Algorithm improvements for molecular dynamics simulations

Wiley Interdisciplinary Reviews: Computational Molecular Science

Volumn 1, Issue 1, 2011, Pages 93-108

  Larsson, Per ^a   Hess, Berk ^a   Lindahl, Erik ^a  

^a STOCKHOLM UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM IMPROVEMENTS; CURRENT PERFORMANCE; DOMAIN DECOMPOSITIONS; GRAPHICS PROCESSING UNIT; IMPROVE PERFORMANCE; MASSIVE PARALLELISM; MOLECULAR DYNAMICS SIMULATIONS; NONBONDED INTERACTION;

COMPUTER GRAPHICS; DATA STRUCTURES; DOMAIN DECOMPOSITION METHODS; HARDWARE; MOLECULAR DYNAMICS; PROGRAM PROCESSORS; SUPERCOMPUTERS;

ALGORITHMS;

EID: 84862813004     PISSN: 17590876     EISSN: 17590884     Source Type: Journal    
DOI: 10.1002/wcms.3     Document Type: Article

References (103)

1. Rahman A. Correlations in the motion of atoms in liquid argon. Phys Rev 1964, 136(2A):A405-A411.
2. Alder BJ, Wainwright TE. Phase transition for a hard sphere system. J Chem Phys 1957, 27(5):1208-1209.
3. Allen MP, Tildesley DJ. Computer Simulations of Liquids Oxford, UK: Oxford Science Publications; 1987.
4. Frenkel D, Smit B. Understanding Molecular Simulation. London: Academic Press; 1996.
5. Brooks BR, Bruccoleri RE, Olafson BD, States DJ, Swaminathan S, Karplus M. CHARMM: a program for macromolecular energy, minimization, and dynamics calculation. J Comp Chem 1983, 4:187-217
6. Brooks BR, Brooks CL 3rd, Mackerell AD Jr, Nilsson L, Petrella RJ, Roux B, Won Y, Archontis G, Bartels C, Boresch S, et al. CHARMM: the biomolecular simulation program. J Comput Chem 2009, 30(10):1545-1614.
7. Case DA, Cheatham III TE, Darden T, Gohlke H, Luo R, Merz KM Jr, Onufriev A, Simmerling C, Wang B, Woods R. The Amber biomolecular simulation programs. J Comp Chem 2005, 26:1668-1688.
8. Nelson MT, Humphrey W, Gursoy A, Dalke A, Kalé LV, Skeel RD, Schulten K. NAMD: a parallel, object-oriented molecular dynamics program. Int J High Perform Comput Appl 1996, 10:251-268.
9. Hess B, Kutzner C, van der Spoel D, Lindahl E. GROMACS 4: algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comp 2008, 4:435.
10. Harvey MJ, Giupponi G, De Fabritiis G. ACEMD: accelerating bio-molecular dynamics in the microsecond time-scale. J Chem Theory Comput 2009, 5:1632-1639.
11. Bowers KJ, Chow E, Xu H, Dror RO, Eastwood MP, Gregersen BA, Klepeis JL, Kolossvary I, Moraes MA, Sacerdoti FD, et al. Scalable algorithms for molecular dynamics simulations on commodity clusters. In Supercomputing, 2006. SC'06. Proceedings of the ACM/EEEI 2006.
12. Rapaport D. The Art of Molecular Dynamics Simulations. Cambridge: Cambridge University Press; 1995.
13. Bowers KJ, Chow E, Xu H, Dror RO, Eastwood MP, Gregersen BA, Klepeis JL, Kolossvary I, Moraes MA, Sacerdoti FD, et al. Scalable algorithms for molecular dynamics simulations on commodity clusters. In ACM/IEEE SC 2006 Conference (SC'06); 2006, 43.
14. Shaw DE, Deneroff MM, Dror RO, Kuskin JS, Larson RH, Salmon JK, Young C, Batson B, Bowers KJ, Chao JC, et al. Anton: A special-purpose machine for molecular dynamics simulation. In ISCA '07. Proceedings of the 34th Annual International Symposium on Computer Architecture. New York, NY: ACM; 2007, 1-12.
15. Zhou R, Berne BJ. A new molecular dynamics method combining the reference system propagator algorithm with a fast multipole method for simulating proteins and other complex systems. J Chem Phys 1995, 103(21):9444-9459.
16. Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG. A smooth particle mesh Ewald potential. J Chem Phys 1995, 103:8577-8592.
17. Hess B. P-lincs: a parallel linear constraint solver for molecular simulation. J Chem Theory Comp 2007, 4: 116-122.
18. Nilsson L. Efficient table lookup without inverse square roots for calculation of pair wise atomic interactions in classical simulations. J Comput Chem 2009, 30(9):1490-1498.
19. Berendsen HJC, van der Spoel D, van Drunen R. GROMACS: a message-passing parallel molecular dynamics implementation. Comp Phys Comm 1995, 91:43-56.
20. Enenkel RF, Fitch BG, Germain RS, Gustavson FG, Martin A, Mendell M, Pitera JW, Pitman MC, Rayshubskiy A, Suits F, et al Custom math functions for molecular dynamics. IBM J Res Dev 2005, 49(2):465-474.
21. Shen MY, Freed KF. A simple method for faster nonbonded force evaluations. J Comput Chem 2005, 26(7):691-698.
22. Bekker H, Berendsen HJC, Dijkstra EJ, Achterop S, Drunen Rv, Spoel Dvd, Sijbers A, Keegstra H, Reitsma B, Renardus MKR. GROMACS method of virial calculation using a single sum. In: de Groot RA, Nadrchal J, eds. Physics Computing 92, Singapore: World Scientific; 1993, 257-261.
23. Bekker H, Dijkstra EJ, Renardus MKR, Berendsen HJC. An efficient, box shape independent non-bonded force and virial algorithm for molecular dynamics. Mol Sim 1995, 14: 137-152.
24. van der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC. GROMACS: fast, flexible and free. J Comp Chem 2005, 26:1701-1718.
25. Heinz TN, Hünenberger PH. A fast pairlist-construction algorithm for molecular simulations under periodic boundary conditions. J Comput Chem 2004, 25(12):1474-1486.
26. Berendsen HJC, Postma JPM, van Gunsteren WF, Hermans J. Interaction models for water in relation to protein hydration. In: Pullman B, ed. Intermolecular Forces. Dordrecht, the Netherlands: D. Reidel Publishing Company; 1981, 331-342.
27. Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML. Comparison of simple potential functions for simulating liquid water. J Chem Phys 1983, 79(2):926-935.
28. Anandakrishnan R, Onufriev AV. An n log n approximation based on the natural organization of biomolecules for speeding up the computation of long range interactions. J Comput Chem 2010, 31(4):691-706.
29. Sagui C, Darden T. Multigrid methods for classical molecular dynamics simulations of biomolecules. J Chem Phys 2001, 114:6578.
30. Skeel RD, Tezcan I, Hardy DJ. Multiple grid methods for classical molecular dynamics. J Comput Chem 2002, 23(6):673-684.
31. Hardy DJ, Stone JE, Schulten K. Multilevel summation of electrostatic potentials using graphics processing units. Parallel Comput 2009, 35(3):164-177.
32. Petrella RJ, Karplus M. Electrostatic energies and forces computed without explicit interparticle interactions: a linear time complexity formulation. J Comput Chem 2005, 26(8):755-787.
33. Greengard L, Rokhlin V. A fast algorithm for particle simulations. J Comp Phys 1987, 73(2):325-348.
34. Greengard L. Fast algorithms for classical physics. Science 1994, 265(5174):909-914.
35. Kurzak J, Pettitt BM. Fast multipole methods for particle dynamics. Mol Simul 2006, 32(10-11):775-790.
36. Lu B, Cheng X, Huang J, McCammon JA. Order n algorithm for computation of electrostatic interactions in biomolecular systems. Proc Natl Acad Sci USA 2006, 103(51):19314-19319.
37. Lu B, Cheng X, McCammon JA. New-version-fast-multipole-method accelerated electrostatic interactions in biomolecular systems. J Comput Phys 2007, 226(2):1348-1366.
38. Lu B, Cheng X, Huang J, McCammon JA. An adaptive fast multipole boundary element method for poisson-boltzmann electrostatics. J Chem Theory Comput 2009, 5(6):1692-1699.
39. Kurzak J, Pettitt BM. Message-passing implementation of the data diffusion communication model in fast multipole methods: large scale biomolecular simulations. J Algorithm Comput Technol 2008, 2(4):557-579.
40. Crocker MS, Hampton SS, Matthey T, Izaguirre JA. MDSIMAID: automatic parameter optimization in fast electrostatic algorithms. J Comput Chem 2005, 26(10):1021-1031.
41. Matthey T, Cickovski T, Hampton S, Ko A, Ma Q, Nyerges M, Raeder T, Slabach T, Izaguirre JA. ProtoMol, an object-oriented framework for prototyping novel algorithms for molecular dynamics. ACM Trans Math Softw (TOMS) 2004, 30(3):237-265.
42. Lindahl E, Hess B, van der Spoel D. GROMACS 3.0: a package for molecular simulation and trajectory analysis. J Mol Mod 2001, 7:306-317.
43. Le Grand S. Broad Phase Collision Detection with CUDA, in Nguyen H, ed. GPU Gems 3. Addison-Wesley Professional; 2007.
44. Stone JE, Phillips JC, Freddolino PL, Hardy DJ, Trabuco LG, Schulten K. Accelerating molecular modeling applications with graphics processors. J Comput Chem 2007, 28(16):2618-2640.
45. Friedrichs MS, Eastman P, Vaidyanathan V, Houston M, Legrand S, Beberg AL, Ensign DL, Bruns CM, Pande VS. Accelerating molecular dynamic simulation on graphics processing units. J Comput Chem 2009, 30(6):864-872.
46. Anderson JA, Lorenz CD, Travesset A. General purpose molecular dynamics simulations fully implemented on graphics processing units. J Comp Phys 2008, 227(10):5342-5359.
47. Eastman P, Pande VS. Efficient nonbonded interactions for molecular dynamics on a graphics processing unit. J Comput Chem 2009, 31:1268-1272.
48. Schmid N, Botschi M, Van Gunsteren WF. A GPU solvent-solvent interaction calculation accelerator for biomolecular simulations using the GROMOS software. J Comput Chem 2010, 31:1636-1643.
49. Harvey MJ, De Fabritiis G. An implementation of the smooth particle Mesh Ewald method on GPU hardware. J Chem Theory Comput 2009, 5(9):2371-2377.
50. Buch I, Harvey MJ, Giorgino T, Anderson DP, De Fabritiis G. High-throughput all-atom molecular dynamics simulations using distributed computing. J Chem Inf Model 2010, 50(3):397-403.
51. Tuckerman M, Berne BJ, Martyna GJ. Reversible multiple time scale molecular dynamics. J Chem Phys 1992, 97(3):1990-2001.
52. Zhou J, Reich S, Brooks BR. Elastic molecular dyanmics with self-consistent flexible constraints. J Chem Phys 2000, 112:7919-7929.
53. Hess B, Saint-Martin H, Berendsen HJC. Flexible constraints: an adiabatic treatment of quantum degrees of freedom, with application to the flexible and polarizable MCDHO model for water. J Chem Phys 2002, 116:9602.
54. Guntert P, Mumenthaler C, Wuthrich K. Torsion angle dynamics for NMR structure calculation with the new program DYANA. J Mol Biol 1997, 273(1):283-298.
55. Ryckaert JP, Ciccotti G, Berendsen HJC. Numerical integration of the cartesian equations of motion of a system with constraints; molecular dynamics of n-alkanes. J Comp Phys 1977, 23:327-341.
56. Barth E, Kuczera K, Leimkuhler B, Skeel RD. Algorithms for constrained molecular dynamics. J Comp Chem 1995, 16:1192-1209.
57. Lowe CP, Bailey AG. MILCH SHAKE: an efficient method for constraint dynamics applied to alkanes. J Comput Chem 2009, 30(15):2485-2493.
58. Eastman P, Pande VS. Constant constraint matrix approximation: a robust, parallelizable constraint method for molecular simulations. J Chem Theory Comput 2010, 6(2):434-437.
59. Ross AL, Bowers KJ, Dror RO, Eastwood MP, Gregersen BA, Klepeis JL, Kolossvary I, Shaw DE. A common, avoidable source of error in molecular dynamics integrators. J Chem Phys 2007, 126:046101.
60. Hans CA. Rattle: a velocity version of the shake algorithm for molecular dynamics calculations. J Comp Phys 1983, 52:24-34.
61. Miyamoto S, Kollman PA. SETTLE: an analytical version of the SHAKE and RATTLE algorithms for rigid water models. J Comp Chem 1992, 13:952-962.
62. Kraeutler V, van Gunsteren WF Hünenberger, PH. A fast SHAKE algorithm to solve distance constraint equations for small molecules in molecular dynamics simulations. J Comput Chem 2001, 22(5):501-508.
63. Gonnet P. P-SHAKE: a quadratically convergent shake in. J Comput Phys 2006, 220(10):740-750.
64. van Gunsteren WF, Karplus M. Effect of constraints on the dynamics of macromolecules. Macromolecules 1982, 15:1528-1544.
65. Feenstra KA, Hess B, Berendsen HJC. Improving efficiency of large time-scale molecular dynamics simulations of hydrogen-rich systems. J Comp Chem 1999, 20:786-798.
66. Bjelkmar P, Larsson P, Cuendet MA, Hess B, Lindahl E. Implementation of the CHARMM force field in GROMACS: analysis of protein stability effects from correction maps, virtual interaction sites, and water models. J Chem Theory Comp 2010, 6(2):459-466.
67. Heffelfinger GS. Parallel atomistic simulations. Comp Phys Comm 2000, 128(1-2):219-237.
68. Bowers KJ, Dror RO, Shaw DE. Overview of neutral territory methods for the parallel evaluation of pairwise particle interactions. J Phys Conf Ser 2005, 16:300-304
69. Liem SY, Brown D, Clarke JHR. Molecular dynamics simulations on distributed memory machines. Comput Phys Commun 1991, 67(2):261-267.
70. Bowers KJ, Dror RO, Shaw DE. The midpoint method for parallelization of particle simulations. J Chem Phys 2006, 124(18): 184109-184109.
71. Shaw DE. A fast, scalable method for the parallel evaluation of distance-limited pairwise particle interactions. J Comp Chem 2005, 26:1318-1328.
72. Bowers KJ, Dror RO, Shaw DE. Zonal methods for the parallel execution of range-limited n-body simulations. J Comp Phys 2007, 221:303-329.
73. Phillips JC, Stone JE, Schulten K. Adapting a message-driven parallel application to GPU-accelerated clusters. In Proceedings of the 2008 ACM/IEEE Conference on Supercomputing. New York: IEEE Press; 2008, 1-9.
74. Kikugawa G, Apostolov R, Kamiya N, Taiji M, Himeno R, Nakamura H, Yonezawa Y. Application of MDGRAPE-3, a special purpose board for molecular dynamics simulations, to periodic biomolecular systems. J Comput Chem 2009, 30(1):110-118.
75. Nadler W, Hansmann UH. Optimized explicit-solvent replica exchange molecular dynamics from scratch. J Phys Chem B 2008, 112(34):10386-10387.
76. Rosta E, Buchete NV, Hummer G. Thermostat artifacts in replica exchange molecular dynamics simulations. J Chem Theory Comput 2009, 5(5):1393-1399.
77. Kubitzki MB, de Groot BL. Molecular dynamics simulations using temperature-enhanced essential dynamics replica exchange. Biophys J 2007, 92(12):4262-4270.
78. Kamberaj H, van der Vaart A. An optimized replica exchange molecular dynamics method. J Chem Phys 2009, 130(7):074906.
79. Swope WC, Pitera JW, Suits F. Describing protein folding kinetics by molecular dynamics simulations. 1. Theory. J Phys Chem B 2004, 108(21):6571-6581.
80. Jayachandran G, Vishal V, Pande VS. Using massively parallel simulation and Markovian models to study protein folding: examining the dynamics of the villin headpiece. J Chem Phys 2006, 124(16):164902.
81. Chodera JD, Singhal N, Pande VS, Dill KA, Swope WC. Automatic discovery of metastable states for the construction of Markov models of macromolecular conformational dynamics. J Chem Phys 2007, 126(15):155101.
82. Buchete NV, Hummer G. Coarse master equations for peptide folding dynamics. J Phys Chem B 2008, 112(19):6057-6069.
83. Bowman GR, Beauchamp KA, Boxer G, Pande VS. Progress and challenges in the automated construction of Markov state models for full protein systems. J Chem Phys 2009, 131(12):124101.
84. Kasson PM, Pande VS. Cross-graining: efficient multi-scale simulation via Markov state models. Pac Symp Biocomput 2010, 260-268.
85. Bowman GR, Ensign DL, Pande VS. Enhanced modeling via network theory: adaptive sampling of Markov state models. J Chem Theory Comput. In press.
86. Rhee YM, Jayachandran G, Sorin E, Lindahl E, Pande VS. Simulations of the role of water in the protein-folding mechanism. Proc Natl Acad Sci USA 2004, 101:6456-6461.
87. Fischer A, Waldhausen S, Horenko I, Meerbach E, Schutte C. Identification of biomolecular conformations from incomplete torsion angle observations by hidden Markov models. J Comput Chem 2007, 28(15):2453-2464.
88. Noe F, Schutte C, Vanden-Eijnden E, Reich L, Weikl TR. Constructing the equilibrium ensemble of folding pathways from short off-equilibrium simulations. Proc Natl Acad Sci USA 2009, 106(45):19011-19016.
89. Noe F, Horenko I, Schutte C, Smith JC. Hierarchical analysis of conformational dynamics in biomolecules: transition networks of metastable states. J Chem Phys 2007, 126(15):155102.
90. Voelz VA, Bowman GR, Beauchamp K, Pande VS. Molecular simulation of ab initio protein folding for a millisecond folder NTL9(1-39). J Am Chem Soc 2010, 132(5):1526-1528.
91. Bashford D, Case DA. Generalized born models of macromolecular solvation effects. Annu Rev Phys Chem 2000, 51:129-152.
92. Roux B, Simonson T. Implicit solvent models. Biophys Chem 1999, 78(1-2):1-20.
93. Qui D, Shenkin PS, Hollinger FP, Still WC. The GB/SA continuum model for solvation. A fast analytical method for the calculation of approximate born radii. J Phys Chem A 1997, 101:3005-3014.
94. Luo R, David L, Gilson MK. Accelerated poisson-boltzmann calculations for static and dynamic systems. J Comput Chem 2002, 23(13):1244-1253.
95. Prabhu NV, Zhu P, Sharp KA. Implementation and testing of stable, fast implicit solvation in molecular dynamics using the smooth-permittivity finite difference Poisson-Boltzmann method. J Comput Chem 2004, 25(16):2049-2064.
96. Schwarzl SM, Huang D, Smith JC, Fischer S. Nonuniform charge scaling (NUCS): a practical approximation of solvent electrostatic screening in proteins. J Comput Chem 2005, 26(13):1359-1371.
97. Larsson P, Lindahl E. A method for interaction rescaling to enable high-performance tabulated generalized born simulations. J Comput Chem. In press.
98. Michel J, Taylor RD, Essex JW. Efficient generalized born models for monte carlo simulations. J Chem Theory Comput 2006, 2:732-739.
99. Haberthur U, Caflisch A. FACTS: fast analytical continuum treatment of solvation. J Comput Chem 2008, 29(5):701-715.
100. Guvench O, Brooks CL, 3rd. Efficient approximate all-atom solvent accessible surface area method parameterized for folded and denatured protein conformations. J Comput Chem 2004, 25(8):1005-1014.
101. Durham E, Dorr B, Woetzel N, Staritzbichler R, Meiler J. Solvent accessible surface area approximations for rapid and accurate protein structure prediction. J Mol Model 2009, 15(9):1093-1108.
102. Dynerman D, Butzlaff E, Mitchell JC. CUSA and CUDE: GPU-accelerated methods for estimating solvent accessible surface area and desolvation. J Comput Biol 2009, 16(4):523-537.
103. Hayryan S, Hu CK, Skrivanek J, Hayryane E, Pokorny I. A new analytical method for computing solvent-accessible surface area of macromolecules and its gradients. J Comput Chem 2005, 26(4):334-343.