP] for the mutant G219S, suggesting an ATP competitive
inhibition. The Ki,app values of Sorafenib is independent of [ATP] for WT, suggesting an ATP noncompetitive inhibition. (c) Inhibition of LRRK2-catalyzed LRRKtide phosphorylation by Bosutinib. Initial velocities was measured for the mutant G219S (A) and WT (D) as a function of [ATP] at different [Bosutinit] as shown in the panel and at a fixed LRRKtide concentration of 5 µm. B & C (for G219S) or E & F (for WT): Bosutinib concentration dependencies of (kcat)atp and (kcat/km)atp apparent values derived from analysis of the data of panel A & D. Figure S3: (a) Overall architecture of LRRK2 kinase domain generated using Modeller. The structure shows an archetypal kinase fold with two major domains. The N-terminal β-sheet rich domain and the largely α-helical C-terminal domain with the ATP docked into the binding cleft. The positions of the Parkinson s disease linked mutations G219S and I22T are shown in CPK. (b) Structural details of the ATP binding site of LRRK2 with ATP docked in. ATP phosphate groups make hydrogen bonds with the backbone atoms of the glycine-rich loop. The adenine substructure makes hydrogen bonds with the hinge region. In addition, the DYG motif on the activation loop stabilizes a Mg 2+ ion, which in turns makes salt-bridge like interactions with the phosphates of ATP. Residues from the catalytic loop K1996 and H1998 provide additional stabilizing interactions to the bound ATP. (c) Surface representation of the DYG-in and DYG-out structures of LRRK2. Green denotes hydrophobic residues, red denotes negatively charged and blue denotes positively charged residues. In the DYG-out conformation, the hydrophobic Tyr occupies part of the ATP binding pocket Figure S4: Free energy surface (FES) generated from metadynamic simulation of LRRK WT and G219S (top panel) generated using the φ/ψ angles of G219 and S219. There is a significant lowering of accessible conformation is observed for G219S relative to WT.
Figure S5: Ligand interaction diagrams for G219S in the DYG-in state and WT in DYG-out state with IFD docked DFG-out inhibitors, bosutinib, imatinib, sorafenib and poantinib. This figure accompanies figure 5 in the main text showing all of the residues that interact with the ligand. The hydrophobic residues are shown in green, negatively charged in red and positively charged in blue. A grey hue around the ligand atoms indicate solvent exposure and pink arrows indicate hydrogen from donor to acceptor.