System setup on wild type and L205R. We used the crystal structure of PKA-CWT (PDB ID: 1ATP) (28) and PKA-CL205R (PDB ID: 4WB6) (16) as the template and chose a monomer (chain A, protein; chain I, PKI5–24) from the dimer. We further aligned the current structure with the full-length PKA-CWT and added the missing residues 1 to 12 at the N terminus. The protonation state of histidine residues followed our previous settings (27). The protein was solvated in a rhombic dodecahedron solvent box with a TIP3P water molecule layer extended approximately 10 Å away from the surface of the proteins. Counter ions (K+ and Cl) were added to ensure electrostatic neutrality corresponding to an ionic concentration of ~150 mM. All protein covalent hydrogen bonds were constrained with the LINCS (linear constraint solver) algorithm, and long-range electrostatic interactions were treated with the particle-mesh Ewald method with a real-space cutoff of 10 Å. Parallel simulations on the apo form, the binary form with one Mg2+ ion and one ATP, and the ternary form with two Mg2+ ions, one ATP, and one PKI5–24 were performed simultaneously using GROMACS 4.6 (44) in CHARMM36a1 force fields (45). Each system was minimized using the steepest decent algorithm to remove the bad contacts and then gradually heated to 300 K at a constant volume over 1 ns, using harmonic restraints with a force constant 1000 kJ/(mol·Å2) on heavy atoms of both proteins and nucleotides. Over the following 12 ns of simulations at constant pressure (1 atm) and temperature (300 K), the restraints were gradually released. The systems were equilibrated for an additional 20 ns without positional restraints. A Parrinello-Rahman barostat was used to keep the pressure constant, while a V-rescale thermostat with a time step of 2 fs was used to keep the temperature constant. Each system was simulated for 1.05 μs, with snapshots recorded every 20 ps. A total of 3.15 μs and 157,500 conformations were used for the analyses.

Energy landscapes using PCA. Cartesian principal components of the backbone atoms were calculated using the GROMACS modules g_covar and g_anaeig to identify the large-scale, low-frequency conformational dynamics of the catalytic core. All the trajectories were aligned with the starting structure (minimization of the crystal structure to remove bad contacts) using helices E (residues 140 to 160) and F (residues 217 to 233) as a reference frame. Dominant principal components were computed from each resulting ensemble from the individual simulations. Moreover, the distance between the Cα atom of Ser53 and Gly186 was measured to characterize the opening and closing motions of the Gly-rich loop. Different trajectories were mapped onto the 2D projection along PC1 and S53-G186 distances.

Docking and simulation of the ternary complexes bound with VPS36 peptide and ATP. We used the unwound conformation of VPS36 and used HADDOCK (46) server for docking into the binding cleft of PKA-C for both wild type and L205R. Specifically, we used the easy interface and selected the active residues of PKA-C, i.e., 133, 168, 202, 198, 204, 205, 207, 230, and 330, as well as the active residues for VPS36, i.e., 3, 6, 7, 9, and 10. The passive residues were set automatically around the active residues by the server. The top-scored structures were further solvated for MD simulations following the same protocol as the ternary complexes with PKI.

Mutual information analysis and mapping of the allosteric network. To monitor the allosteric differences of the wild type and L205R, MutInf (29) was used to compute mutual information between all residues. MutInf is a python package that translates the distribution of dihedral angles of residues into their conformational entropy and identifies the correlated motions between residues. The time series of dihedral angles in the MD ensemble was computed using g_chi and divided into six overlapped blocks, and then, correlations of local motions were computed as the mutual information between selected residue pairs in each block. The results were averaged over these blocks to filter out the correlations that were not statistically significant. These matrices of mutual information and their differences were further mapped onto the crystal structure. Graph analysis was applied to detect hubs in the networks and key allosteric communication pathways in PKA-C.

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