Molecular Dynamics Simulation on a Parallel Computer

High performance computing in biology: multimillion atom simulations of nanoscale systems

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nano-scale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail.

Ligand binding: molecular mechanics calculation of the streptavidin-biotin rupture force

The force required to rupture the streptavidin-biotin complex was calculated here by computer simulations. The computed force agrees well with that obtained by recent single molecule atomic force microscope experiments. These simulations suggest a detailed multiple-pathway rupture mechanism involving five major unbinding steps. Binding forces and specificity are attributed to a hydrogen bond network between the biotin ligand and residues within the binding pocket of streptavidin. During rupture, additional water bridges substantially enhance the stability of the complex and even dominate the binding interactions. In contrast, steric restraints do not appear to contribute to the binding forces, although conformational motions were observed.

Molecular dynamics study of glucocorticoid receptor-DNA binding

Molecular dynamics simulations have been conducted to investigate the binding of the glucocorticoid receptor (GR) dimer to DNA. For this purpose simulations of the complex formed by a DNA segment and a dimer of GR-DNA binding domains (GR-DBD) have been carried out, employing an available X-ray structure. A second set of simulations was based on this structure as well, except that the DNA segment was altered to the consensus glucocorticoid response element (GRE). Simulations of a single GR-DBD and of the uncomplexed GRE served as controls. For the simulations, each system was encapsulated in an ellipsoid of water. Protein-DNA interactions, dimer interactions, and DNA structural parameters were analyzed for each system and compared. The consensus GRE is found to yield more favorable and symmetric interactions between the GR-DBDs and the GRE, explaining the ability of the GR dimer to recognize this DNA segment. Further analysis focused on deformations of the DNA that are induced by the binding of GR. The deformations observed involve a 35 degree bend of the DNA, an unwinding, and a displacement of the helical axis. These deformations are consistent with a mechanism for transcriptional regulation that involves a change of nucleosome packing upon GR binding. Significant protein-protein and protein-DNA interactions, both direct and water mediated, develop due to the deformations of the GRE and are indicative of an increased recognition achieved through DNA deformation. The interactions include direct interactions between the GRE and glycine-458 and serine-459, side groups which differentiate GR from other members of the nuclear hormone receptor family.

Molecular dynamics simulation on a network of workstations using a machine-independent parallel programming language

Molecular dynamics simulations investigate local and global motion in molecules. Several parallel computing approaches have been taken to attack the most computationally expensive phase of molecular simulations, the evaluation of long range interactions. This paper reviews these approaches and develops a straightforward but effective algorithm using the machine-independent parallel programming language, Linda. The algorithm was run both on a shared memory parallel computer and on a network of high performance Unix workstations. Performance benchmarks were performed on both systems using two proteins. This algorithm offers a portable cost-effective alternative for molecular dynamics simulations. In view of the increasing numbers of networked workstations, this approach could help make molecular dynamics simulations more easily accessible to the research community.