Dissecting the structure of a partially folded protein. Circular dichroism and nuclear magnetic resonance studies of peptides from ubiquitin.

The nature and interaction of structural elements in a partially ordered form of ubiquitin, the A-state, which is populated at low pH in 40 to 60% aqueous methanol, have been investigated. Two synthetic peptides have been studied under the same conditions: U(1-21), corresponding to the N-terminal beta-hairpin in the native (N) and A-states of ubiquitin and U(1-35), which includes this hairpin plus an alpha-helix. Circular dichroism studies indicate that, although these peptides are largely unfolded in water, their structural content in 30 and 60% methanol is comparable with the corresponding native secondary structure. Sequence-specific assignments of the 1H n.m.r. spectra of U(1-35) in aqueous methanol and subsequent secondary structure determination confirm the conservation in detail of native-like secondary structure. Corresponding resonances in spectra of U(1-35), U(1-21) and the A-state itself were found to have closely similar chemical shifts, suggesting that the beta-hairpin exists independently in the partially folded protein, with little or no influence from the rest of the molecule. This is confirmed by the virtual absence in nuclear Overhauser enhancement spectroscopy and rotating frame nuclear Overhauser enhancement spectroscopy spectra of nuclear Overhauser enhancement effects between structural elements. c.d. and n.m.r. evidence suggests that structure in the C-terminal half of the molecule in the A-state is largely non-native. Thus, although methanol is necessary to assure its stability in the absence of wider native interactions, the structure of the beta-hairpin, including the register of its hydrogen bonding, appears to be determined entirely by its own sequence. This intrinsic structural preference in the first part of the ubiquitin sequence is much stronger than in the C-terminal half, a conclusion reflected in the results from a variety of secondary structure prediction algorithms.