Accelerated molecular dynamics simulation with the parallel fast multipole algorithm

Board, John A.; Causey, Jeffrey W.; Leathrum, James F.; Windemuth, Andreas; Schulten, Klaus

doi:10.1016/0009-2614(92)90053-p

Cited by 175 publications

(77 citation statements)

References 14 publications

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“…This approach provides important information also relevant for conformations adopted in the structured environment of a protein binding site. Through exhausive searches of the Cambridge Crystallographic Data Base'" - 231 we have retrieved conformational libraries for torsional fragments. These libraries can be used in a conformational analysis to generate biologically relevant confomations.…”

Section: Conformational Libraries Derived From Crystal Structuresmentioning

confidence: 99%

What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?

Böhm

Klebe

1996

Angew. Chem. Int. Ed. Engl.

312

156

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The understanding of noncovalent interactions in protein-ligand complexes is essential in modern biochemistry and should contribute toward the discovery of new drugs. In the present review, we summarize recent work aimed at a better understanding of the physical nature of molecular recognition in protein -ligand complexes and also at the development and application of new computational tools that exploit our current knowledge on structural and energetic aspects of ~~ ~ protein-ligand interactions in the design of novel ligands. These approaches are based on the exponentially growing amount of information about the geometry of protein structures and the properties of small organic molecules exposed to a structured molecular environment. The various contributions that determine the binding affinity of ligands toward a particular receptor are discussed. Their putative binding site conformations are analyzed, and some predictions are attempted. The similarity of ligands is examined with respect to their recognition properties. This information is used to understand and propose binding modes. In addition, an overview of the existing methods for the design and selection of novel protein ligands is given.

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Section: Conformational Libraries Derived From Crystal Structuresmentioning

confidence: 99%

What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?

Böhm

Klebe

1996

Angew. Chem. Int. Ed. Engl.

312

156

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“…Increases in computing power allowed inclusion of solvent for small systems (bovine pancreatic trypsin inhibitor, N atoms~3 100, τ 2 5 ps) (Van Gunsteren and Karplus 1982). Fast multipole algorithms were used to achieve simulation sizes of 1.26 x10 4 (τ ~ 40 ps, photosynthetic reaction center of Rhodopseudomonas viridis) (Heller et al 1990), 2.4x10 4 (POPC lipid bilayer patch) (Board et al 1992), and 3.6x10 4 atoms (τ ~ 1 ps, estrogen receptor binding domain plus DNA complex) (Nelson et al 1996). Simulations of the HIV-1 protease using a CRAY YMP with vector parallelization were also performed (N atoms ~ 2.3x10 4 , τ ~ 40 ps) ).…”

Section: Introductionmentioning

confidence: 99%

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

Sanbonmatsu

Tung

2007

Journal of Structural Biology

169

107

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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 nanoscale 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.

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“…Our code has allowed us to make significant progress in the study of galaxy dynamics [22] and cosmology [23]. In addition, we note applications in molecular dynamics [29], computational fluid dynamics [30,31] and partial differential equations relevant to biology [32]. Fast multipole methods have been used to address twodimensional problems in potential flows [33], and electromagnetic scattering [34].…”

Section: Resultsmentioning

confidence: 99%

A portable parallel particle program

Warren

Salmon

1995

Computer Physics Communications

133

119

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We describe our implementation of the parallel hashed oct-tree (HOT) code, and in particular its application to neighbor finding in a smoothed particle hydrodynamics (SPH) code. We also review the error bounds on the multipole approximations involved in treecodes, and extend them to include general cell-cell interactions. Performance of the program on a variety of problems (including gravity, SPH, vortex method and panel method) is measured on several parallel and sequential machines.

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Accelerated molecular dynamics simulation with the parallel fast multipole algorithm

Cited by 175 publications

References 14 publications

What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?

What Can We Learn from Molecular Recognition in Protein–Ligand Complexes for the Design of New Drugs?

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

A portable parallel particle program

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