Computational approaches can yield important details about the interaction of RD with DNA and CBFb (21). For example, the energetic contribution of individual residues to both DNA and CBFb binding can be determined. By doing such analysis in systems with all wild-type residues present, the risk of mutation induced conformational change, including changes in protein stability, is avoided. Computational analysis can also account for the contribution of all atoms in a given residue, including the backbone atoms, whereas mutational analysis can only detect the importance of side chain atoms. Thus, computational analysis can ﬁll gaps in understanding the RD–DNA, RD–CBFb and CBFb–RD–DNA ternary complex interactions. In the present work, the RD was subjected to molecular dynamic (MD) simulations in the free state and in several complexes. Complexes include the binary RD–DNA and RD–CBFb complexes, and the CBFb–RD–DNA ternary com- plex. In addition, two DNA simulations and a CBFb monomer simulation were performed. From the MD simulations, in combination with free energy component analysis (22–24) based on the Generalized-Born model (25,26), overall binding energies, desolvation effects and detailed interaction energies were calculated. These results, along with previous structural analysis and observations, were used to interpret a variety of experimental data involving RD–DNA and RD–CBFb interactions (16–19,27). METHODS MD simulations and all calculations were performed using the program CHARMM (28). The all-hydrogen CHARMM22 protein (29) and CHARMM27 nucleic acid (30,31), the TIP3P water model (32), along with published sodium and chloride parameters were used (33). Coordinates from the CBFb–RD– DNA ternary complex X-ray crystal structure (PDB accession code 1H9D) (13) were used as starting structures of the seven simulation systems (Supplementary Table S1). The only exception was the second DNA simulation, which was initi- ated with the DNA in the canonical B form (34), as obtained from the program Quanta (Accelrys Inc.). In the crystal structure terminal residues 50–53 and 179–183 in RD are not observed experimentally as are residues 71–79 of CBFb. Accordingly, in the simulations these residues were omitted. Omission of residues 71–79 of CBFb, which are spatially removed from the RD in the experimental structure (Figure 1), was performed by creating a peptide bond between residues 70 and 80 and relaxing the structure during the min- imization and MD simulation protocols described below. Root-mean-square (RMS) difference analysis of the residues adjacent to the deleted residues in CBFb (i.e. residues 66–70 and 80–84) showed signiﬁcant structural changes to occur only in the one or two residues directly adjacent to the deleted residues (Supplementary Table S2). Each structure to be simulated was generated with CHARMM and the hydrogens added. The dimensions of each complex (solute) were determined, and a box of solvent was prepared to overlay the solute. The edge of the solvent was extended to a minimum of 8 s beyond the solute in each dimension. Then each solute was overlaid with the solvent water box that also contained either sodium or chloride ions, Nucleic Acids Research, 2005, Vol. 33, No. 13 4213 Figure 1. Ribbon image of the CBFb–RD–DNA after 4.5 ns dynamics simulation including coloring of the RD segments used for analysis (Table 2). DNA (green), CBFb (tan) and residues surrounding omitted residues 71–79 in CBFb (red). depending on the total charge of the solute. All water molecules whose oxygen atom was within 2.5 s of any solute non-hydrogen atom were then deleted and excess ions were deleted to make the systems electrically neutral. Details of the systems are shown in Supplementary Table S1. All subsequent calculations were performed using periodic boundary condi- tions, with images generated using the CRYSTAL module of CHARMM. Equilibration of each simulation system was carried out by performing 500 steps of steepest descent energy minimization followed by a 10 ps MD NVT simulation with harmonic restraints of 5 kcal/(mol s) on the solute non-hydrogen atoms. Additional minimization using the Adopted Basis Newton–Raphson (ABNR) algorithm was performed for 100 steps without any restraints. The systems were then sub- jected to a 5 ns MD simulation in the NPT ensemble at 300 K with the Leap Frog integrator, and a time step of 0.002 ps. Pressure control was performed with the Langevin Piston algorithm (35). SHAKE was used to constrain covalent bonds involving hydrogens (36). Particle Mesh Ewald (PME) was used to treat long-range electrostatic interactions (37). PME calculations were carried out using real space electrostatic and Lennard–Jones interaction cutoffs at 10 s, with utilization of heuristic non-bond list update out to 12 s and smoothing of the LJ interactions from 8 to 10 s using the force switch method (38). The ﬁrst 500 ps of the simulations were treated as equi- libration. Coordinates were saved every 5 ps, and by the end of the 4.5 ns production MD simulation, 900 sets of structural coordinates were available for analysis. Structural ﬁgures were generated using the program VMD (39) and rendered by Raster3D (40). Calculation of binding free energies via free energy com- ponent analysis: binding free energies, DGbind, were calculated as follows: DGbind ¼ Gcomplex GpartnerA GpartnerB‚ 1