Skip to main content

Computational Molecular Modeling Techniques of Biomacromolecular Systems

  • Chapter
  • First Online:
Plant Structural Biology: Hormonal Regulations
  • 1064 Accesses

Abstract

Computational simulations are used to study the structural and dynamics properties of biomoleculer systems at atomistic resolution. Morover, the simuations also allow to access the energetics of studied systems that can be applied in free energy calculations. Free energy determines the thermodynamic stability and solubility of biomoleclacues in given solution, their affinities towards another biomolecules and their populations in available conformational states. Traditional molecular dynamics simulations of biomacromolecules in explicit water solvent technique are currently restricted to the microseconds time scale but this limitation can be overcome by variety of enhanced sampling computational simulations.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
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

  • Abrams C, Bussi G (2014) Enhanced sampling in molecular dynamics using metadynamics, replica-exchange, and temperature-acceleration. Entropy 16:163–199

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  • Barducci A, Bonomi M, Parrinello M (2001) Metadynamics. WILEY Int Rev Comput Sci 1:826–843

    Google Scholar 

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

    Article  CAS  Google Scholar 

  • Burkert U, Allinger NL (1982) Molecular mechanics. In: ACS monograph, vol 177. American Chemical Society, Washington, DC

    Google Scholar 

  • Bussi G, Gervasio FL, Laio A, Parrinello M (2006) Free-energy landscape for beta hairpin folding from combined parallel tempering and metadynamics. J Am Chem Soc 128:13435–13441

    Article  CAS  PubMed  Google Scholar 

  • Dauber-Osguthorpe P, Robert VA, Osguthorpe DJ, Hagler AT (1988) Structure and energetics of ligand-binding to proteins - Escherichia-coli dihydrofolate reductase trimethoprim, a drug-receptor system. Protein Struct Funct Genet 4:31–47

    Article  CAS  Google Scholar 

  • de Ruiter A, Oostenbrink C (2013) Protein–ligand binding from distancefield distances and hamiltonian replica exchange simulations. J Chem Theory Comput 9:883–892

    Article  CAS  PubMed  Google Scholar 

  • Frenkel D, Smit B (2002) Understanding molecular simulation: from algorithms to applications. Academic Press, Boston

    Google Scholar 

  • Hansen JP, McDonald IR (1986) Theory of simple liquids, 2nd edn. Academic Press, London

    Google Scholar 

  • Hermans J, Berendsen HJC, van Gunsteren WF, Postma JPM (1984) A consistent empirical potential for water-protein interactions. Biopolymers 23:1513–1518

    Article  CAS  Google Scholar 

  • Hess B, Bekker H, Berendsen HJC, Fraaije JGEM (1997) LINCS: a linear constraint solver for molecular simulations. J Comput Chem 18:1463–1472

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  • Hritz J, Oostenbrink C (2007) Optimization of replica exchange molecular dynamics by fast mimicking. J Chem Phys 127:204104

    Article  CAS  PubMed  Google Scholar 

  • Hritz J, Oostenbrink C (2008) Hamiltonian replica exchange molecular dynamics using soft-core interactions. J Chem Phys 128:144121

    Article  CAS  PubMed  Google Scholar 

  • Huber T, Torda AE, van Gunsteren WF (1994) Local elevation: a method for improving the searching properties of molecular dynamics simulation. J Comput Aided Mol Des 8:695–708

    Article  CAS  PubMed  Google Scholar 

  • Kaestner J (2011) Umbrella sampling. WILEY Int Rev Comput Sci 1:932–942

    CAS  Google Scholar 

  • Kaminski G, Friesner RA, Tirado-Rives J, Jorgensen WL (2001) Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J Phys Chem B 105:6474–6487

    Article  CAS  Google Scholar 

  • Kirkpatrick C, Gelatt D Jr, Vecchi MP (1983) Optimalization by simulated annealing. Science 220:671–680

    Article  CAS  Google Scholar 

  • Kumar S, Rosenberg JM, Bouzida D, Swendsen RH, Kollman PA (1992) The weighted histogram analysis method for free-energy calculations on biomolecules. I. The method. J Comput Chem 13:1011–1021

    Article  CAS  Google Scholar 

  • Laio A, Parrinello M (2002) Escaping free energy minima. Proc Natl Acad Sci U S A 99:12562–12566

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lautz J, Kessler H, Kaptein R, van Gunsteren WF (1987) Molecular dynamics simulations of cyclosporin A: the crystal structure and dynamic modelling of a structure in Apolar solution based on NMR data. J Comput Aided Mol Des 1:219–241

    Article  CAS  PubMed  Google Scholar 

  • Lavery R, Rivail J-L (1991) In: Smith J (ed) American Institute of Physics (A.I.P.) conference proceedings 1991, vol 239. New York, pp 131–146

    Google Scholar 

  • MacKerell AD Jr, Bashford D, Bellott M, Dunbrack RL Jr, Evanseck JD, Field MJ, Fischer S, Gao J, Guo H, Ha S, Joseph-McCarthy D, Kuchnir L, Kuczera K, Lau FTK, Mattos C, Michnick S, Ngo T, Nguyen DT, Prodhom B, Reiher WE III, Roux B, Schlenkrich M, Smith JC, Stote R, Straub J, Watanabe M, Wiorkiewicz-Kuczera J, Yin D, Karplus M (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. J Phys Chem B 102:3586–3616

    Article  CAS  PubMed  Google Scholar 

  • McDonald IR, Singer K (1967) Machine calculation of thermodynamic properties of a simple fluid at supercritical temperatures. J Chem Phys 47:4766–4772

    Article  CAS  Google Scholar 

  • McDonald IR, Singer K (1969) Examination of the adequacy of the 12–6 potential for liquid argon by means of Monte Carlo calculations. J Chem Phys 50:2308–2315

    Article  CAS  Google Scholar 

  • Meli M, Colombo G (2013) A Hamiltonian replica exchange molecular dynamics (MD) method for the study of folding, based on the analysis of the stabilization determinants of proteins. Int J Mol Sci 14:12157–12169

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  Google Scholar 

  • Oostenbrink C, de Ruiter A, Hritz J, Vermeulen NPE (2012) Malleability and versatility of Cytochrome P450 active sites studied by molecular simulations. Curr Drug Metab 13:190–196

    Article  CAS  PubMed  Google Scholar 

  • Piana S, Laio A (2007) A bias-exchange approach to protein folding. J Phys Chem B 111:4553–4559

    Article  CAS  PubMed  Google Scholar 

  • Ryckaert J-P, Ciccotti G, Berendsen HJC (1977) Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J Comput Phys 23:327–341

    Article  CAS  Google Scholar 

  • Spiwok V, Sucur Z, Hosek P (2015) Enhanced sampling techniques in biomolecular simulations. Biotechnol Adv 33:1130–1140

    Article  CAS  PubMed  Google Scholar 

  • Sugita Y, Okamoto Y (1999) Replica-exchange molecular dynamics method for protein folding. Chem Phys Lett 314:141–151

    Article  CAS  Google Scholar 

  • Swendsen RH, Wang JS (1986) Replica Monte Carlo simulation of spin glasses. Phys Rev Lett 57:2607–2609

    Article  CAS  PubMed  Google Scholar 

  • Torrie GM, Valleau JP (1974) Monte Carlo free energy estimates using non-Boltzmann sampling: application to the sub-critical Lennard-Jones fluid. Chem Phys Lett 28:578–581

    Article  CAS  Google Scholar 

  • Torrie GM, Valleau JP (1977) Non-physical sampling distributions in Monte Carlo free-energy estimation: umbrella sampling. J Comput Phys 23:187–199

    Article  Google Scholar 

  • van Gunsteren WF, Berendsen HJC (1984) Computer simulation as a tool for tracing the comformational differences between proteins in solution and in the crystalline state. J Mol Biol 176:559–564

    Article  PubMed  Google Scholar 

  • van Gunsteren WF, Berendsen HJC (1987) Gromos-87 manual. Biomos BV, Groningen

    Google Scholar 

  • van Gunsteren WF (1991) Computer simulation of biomolecular systems: overview of timesaving techniques. In: Advances in biomolecular simulations. American Institute of Physics (A.I.P.), New York

    Google Scholar 

  • Weiner SJ, Kollman PA, Case DA, Singh UC, Ghio C, Alagona G, Profeta S Jr, Weiner P (1984) A new force field for molecular mechanical simulation of nucleic acids and proteins. J Am Chem Soc 106:765–784

    Article  CAS  Google Scholar 

  • Weiner SJ, Kollman PA, Nguyen DT et al (1986) An all atom force-field for simulations of proteins and nucleic-acids. J Comput Chem 7:230–252

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The financial contribution made by the Ministry of Education, Youths and Sports of the Czech Republic within special support paid from the National Programme for Sustainability II funds, project CEITEC 2020 (LQ1601), is gratefully acknowledged.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jozef Hritz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Hritz, J., Mladek, A. (2018). Computational Molecular Modeling Techniques of Biomacromolecular Systems. In: Hejátko, J., Hakoshima, T. (eds) Plant Structural Biology: Hormonal Regulations. Springer, Cham. https://doi.org/10.1007/978-3-319-91352-0_15

Download citation

Publish with us

Policies and ethics