Physics and Biology of Proteins

Workshop | Monday, June 12, 2017 - Friday, June 30, 2017

Nonnative effects in protein folding and evolutionary switches (minicourse. Part II)

Tuesday, June 27, 2017 - 09:00:00 - 10:00:00

Hue Sun Chan

University of Toronto

I will first discuss the fundamental importance of understanding
nonnative effects as an indispensable aspect in our effort to
decipher biomolecular recognition [1], then I will proceed to present
recent advances in applying atomic and coarse-grained simulation
approaches to gain physical insights into nonnative effects in
protein folding, using primarily examples from my group's effort. These
include (but are not limited to): (i) Bacterial colicin-immunity
proteins Im7 and Im9. These proteins are homologous, but they fold by
different mechanisms. Im7 tends to fold in a three-state manner via
an intermediate but Im9 folding is two-state-like. Our model suggests
that nonnative effects in Im7 folding are caused by a higher local
hydrophobicity concomitant with a lower local native contact density [2].
More recent atomic simulations indicate that frustration is also present
in Im9, and that the reason why it does not impede folding kinetics is
likely because of the peculiar order of helix packing in Im9 folding.
(ii) The GA/GB system. How novel folds of proteins may evolve is addressed
by modeling the folding behaviors of 12 experimentally well-characterized
GA/GB sequences covering a switch from an all-alpha GA fold to an entirely
different four-beta + alpha GB fold. In agreement with experiment, our
implicit-solvent all-atom model exhibits conformational switching upon
a single L45Y substitution [3]. The fold preference shows a gradual
sequence-dependent change in our model, in line with the latent
evolutionary potential concept [4,5]. Our theoretical perspective thus
provide a coherent physical picture for rationalizing and predicting
nonnative effects and conformational switches.

[1] Chen, Song & Chan (2015) Curr Opin Struct Biol 30:32-42
[2] Chen & Chan (2015) PLoS Comput Biol 11(5): e1004260
[3] Sikosek, Krobath & Chan (2016) PLoS Comput Biol 12(6):e1004960
[4] Sikosek, Chan & Bornberg-Bauer (2012) PNAS 109:14888-14893
[5] Sikosek & Chan (2014) J Royal Soc Interface 11:140419