Abstract Nascent helicity in polypeptides and unfolded proteins is a type of rapid local structure formation that could represent the earliest events in a protein folding reaction. Nascent helicity may also influence the physical properties of intrinsically disordered regions. For this reason, there has been great interest in statistical mechanical models that describe the coil → helix transitions that give rise to nascent helicity. These models, collectively called helix–coil models, have been empirically parameterized using an extensive data set of CD measurements of natural and designed peptides that form various degrees of nascent helicity. Some of these models have been developed to predict the helicity of a given sequence based on sample temperature, pH, and ionic strength. Here, we extend our previous model to add the presence of both stabilizing (TMAO) and destabilizing (urea) osmolytes. We also present additional experimental data on a peptide corresponding in sequence to helix 1 of the N‐terminal domain of repressor. We have used Bayesian inference to build the extended model using our new data along with data from previously published osmolyte studies and have obtained estimates for the linear dependence of the Δ G of the coil → helix transition ( m values). We believe these new parameter estimates will be useful in future helical peptide studies, as will the extended predictive model, which can now predict the effect of osmolytes.
Hughes et al. (Tue,) studied this question.