The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Anton, a special-purpose machine for molecular dynamics simulation
Open accessAbstract
The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macro-molecules could in principle provide answers to some of the most important currently outstanding questions in the fields of biology, chemistry, and medicine. A wide range of biologically interesting phenomena, however, occur over timescales on the order of a millisecond---several orders of magnitude beyond the duration of the longest current MD simulations. We describe a massively parallel machine called Anton, which should be capable of executing millisecond-scale classical MD simulations of such biomolecular systems. The machine, which is scheduled for completion by the end of 2008, is based on 512 identical MD-specific ASICs that interact in a tightly coupled manner using a specialized highspeed communication network. Anton has been designed to use both novel parallel algorithms and special-purpose logic to dramatically accelerate those calculations that dominate the time required for a typical MD simulation. The remainder of the simulation algorithm is executed by a programmable portion of each chip that achieves a substantial degree of parallelism while preserving the flexibility necessary to accommodate anticipated advances in physical models and simulation methods.
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GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation
Hess, B., Kutzner, C., van der Spoel, D., & Lindahl, E. (2008) · Journal of Chemical Theory and Computation · doi:10.1021/ct700301q · Cited by 15,908
Jorgensen, W. L., Maxwell, D. S., & Tirado-Rives, J. (1996) · Journal of the American Chemical Society · doi:10.1021/ja9621760 · Cited by 15,409
All-Atom Empirical Potential for Molecular Modeling and Dynamics Studies of Proteins
MacKerell, A. D., Bashford, D., Bellott, M., Dunbrack, R. L., Evanseck, J. D., Field, M. J., Fischer, S., Gao, J., Guo, H., Ha, S., et al. (1998) · The Journal of Physical Chemistry B · doi:10.1021/jp973084f · Cited by 14,311
Molecular dynamics---Scalable algorithms for molecular dynamics simulations on commodity clusters
Bowers, K. J., Sacerdoti, F. D., Salmon, J. K., Shan, Y., Shaw, D. E., Chow, E., Xu, H., Dror, R. O., Eastwood, M. P., Gregersen, B. A., et al. (2006) · Proceedings of the 2006 ACM/IEEE conference on Supercomputing - SC '06 · doi:10.1145/1188455.1188544 · Cited by 2,580
Self-citationNAMD2: Greater Scalability for Parallel Molecular Dynamics
Kalé, L., Skeel, R., Bhandarkar, M., Brunner, R., Gursoy, A., Krawetz, N., Phillips, J., Shinozaki, A., Varadarajan, K., & Schulten, K. (1999) · Journal of Computational Physics · doi:10.1006/jcph.1999.6201 · Cited by 2,428
Molecular Dynamics: Survey of Methods for Simulating the Activity of Proteins
Adcock, S. A., & McCammon, J. A. (2006) · Chemical Reviews · doi:10.1021/cr040426m · Cited by 1,272
Gaussian split Ewald: A fast Ewald mesh method for molecular simulation
Shan, Y., Klepeis, J. L., Eastwood, M. P., Dror, R. O., & Shaw, D. E. (2005) · The Journal of Chemical Physics · doi:10.1063/1.1839571 · Cited by 432
Self-citationPande, V. S., Baker, I., Chapman, J., Elmer, S. P., Khaliq, S., Larson, S. M., Rhee, Y. M., Shirts, M. R., Snow, C. D., Sorin, E. J., et al. (2003) · Biopolymers · doi:10.1002/bip.10219 · Cited by 369
Kollman, P., Dixon, R., Cornell, W., Fox, T., Chipot, C., & Pohorille, A. (1997) · Computer Simulation of Biomolecular Systems · doi:10.1007/978-94-017-1120-3_2 · Cited by 242
Shaw, D. E. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20267 · Cited by 226
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Molecular Dynamics Simulation for All
Hollingsworth, S. A., & Dror, R. O. (2018) · Neuron · doi:10.1016/j.neuron.2018.08.011 · Cited by 3,257
Self-citationRoutine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born
Götz, A. W., Williamson, M. J., Xu, D., Poole, D., Le Grand, S., & Walker, R. C. (2012) · Journal of Chemical Theory and Computation · doi:10.1021/ct200909j · Cited by 2,046
The Protein-Folding Problem, 50 Years On
Dill, K. A., & MacCallum, J. L. (2012) · Science · doi:10.1126/science.1219021 · Cited by 1,699
Unke, O. T., Chmiela, S., Sauceda, H. E., Gastegger, M., Poltavsky, I., Schütt, K. T., Tkatchenko, A., & Müller, K.-R. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c01111 · Cited by 1,647
Salmaso, V., & Moro, S. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.00923 · Cited by 666
Metadata
- Authors
- Shaw, D. E., Deneroff, M. M., Dror, R. O., Kuskin, J. S., Larson, R. H., Salmon, J. K., Young, C., Batson, B., Bowers, K. J., Chao, J. C., Eastwood, M. P., Gagliardo, J., Grossman, J. P., Ho, C. R., Ierardi, D. J., Kolossváry, I., Klepeis, J. L., Layman, T., McLeavey, C., Moraes, M. A., Mueller, R., Priest, E. C., Shan, Y., Spengler, J., Theobald, M., Towles, B., & Wang, S. C.
- Venue
- Communications of the ACM
- Published
- 2008-07
- Volume
- 51
- Issue
- 7
- Pages
- 91-97
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2028263411
- Cited by
- 817
- References
- 22
- FWCI
- 54.51
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Shaw, D. E., Deneroff, M. M., Dror, R. O., Kuskin, J. S., Larson, R. H., Salmon, J. K., Young, C., Batson, B., Bowers, K. J., Chao, J. C., Eastwood, M. P., Gagliardo, J., Grossman, J. P., Ho, C. R., Ierardi, D. J., Kolossváry, I., Klepeis, J. L., Layman, T., McLeavey, C., . . . Wang, S. C. (2008). Anton, a special-purpose machine for molecular dynamics simulation. Communications of the ACM. https://doi.org/10.1145/1364782.1364802
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