Quality Control

As a quality control measure, the resulting simulation systems were individually inspected. Problems such as minimization or preparation failures (e.g. failure of the total energy to decrease during minimization, typically a result of omission of a disulfide bond, etc.), and large structural changes in the protein were identified and corrected. To ensure that all systems were correct, each simulation’s starting configuration was examined by hand.

After simulation, we aim to identify any structure that undergoes a considerable rearrangement or lacks a well-defined conformation. For native state simulations, no such rearrangements or lack of structure should occur. Simultaneously, we must keep in mind that small conformational changes from the experimentally determined starting structure are to be expected and small fluctuations may be necessary for structural stability. To quantify the stability of (native state) simulations, we calculated root-mean square deviation (RMSD) values based on only the Cα positions of residues that make up the ‘core’ of the protein: all residues that have a solvent-accessible surface of less than < 40 Ų. This prevents large movements of tails or surface loops in our simulations from significantly affecting RMSD values. We further defined a ‘median structure’ as the structure from the simulation that has the lowest RMSD value to all other structures. A median root-mean square fluctuation (mRMSF) can now be defined as the root of the average RMSD from every structure to the median structure. Additionally, the median root-mean square deviation (mRMSD) was defined as the RMSD between the starting structure and the median structure. For all simulated targets, these two values are correlated (R=0.74), with the mRMSD being approximately twice as large as the mRMSF. Clear outliers were simulations with mRMSD values above 4 Å or mRMSF values above 2 Å (Figure 1). Inspection of these simulations revealed several with large structural rearrangements and exposure of hydrophobic cores, whereas this was not observed in simulations with smaller mRMSD and mRMSF values.

Where NMR data are available from the PDB or the BioMagResBank (BMRB) [1] in formats that could be directly employed for analyses or readily converted by the DOCR tools [2], trajectories were analyzed in the context of those data. For the purposes of comparison to nuclear Overhauser effects (NOE), an experimental NOE was considered satisfied if the r-6 weighted distance of the closest pairs of protons specified by the constraint was less than 5.0 Å or the experimental upper-bound. Order parameters (S2 ), primarily in the form of main-chain amide, were calculated from MD trajectories as described in [3] and an R to the experimental values was used as a measure of agreement. Similarly, chemical shifts predicted from MD trajectories were compared to the experimental values by the measure of R. Residual dipolar couplings (RDC) from MD trajectories were calculated by the algorithm presented in [4] and compared with experimental data. All analyses were performed in ilmm with the exception of chemical shifts, which were calculated with SHIFTS [5].

References

1. Doreleijers JF, Mading S, Maziuk D, Sojourner K, Yin L, Zhu J, Markley JL, Ulrich EL. BioMagResBank database with sets of experimental NMR constraints corresponding to the structures of over 1400 biomolecules deposited in the Protein Data Bank. Journal of Biomolecular NMR, 26: 139-146, 2003.
2. Doreleijers JF, Nederveen AJ, Vranken W, Lin J, Bonvin AM, Kaptein R, Markley JL, Ulrich EL. BioMagResBank databases DOCR and FRED containing converted and filtered sets of experimental NMR restraints and coordinates from over 500 protein PDB structures. Journal of Biomolecular NMR,32: 1-12, 2005.
3. Wong KB, Daggett V. Barstar has a highly dynamic hydrophobic core: Evidence from molecular dynamics simulations and nuclear magnetic resonance relaxation data. Biochemistry, 37: 11182-11192, 1998.
4. Losonczi JA, Andrec M, Fischer MW, Prestegard JH. Order matrix analysis of residual dipolar couplings using singular value decomposition. Journal of Magnetic Resonance, 138: 334-342, 1999.
5. Osapay K, Case DA. A New Analysis of Proton Chemical-Shifts in Proteins. Journal of the American Chemical Society, 113: 9436-9444, 1991.