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Polymer principles and protein folding.

K A Dill1

  • 1University of California, San Francisco 94118, USA. dill@maxwell.ucsf.edu

Protein Science : a Publication of the Protein Society
|July 1, 1999
PubMed
Summary
This summary is machine-generated.

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Statistical mechanics and polymer theory explain protein folding by viewing it as a guided process, not a random search. This resolves classic paradoxes regarding protein origin and folding time.

Area of Science:

  • Biophysics
  • Computational Biology
  • Statistical Mechanics

Background:

  • Protein folding is crucial for biological function.
  • Classic paradoxes (Blind Watchmaker's, Levinthal's) question protein origin and folding efficiency.
  • Traditional views emphasize random search through vast conformational spaces.

Purpose of the Study:

  • Survey the role of statistical mechanics and polymer theory in protein folding.
  • Reframe protein folding as a guided process.
  • Resolve classic paradoxes using a polymer perspective.

Main Methods:

  • Application of polymer theory to protein folding.
  • Analysis of protein folding as a "solvation code" rather than local propensities.
  • Conceptualization using energy and fitness landscapes.

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Main Results:

  • The polymer perspective resolves the Blind Watchmaker's and Levinthal's Paradoxes.
  • Protein folding is presented as a guided search (like a ball rolling down a funnel), not a random one.
  • Vastness of search space is largely irrelevant to folding time and success.

Conclusions:

  • Statistical mechanics and polymer theory provide a powerful framework for understanding protein folding.
  • Energy landscapes bridge microscopic and macroscopic scales in protein dynamics.
  • This approach facilitates the development of novel computational search strategies for protein folding.