Fig. 5: MD-simulations feature  a highly dynamic M2 domain in PAPP-A2.

a Open conformations of PAPP-A2 structures emerged from three independent replicates of MD simulations using the CHARMM36m force field. The snapshots were captured at time points: 600 ns of replicate 1 (left), 600 ns of replicate 2 (middle), and 628 ns of replicate 3 (right). Conformational changes in PAPP-A2, crucial for substrate recognition, were evaluated based on the distances between the M1 domain (center of mass of Cα atoms of residues: 610-927) and the M2 domain (center of mass of Cα atoms of residues: 953-1160), as well as the M2 domain and the anchor peptide (center of mass of Cα atoms of residues: 120-143). For the sake of clarity, the remainder of the C-terminus of PAPP-A2 (residues 1167 to the end) is not depicted. b Graphs depicting simulation results: M2-M1 distance (top), M2-anchor peptide distance (middle), and RMSD values for Cα atoms (bottom). RMSD values were measured relative to the AlphaFold multimer (AFM) construct at the start of the simulations (t = 0 ns). Exponential moving averages over the trajectory are shown as solid lines. For each replicate, average and standard deviation were computed using block averaging, using the final 400 ns frames to reduce the effects of initial transients. Eight blocks of 50 ns frames were used for measurement. c Distribution histograms: distance between M2 and M1 domains (top), and distance between the M2 domain and the anchor peptide (bottom). Histograms are based on the last 400 ns frames of all production simulations. To estimate distance distributions, a Gaussian kernel density estimator was applied using Python’s scikit-learn package, using a covariance factor of 3 Å. The overall average and standard deviation for three replicates are as follows: M1-M2 distance = 62.9 ± 5.3 Å and M2-anchor peptide distance = 51.7 ± 7.1 Å. The AlphaFold multimer (AFM) distances are shown as dashed lines in the plots. The cut-off distances were calculated as AFM distance + 0.5 * standard deviation, to capture a region that extends beyond the AFM close state while considering the spread of the distribution. Simulation run graphs for replicate 2 and 3 are shown in Supplementary Fig. 16a.