Changes in solvent environment greatly affect macromolecular structure and stability. To investigate the role of excluded volume in solvation, scaled-particle theory is often used to calculate delta G(tr)(ev), the excluded-volume portion of the solute transfer free energy, delta G(tr). The inputs to SPT are the solvent radii and molarities. Real molecules are not spheres. Hence, molecular radii are not uniquely defined and vary for any given species. Since delta G(tr)(ev) is extremely sensitive to solvent radii, uncertainty in these radii causes a large uncertainty in delta G(tr)(ev)-several kcal/mol for amino acid solutes transferring from water to aqueous mixtures. This uncertainty is larger than the experimental delta G(tr) values. Also, delta G(tr)(ev) can be either positive or negative. Adding neutral crowding molecules may not necessarily reduce solubility. Lastly, delta G(tr)(ev) is very sensitive to solvent density, rho. A few percent error in rho may even cause qualitative deviations in delta G(tr)(ev). For example, if rho is calculated by assuming the hard-sphere pressure to be constant, then delta G(tr)(ev) values and uncertainties are now only tenths of a kcal/mol and are positive. Because delta G(tr)(ev) values calculated by scaled-particle theory are strongly sensitive to solvent radii and densities, determining the excluded-volume contribution to transfer free energies using SPT may be problematic.

Candida albicans strains tolerate aneuploidy, historically detected as karyotype alterations by pulsed-field gel electrophoresis and more recently revealed by array comparative genome hybridization, which provides a comprehensive and detailed description of gene copy number. Here, we first retrospectively analyzed 411 expression array experiments to predict the frequency of aneuploidy in different strains. As expected, significant levels of aneuploidy were seen in strains exposed to stress conditions, including UV light and/or sorbose treatment, as well as in strains that are resistant to antifungal drugs. More surprisingly, strains that underwent transformation with DNA displayed the highest frequency of chromosome copy number changes, with strains that were initially aneuploid exhibiting ϳ3-fold more copy number changes than strains that were initially diploid. We then prospectively analyzed the effect of lithium acetate (LiOAc) transformation protocols on the stability of trisomic chromosomes. Consistent with the retrospective analysis, the proportion of karyotype changes was highly elevated in strains carrying aneuploid chromosomes. We then tested the hypothesis that stresses conferred by heat and/or LiOAc exposure promote chromosome number changes during DNA transformation procedures. Indeed, a short pulse of very high temperature caused frequent gains and losses of multiple chromosomes or chromosome segments. Furthermore, milder heat exposure over longer periods caused increased levels of loss of heterozygosity. Nonetheless, aneuploid chromosomes were also unstable when strains were transformed by electroporation, which does not include a heat shock step. Thus, aneuploid strains are particularly prone to undergo changes in chromosome number during the stresses of DNA transformation protocols.

We study the fluctuations of native proteins by exact enumeration using the HP lattice model. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This prediction is consistent with the observation by Tilton et al. [R. F. Tilton, Jr., J. C. Dewan, and G. A. Petsko, Biochemistry 31, 2469 (1992)], that the thermal motions of ribonuclease A increase sharply above about 200 K. We also explore protein "flexibility" as defined by Debye-Waller-like factors and solvent accessibilities of core residues to hydrogen exchange. We find that proteins having greater stability tend to have fewer large fluctuations, and hence lower flexibilities. If flexibility is necessary for enzyme catalysis, this could explain why proteins from thermophilic organisms, which are exceptionally stable, may be catalytically inactive at normal temperatures.

Biological macromolecules are often studied in mixed solvents. To understand cosolvent-macromolecule interactions, the preferential interaction coefficient, Gamma(3), may help determine surface solvent compositions. Gamma(3) measures the amounts of water, B(1), and cosolvent, B(3), within the "local domain," the (possibly far-reaching) region surrounding the macromolecule where the solvent is non-bulk-like. The local domain's boundary is, however, vague and it is unclear which molecules are counted in B(i). It is useful to explore a simple model system to make B(i) more concrete and to understand which aspects of the surface solvent distribution, rho(x), are sampled by Gamma(3). We performed computer simulations on a two-dimensional (2D) system consisting of a hard-wall solute (the macromolecule) in a mixed solvent (hard disks of different radii). We simultaneously calculated Gamma(3) and rho(x). We found that 1) in practice, the local domain's boundary is demarked by the outer limit of the first cosolvent (not water) layer; B(i) mainly counts the solvent near the macromolecule; 2) assuming B(1) to count only the waters within the first water layer is a poor approximation; 3) when determining B(1) and B(3), water and cosolvent molecules must be counted from the same region of space. We speculate that these 2D results may serve as a first-order approximation for the dominant contributions to Gamma(3) even in three dimensions, so long as the cosolvent is not strongly excluded from the macromolecular surface and there is no significant long-ranged solvent structure.

ABSTRACT:Proteins undergo fluctuations under native conditions. Many lines of evidence are usually interpreted as implying that fluctuations are small excursions away from the native structure. By definition, fluctuations from the native conformation are small increases in free energy. But if protein folding energy landscapes are bumpy, such fluctuations could involve highly nonnative but compact ''misfolded'' structures, even while the excursions in energy are small. Using a model in which we can rigorously study fluctuations and rugged energy landscapes, we ask whether current experimental measures of structure, such as X-ray crystallographic Patterson maps and Debye᎐Waller Ž . Ž . factors or nuclear magnetic resonance NMR nuclear Overhauser effect NOE spectra, could detect bumpy landscapes. We find that even a substantial population of highly nonnative transients will generally be masked by the heavy averaging implicit in current experiments. This means that, in contrast to current interpretations, very nonnative or Misfold Fluctuations of native proteins may exist but are escaping experimental detection. A positive implication is that structure determination is robust to the presence of much conformational noise.