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Constant pressure hybrid Monte Carlo simulations in GROMACS

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Abstract

Adaptation and implementation of the Generalized Shadow Hybrid Monte Carlo (GSHMC) method for molecular simulation at constant pressure in the NPT ensemble are discussed. The resulting method, termed NPT-GSHMC, combines Andersen barostat with GSHMC to enable molecular simulations in the environment natural for biological applications, namely, at constant pressure and constant temperature. Generalized Hybrid Monte Carlo methods are designed to maintain constant temperature and volume and extending their functionality to preserving pressure is not trivial. The theoretical formulation of NPT-GSHMC was previously introduced. Our main contribution is the implementation of this methodology in the GROMACS molecular simulation package and the evaluation of properties of NPT-GSHMC, such as accuracy, performance, effectiveness for real physical systems in comparison with well-established molecular simulation techniques. Benchmarking tests are presented and the obtained preliminary results are promising. For the first time, the generalized hybrid Monte Carlo simulations at constant pressure are available within the popular open source molecular dynamics software package.

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References

  1. Andersen HC (1980) Molecular dynamics simulations at constant pressure and/or temperature. J Chem Phys 72:2384–2393

    Article  CAS  Google Scholar 

  2. Parrinello M, Rahman A (1981) Polymorphic transitions in single crystals: a new molecular dynamics method. J Appl Phys 52:7182–7190

    Article  CAS  Google Scholar 

  3. Nosé S (1984) A unified formulation of the constant temperature molecular-dynamics methods. J Chem Phys 81(1):511–519

    Article  Google Scholar 

  4. Hoover WG (1985) Canonical dynamics: equilibrium phase-space distributions. Phys Rev A 31(3):1695–1697

    Article  Google Scholar 

  5. Evans DJ, Holian BL (1985) The Nose-Hoover thermostat. J Chem Phys 83:4069

    Article  CAS  Google Scholar 

  6. Martyna GJ, Tuckerman ME, Tobias DJ, Klein ML (1996) Explicit reversible integrators for extended systems dynamics. Molec Phys 87(5):1117–1157

    Article  CAS  Google Scholar 

  7. Berendsen HJC, Postma JPM, Van Gunsteren WF, DiNola A, Haak JR (1984) Molecular dynamics with coupling to an external bath. J Chem Phys 81:3684–3690

    Article  CAS  Google Scholar 

  8. Hess B, Kutzner C, Van der Spoel D, Lindahl E (2008) GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J Chem Theory Comput 4(3):435–447

    Article  CAS  Google Scholar 

  9. Berendsen HJC, Van der Spoel D, Van Drunen R (1995) GROMACS: A message-passing parallel molecular dynamics implementation. Comput Phys Comm 91:43–56

    Article  CAS  Google Scholar 

  10. Salomon-Ferrer R, Case DA, Walker RC (2013) An overview of the Amber biomolecular simulation package. WIREs Comput Mol Sci 3:198–210

    Article  CAS  Google Scholar 

  11. Plimpton S (1995) Fast Parallel Algorithms for Short-Range Molecular Dynamics. J Comput Phys 117:1–19

    Article  CAS  Google Scholar 

  12. Bowers KJ, Chow E, Xu H, Dror RO, Eastwood MP, Gregersen BA, Klepeis JL, Kolossváry I, Moraes MA, Sacerdoti FD, Salmon J K, Shan Y, Shaw DE (2006) Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters Proceedings of the ACM/IEEE Conference on Supercomputing (SC06), Tampa, Florida, November 11–17

  13. Duane S, Kennedy AD, Pendleton BJ, Roweth D (1987) Hybrid Monte Carlo. Phys Lett B 195:216–222

    Article  CAS  Google Scholar 

  14. Akhmatskaya E, Reich S (2008) GSHMC: An efficient method for molecular simulation. J Comput Phys 227:4934–4954

    Article  Google Scholar 

  15. Akhmatskaya E, Reich S, Nobes R (2011) Method, apparatus and computer program for molecular simulation. US patent (granted), US007908129

  16. Horowitz AM (1991) A generalized guided Monte Carlo algorithm. Phys Lett B 268:247–252

    Article  Google Scholar 

  17. Kennedy AD, Pendleton B (2001) Cost of the Generalised Hybrid Monte Carlo Algorithm for Free Field Theory. Nucl Phys B 607:456–510

    Article  Google Scholar 

  18. Izaguirre JA, Hampton SS (2004) Shadow hybrid Monte Carlo: an efficient propagator in phase space of macromolecules. J Comput Phys 200:581–604

    Article  CAS  Google Scholar 

  19. Akhmatskaya E, Reich S (2010) New Hybrid Monte Carlo Methods for Efficient Sampling: from Physics to Biology and Statistics. In: Proceedings of the Joint International Conference of the Supercomputing in Nuclear Application and Monte Carlo, Tokyo, Japan, October 17–21

  20. Wee CL, Sansom MS, Reich S, Akhmatskaya E (2008) Improved sampling for simulations of interfacial membrane proteins: application of generalized shadow hybrid Monte Carlo to a peptide toxin/bilayer system. J Phys Chem B 112(18):5710–5717

    Article  CAS  Google Scholar 

  21. Faller R, De Pablo JJ (2002) Constant pressure hybrid Molecular Dynamics-Monte Carlo simulations. J Chem Phys 116:55–59

    Article  CAS  Google Scholar 

  22. Bussi G, Donadio D, Parrinello M (2007) Canonical sampling through velocity rescaling. J Chem Phys 126:014101

    Article  Google Scholar 

  23. Escribano B, Akhmatskaya E, Mujika JI (2013) Combining stochastic and deterministic approaches within high efficiency molecular simulations. Cent Eur J Math 11(4):787–799

    Article  Google Scholar 

  24. GROMACS Programmer’s Guide, available at, URL http://www.gromacs.org/Developer_Zone/Programming_Guide/Programmer

  25. Kolb A, Dünweg B (1999) Optimized constant pressure stochastic dynamics. J Chem Phys 111:4453–4459

    Article  CAS  Google Scholar 

  26. Jung HJ, Lee JY, Kim S H, Eu YJ, Shin SY, Milescu M, Swartz KJ, Kim JL (2005) Solution structure and lipid membrane partitioning of VSTx1, an inhibitor of the KvAP potassium channel. J Biochem 44(16):6015–6023

    Article  CAS  Google Scholar 

  27. Bazari WL, Matsudaira P, Wallek M, Smeal T, Jakes R, Ahmed Y (1988) Villin sequence and peptide map identify six homologous domains. Proc Natl Acad Sci USA 85(14):4986– -4990

    Article  Google Scholar 

  28. Wallace E, Sansom M (2007) Carbon Nanotube/Detergent Interactions via Coarse-Grained Molecular Dynamics. Nano Lett 7(7):1923–1928

    Article  CAS  Google Scholar 

  29. Shih A, Arkhipov A, Freddolino P, Schulten K (2006) Coarse Grained protein-lipid model with application to lipoprotein particles. J Phys Chem B 110(8):3674–3684

    Article  CAS  Google Scholar 

  30. Wagoner JA, Pande VS (2012) Reducing the effect of Metropolization on mixing times in molecular dynamics simulations. J Chem Phys 137:214105

    Article  Google Scholar 

  31. Ramachandran GN, Ramakrishnan C, Sasisekharan V (1963) Stereochemistry of polypeptide chain configurations. J Molec Biol 7:95–99

    Article  CAS  Google Scholar 

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Acknowledgments

The authors would like to thank the financial support from MTM2011-24766 and MTM2010-18318 funded by MICINN (Spain). This work has been possible thanks to the support of the computing infrastructure of the i2BASQUE academic network and the SGI/IZO-SGIker UPV/EHU. TR would like to thank the Spanish Ministry of Education for funding through the fellowship FPU12/05209. This research is supported by the Basque Government through the BERC 2014-2017 program and by the Spanish Ministry of Economy and Competitiveness MINECO: BCAM Severo Ochoa accreditation SEV-2013-0323.

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Authors and Affiliations

  1. Basque Center for Applied Mathematics, E-48009, Bilbao, Spain

    Mario Fernández-Pendás, Bruno Escribano, Tijana Radivojević & Elena Akhmatskaya

  2. IKERBASQUE, Basque Foundation for Science, E-48011, Bilbao, Spain

    Elena Akhmatskaya

Authors
  1. Mario Fernández-Pendás
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  2. Bruno Escribano
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  3. Tijana Radivojević
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  4. Elena Akhmatskaya
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Correspondence to Bruno Escribano.

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This paper belongs to Topical Collection QUITEL 2013

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Fernández-Pendás, M., Escribano, B., Radivojević, T. et al. Constant pressure hybrid Monte Carlo simulations in GROMACS. J Mol Model 20, 2487 (2014). https://doi.org/10.1007/s00894-014-2487-y

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