Skip to main content

Large-Scale Molecular Dynamics Simulations of Cellular Compartments

  • Protocol
  • First Online:
Structure and Function of Membrane Proteins

Abstract

Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Alberts B (2010) Cell biology: the endless frontier. Mol Biol Cell 21(22):3785

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Singharoy A, Maffeo C, Delgado-Magnero K et al (2019) Atoms to phenotypes: molecular design principles of cellular energy metabolism. Cell 179(5):1098–1111.e23

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Goh BC, Hadden JA, Bernardi RC et al (2016) Computational methodologies for real-space structural refinement of large macromolecular complexes. Annu Rev Biophys 45:253–278

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Voth GA (2017) A multiscale description of biomolecular active matter: the chemistry underlying many life processes. Acc Chem Res 50(3):594–598

    Article  CAS  PubMed  Google Scholar 

  5. Davtyan A, Simunovic M, Voth GA (2016) Multiscale simulations of protein-facilitated membrane remodeling. J Struct Biol 196(1):57–63

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Van Meel JA, Arnold A, Frenkel D et al (2008) Harvesting graphics power for md simulations. Mol Simul 34(3):259–266

    Article  CAS  Google Scholar 

  7. Ananthraj V, De K, Jha S et al (2018) Towards exascale computing for high energy physics: The atlas experience at ornl. In: 2018 IEEE 14th international conference on e-science (e-science), pp 341–342

    Chapter  Google Scholar 

  8. Kilburg D, Gallicchio E (2016) Recent advances in computational models for the study of protein–peptide interactions. Adv Protein Chem Struct Biol 105:27–57

    Article  CAS  PubMed  Google Scholar 

  9. Ourmazd A (2019) Cryo-em, xfels and the structure conundrum in structural biology. Nat Methods 16(10):941–944

    Article  CAS  PubMed  Google Scholar 

  10. Marrink SJ, Corradi V, Souza PC et al (2019) Computational modeling of realistic cell membranes. Chem Rev 119(9):6184–6226

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Feig M, Harada R, Mori T et al (2015) Complete atomistic model of a bacterial cytoplasm for integrating physics, biochemistry, and systems biology. J Mol Graph Model 58:1–9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Yu I, Mori T, Ando T et al (2016) Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm. elife 5:e19274

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Perilla JR, Schulten K (2017) Physical properties of the hiv-1 capsid from all-atom molecular dynamics simulations. Nat Commun 8:15959

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wickles S, Singharoy A, Andreani J et al (2014) A structural model of the active ribosome-bound membrane protein insertase yidc. elife 3:e03035

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Trabuco LG, Villa E, Mitra K et al (2008) Flexible fitting of atomic structures into electron microscopy maps using molecular dynamics. Structure 16(5):673–683

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Schweitzer A, Aufderheide A, al Rudack T (2016) Structure of the human 26s proteasome at a resolution of 3.9 Å. Proc Natl Acad Sci U S A 113(28):7816–7821

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Durrant JD, Bush RM, Amaro RE (2016) Microsecond molecular dynamics simulations of influenza neuraminidase suggest a mechanism for the increased virulence of stalk-deletion mutants. J Phys Chem B 120(33):8590–8599

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Mannige RV, Brooks CL III (2010) Periodic table of virus capsids: implications for natural selection and design. PLoS One 5(3):e9423

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Blood PD, Voth GA (2006) Direct observation of bin/amphiphysin/rvs (bar) domaininduced membrane curvature by means of molecular dynamics simulations. Proc Natl Acad Sci U S A 103(41):15068–15072

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Arkhipov A, Yin Y, Schulten K (2008) Four-scale description of membrane sculpting by bar domains. Biophys J 95(6):2806–2821

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Jung J, Nishima W, Daniels M et al (2019) Scaling molecular dynamics beyond 100,000 processor cores for large-scale biophysical simulations. J Comput Chem 40(21):1919–1930

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Renaud J-P, Chari A, Ciferri C et al (2018) Cryo-EM in drug discovery: achievements, limitations and prospects. Nat Rev Drug Discov 17(7):471–492

    Article  CAS  PubMed  Google Scholar 

  23. Camargo C (2018) Physics makes rules, evolution rolls the dice. Science 361(6399):236–236

    Article  CAS  Google Scholar 

  24. Şener MK, Olsen JD, Hunter CN et al (2007) Atomic-level structural and functional model of a bacterial photosynthetic membrane vesicle. Proc Natl Acad Sci 104(40):15723–15728

    Article  PubMed  PubMed Central  Google Scholar 

  25. Blankenship RE (2014) Molecular mechanisms of photosynthesis. John Wiley & Sons, Hoboken, New Jersey

    Google Scholar 

  26. Vant, J. W. (2019). Chromatophore_large_system_simulation. https://github.com/jvant/Chromatophore_Large_System_Simulation GitHub

  27. Phillips JC, Braun R, Wang W et al (2005) Scalable molecular dynamics with NAMD. J Comput Chem 26(16):1781–1802

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Comer J, Aksimentiev A (2016) DNA sequence-dependent ionic currents in ultra-small solidstate nanopores. Nanoscale 8(18):9600–9613

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Humphrey W, Dalke A, Schulten K (1996) VMD: Visual molecular dynamics. J Mol Graph 14(1):33–38

    Article  CAS  PubMed  Google Scholar 

  30. Singharoy A, Cheluvaraja S, Ortoleva P (2011) Order parameters for macromolecules: application to multiscale simulation. J Chem Phys 134(4):044104

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Acun B, Hardy DJ, Kale LV et al (2018) Scalable molecular dynamics with NAMD on the summit system. IBM J Res Dev 62(6):1–9

    Article  CAS  PubMed  Google Scholar 

  32. Chandler DE, Strümpfer J, Sener M et al (2014) Light harvesting by lamellar chromatophores in rhodospirillum photometricum. Biophys J 106(11):2503–2510

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Şener M, Strümpfer J, Timney JA et al (2010) Photosynthetic vesicle architecture and constraints on efficient energy and harvesting. Biophys J 99(1):67–75

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Cartron ML, Olsen JD, Sener M et al (2014) Integration of energy and electron transfer processes in the photosynthetic membrane of rhodobacter sphaeroides. Biochim Biophys Acta 1837(10):1769–1780

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Kumar S, Cartron ML, Mullin N et al (2016) Direct imaging of protein organization in an intact bacterial organelle using high-resolution atomic force microscopy. ACS Nano 11(1):126–133

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Scheuring S, Nevo R, Liu L-N et al (2014) The architecture of rhodobacter sphaeroides chromatophores. Biochim Biophys Acta 1837(8):1263–1270

    Article  CAS  PubMed  Google Scholar 

  37. Russel D, Lasker K, Webb B et al (2012) Putting the pieces together: integrative modeling platform software for structure determination of macromolecular assemblies. PLoS Biol 10(1):e1001244

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Ho PT, Montiel-Garcia DJ, Wong JJ et al (2018) VIPERdb: a tool for virus research. Annu Rev Virol 5(1):477–488

    Article  CAS  PubMed  Google Scholar 

  39. Durrant JD, Amaro RE (2014) Lipidwrapper: an algorithm for generating large-scale membrane models of arbitrary geometry. PLoS Comput Biol 10(7):e1003720

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Wells DB, Abramkina V, Aksimentiev A (2007) Exploring transmembrane transport through α-hemolysin with grid-steered molecular dynamics. J Chem Phys 127(12):09B619

    Article  CAS  Google Scholar 

  41. Balasubramanian V, Turilli M, Hu W et al (2018) Harnessing the power of many: extensible toolkit for scalable ensemble applications. In: In 2018 IEEE international parallel and distributed processing symposium (ipdps). IEEE, New York, pp 536–545

    Chapter  Google Scholar 

  42. Turilli M, Santcroos M, Jha S (2018) A comprehensive perspective on pilot-job systems. ACM Comput Surv 51(2):43:1–43:32

    Google Scholar 

  43. Goodale T, Jha S, Kaiser H et al (2006) SAGA: a simple API for grid applications, high-level application programming on the grid. Comput Methods Sci Technol 12(1):7–20

    Article  Google Scholar 

  44. Merzky A, Weidner O, Jha S (2015) SAGA: a standardized access layer to heterogeneous distributed computing infrastructure. Software-X 1-2:3–8

    Google Scholar 

  45. MDFF Integration with EnTK on OLCF Summit. (2019). https://github.com/radical-collaboration/MDFF-Error.GitHub

  46. Chandler DE, Hsin J, Harrison CB et al (2008) Intrinsic curvature properties of photosynthetic proteins in chromatophores. Biophys J 95(6):2822–2836

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Singharoy A, Barragan AM, Thangapandian S et al (2016b) Binding site recognition and docking dynamics of a single electron transport protein: cytochrome c 2. J Am Chem Soc 138(37):12077–12089

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Singharoy A, Teo I, McGreevy R et al (2016a) Molecular dynamics-based model refinement and validation for sub-5 angstrom cryo-electron microscopy maps. eLife 5:e16105

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Acknowledgments

The authors acknowledge start-up funds from the School of Molecular Sciences and Center for Applied Structure Discovery at Arizona State University, and the resources of the OLCF at the Oak Ridge National Laboratory, which is supported by the Office of Science at DOE under Contract No. DEAC05-00OR22725, made available via the INCITE program. We also acknowledge NAMD and VMD developments supported by NIH (P41GM104601) and R01GM098243-02 for supporting our study of membrane proteins.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Chitrak Gupta , Daipayan Sarkar or Abhishek Singharoy .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Wilson, E. et al. (2021). Large-Scale Molecular Dynamics Simulations of Cellular Compartments. In: Schmidt-Krey, I., Gumbart, J.C. (eds) Structure and Function of Membrane Proteins. Methods in Molecular Biology, vol 2302. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1394-8_18

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-1394-8_18

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1393-1

  • Online ISBN: 978-1-0716-1394-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics