Skip to main content

Principal Components Analysis of Biological Systems

  • Chapter
  • First Online:
Computer Simulations in Molecular Biology

Part of the book series: Scientific Computation ((SCIENTCOMP))

  • 273 Accesses

Abstract

This chapter describes the principal components analysis of biological systems in explicit solvent and the stability of the principal components analysis by comparing the quasi-harmonic modes of different simulation trajectories of the same system.

The chapter aims to describe principal components analysis of biological systems in explicit solvent.

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
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

  • D. Aalten, A. Amadei, A. Linssen, V. Eijsink, G. Vriend, H. Berendsen, The essential dynamics of thermolysin-conformation of the hinge-bending motion and comparison of simulations in vacuum and water. Proteins 22, 45–54 (1993)

    Article  Google Scholar 

  • J. Albers, J.M. Deutch, I. Oppenheim, Generalized Langevin equations. J. Chem. Phys. 54(8), 3541–3546 (1971)

    Article  ADS  Google Scholar 

  • A. Amadei, A.B.M. Linssen, H.J.C. Berendsen, Essential dynamics of proteins. Proteins 17, 412 (1993)

    Article  Google Scholar 

  • A. Amadei, B. de Groot, M. Ceruso, M. Paci, A. Di Nola, H. Berendsen, A kinetic model for the internal motions of proteins: diffusion between multiple harmonic wells. Proteins 35(3), 283–292 (1999)

    Article  Google Scholar 

  • U. Balucani, M. Zoppi, Dynamics of the Liquid State (Clarendon, Oxford, 1994)

    Google Scholar 

  • B.B. Brooks, D. Janezic, M. Karplus, Hamonic-analysis of large systems. 1. Methodology. J. Comput. Chem. 16, 1522–1542 (1995)

    Google Scholar 

  • A.E. Garcia, Large-amplitude nonlinear motions in proteins. Phys. Rev. Lett. 68, 2696 (1992)

    Article  ADS  Google Scholar 

  • I.V. Getun, C.K. Brown, J. Tulla-Puche, D. Ohlendorf, C. Woodward, G. Barany, Partially folded Bovine pancreatic trypsin inhibitor analogues attain fully native structures when co-crystallized with S195A rat trypsin. J. Mol. Biol. 375, 812 (2008)

    Article  Google Scholar 

  • N. Go, A theorem on amplitudes of thermal atomic fluctuations in large molecules assuming specific conformations calculated by normal mode analysis. Biophys. Chem. 35, 105–112 (1990)

    Article  Google Scholar 

  • H. Grubmüller, Predicting slow structural transitions in macromolecular systems: conformational flooding. Phys. Rev. E 52, 2893 (1995)

    Article  ADS  Google Scholar 

  • T. Ichiye, M. Karplus, Collective motions in proteins: a covariance analysis of atomic fluctuations in molecular dynamics and normal modes simulations. Proteins 11(3), 205–217 (1991)

    Article  Google Scholar 

  • D. Janezic, B.B. Brooks, Harmonic analysis of large systems: II. Comparison of different protein models. J. Comput. Chem. 16, 1543–1553 (1995)

    Google Scholar 

  • H. Kamberaj, A theoretical model for the collective motion of proteins by means of principal component analysis. Cent. Eur. J. Phys. 9(1), 96–109 (2011)

    Google Scholar 

  • H. Kamberaj, A. van der Vaart, Correlated motions and interactions at the onset of the dna-induced partial unfolding of ets-1. Biophys. J . 96, 1307–1317 (2009)

    Article  Google Scholar 

  • K. Karhunen, Uber Lineare Methoden in der Wahrscheinlichkeitsrechnung. Ann. Acad. Sci. Fenn. Ser. A1(37), 1–79 (1947)

    MathSciNet  MATH  Google Scholar 

  • M. Karplus, J.N. Jushick, Method for estimating the configurational entropy of macromolecules. Macromolecules 14, 325–332 (1981)

    Article  ADS  Google Scholar 

  • A. Kitao, F. Hirata, N. Go, The effect of solvent on the conformation and the collective motions of protein: normal mode analysis and molecular dynamics simulations of melittin in water and in vacuum. Chem. Phys. 158, 447–472 (1991)

    Article  Google Scholar 

  • O.F. Lange, H. Grubmüller, Can principal components yield a dimension reduced description of protein dynamics on long time scales? J. Phys. Chem. B 110, 22842–22852 (2006)

    Article  Google Scholar 

  • O.F. Lange, L.V. Schäfer, H. Grubmüller, Flooding in gromacs: accelerated barrier crossing in molecular dynamics. J. Comput. Chem. 27(14), 1693–1702 (2006)

    Article  Google Scholar 

  • W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery, Numerical Recipes in Fortran 90. The Art of Parallel Scientific Computing, vol. 2, 2nd edn. (Cambridge University Press, New York, 1996)

    Google Scholar 

  • M. Stepanova, Dynamics of essential collective motions in proteins: theory. Phys. Rev. E 76(5), 051918 (2007)

    Article  ADS  MathSciNet  Google Scholar 

  • A. Tournier, J. Smith, Principal components of the protein dynamical transition. Phys. Rev. Lett. 91, 208106 (2003)

    Article  ADS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hiqmet Kamberaj .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kamberaj, H. (2023). Principal Components Analysis of Biological Systems. In: Computer Simulations in Molecular Biology. Scientific Computation. Springer, Cham. https://doi.org/10.1007/978-3-031-34839-6_13

Download citation

Publish with us

Policies and ethics