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The Energy Computation Paradox and ab initio Protein Folding
Author(s) -
John C. Faver,
Mark L. Benson,
Xiao He,
Benjamin P. Roberts,
Bing Wang,
Michael S. Marshall,
C. David Sherrill,
Kenneth M. Merz
Publication year - 2011
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0018868
Subject(s) - bottleneck , maxima and minima , computation , protein folding , ab initio , statistical physics , protein structure prediction , energy (signal processing) , folding (dsp implementation) , energy landscape , computer science , physics , protein structure , algorithm , mathematics , quantum mechanics , nuclear magnetic resonance , mathematical analysis , embedded system , electrical engineering , thermodynamics , engineering
The routine prediction of three-dimensional protein structure from sequence remains a challenge in computational biochemistry. It has been intuited that calculated energies from physics-based scoring functions are able to distinguish native from nonnative folds based on previous performance with small proteins and that conformational sampling is the fundamental bottleneck to successful folding. We demonstrate that as protein size increases, errors in the computed energies become a significant problem. We show, by using error probability density functions, that physics-based scores contain significant systematic and random errors relative to accurate reference energies. These errors propagate throughout an entire protein and distort its energy landscape to such an extent that modern scoring functions should have little chance of success in finding the free energy minima of large proteins. Nonetheless, by understanding errors in physics-based score functions, they can be reduced in a post-hoc manner, improving accuracy in energy computation and fold discrimination.

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