Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom molecular dynamics simulation is the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes in explicit solvent. Here, we report simulation results for the ribosome, using 2.64 million atoms, approximately 6 times larger than the largest previously published all-atom biomolecular simulation. The performance of the LANL Q Machine as a function of the number of atoms simulated was measured. The NAMD (UIUC) molecular dynamics simulation program displays approximately 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. Targeted molecular dynamics simulations of the ribosome have enabled us to identify candidate 23S rRNA nucleotides important for protein synthesis and antibiotic design.