Biology – Quantitative Biology – Biomolecules
Scientific paper
2008-08-16
J Mol Biol. 2009 Oct 9;392(5):1303-14.
Biology
Quantitative Biology
Biomolecules
11 pages, 4 figures
Scientific paper
10.1016/j.jmb.2009.06.058
Models of protein energetics which neglect interactions between amino acids that are not adjacent in the native state, such as the Go model, encode or underlie many influential ideas on protein folding. Implicit in this simplification is a crucial assumption that has never been critically evaluated in a broad context: Detailed mechanisms of protein folding are not biased by non-native contacts, typically imagined as a consequence of sequence design and/or topology. Here we present, using computer simulations of a well-studied lattice heteropolymer model, the first systematic test of this oft-assumed correspondence over the statistically significant range of hundreds of thousands of amino acid sequences, and a concomitantly diverse set of folding pathways. Enabled by a novel means of fingerprinting folding trajectories, our study reveals a profound insensitivity of the order in which native contacts accumulate to the omission of non-native interactions. Contrary to conventional thinking, this robustness does not arise from topological restrictions and does not depend on folding rate. We find instead that the crucial factor in discriminating among topological pathways is the heterogeneity of native contact energies. Our results challenge conventional thinking on the relationship between sequence design and free energy landscapes for protein folding, and help justify the widespread use of Go-like models to scrutinize detailed folding mechanisms of real proteins.
Garrahan Juan P.
Geissler Phillip L.
Gin Brian C.
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