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Absolute comparison of simulated and experimental protein-folding dynamics

Author

Listed:
  • Christopher D. Snow

    (Stanford University)

  • Houbi Nguyen

    (University of Illinois)

  • Vijay S. Pande

    (Stanford University)

  • Martin Gruebele

    (University of Illinois)

Abstract

Protein folding is difficult to simulate with classical molecular dynamics. Secondary structure motifs such as α-helices and β-hairpins can form in 0.1–10 µs (ref. 1), whereas small proteins have been shown to fold completely in tens of microseconds2. The longest folding simulation to date is a single 1-µs simulation of the villin headpiece3; however, such single runs may miss many features of the folding process as it is a heterogeneous reaction involving an ensemble of transition states4,5. Here, we have used a distributed computing implementation to produce tens of thousands of 5–20-ns trajectories (700 µs) to simulate mutants of the designed mini-protein BBA5. The fast relaxation dynamics these predict were compared with the results of laser temperature-jump experiments. Our computational predictions are in excellent agreement with the experimentally determined mean folding times and equilibrium constants. The rapid folding of BBA5 is due to the swift formation of secondary structure. The convergence of experimentally and computationally accessible timescales will allow the comparison of absolute quantities characterizing in vitro and in silico (computed) protein folding6.

Suggested Citation

  • Christopher D. Snow & Houbi Nguyen & Vijay S. Pande & Martin Gruebele, 2002. "Absolute comparison of simulated and experimental protein-folding dynamics," Nature, Nature, vol. 420(6911), pages 102-106, November.
  • Handle: RePEc:nat:nature:v:420:y:2002:i:6911:d:10.1038_nature01160
    DOI: 10.1038/nature01160
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    Cited by:

    1. Kalyan S. Chakrabarti & Simon Olsson & Supriya Pratihar & Karin Giller & Kerstin Overkamp & Ko On Lee & Vytautas Gapsys & Kyoung-Seok Ryu & Bert L. Groot & Frank Noé & Stefan Becker & Donghan Lee & Th, 2022. "A litmus test for classifying recognition mechanisms of transiently binding proteins," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Isabella Daidone & Hannes Neuweiler & Sören Doose & Markus Sauer & Jeremy C Smith, 2010. "Hydrogen-Bond Driven Loop-Closure Kinetics in Unfolded Polypeptide Chains," PLOS Computational Biology, Public Library of Science, vol. 6(1), pages 1-9, January.
    3. John C Faver & Mark L Benson & Xiao He & Benjamin P Roberts & Bing Wang & Michael S Marshall & C David Sherrill & Kenneth M Merz Jr., 2011. "The Energy Computation Paradox and ab initio Protein Folding," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.

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