Predicting the redox state and secondary structure of cysteine residues in proteins using NMR chemical shifts

We report 2D cluster analyses of H-1(alpha), H-1(N), C-13(alpha), and C-13' versus C-13(beta) NMR chemical shifts (CSs) that can be used to predict the redox state and secondary structure of cysteine residues in proteins. A database of cysteine H-1(alpha), H-1(beta 2), H-1(beta 3), H-1(N), C-13(alpha), C-13(beta), C-13', and N-15(H) CSs as a function of secondary structure and redox state was constructed from BioMagResBank entries. One-dimensional. statistical analysis showed that cysteine H-1(alpha), H-1(N), C-13(alpha), C-13', and N-15(H) CSs reflected the secondary structure, and that cysteine C-beta CS is extremely sensitive to the redox state. In contrast, cysteine H-1(beta) CS was not correlated with its redox state or secondary structure. Two-dimensional cluster analysis revealed that 2D C-alpha/C-beta, C'/C-beta, H-N/C-beta, and H-alpha/C-beta clusters were helpful in distinguishing both the redox state and secondary structure of cysteine residues. Based on these results, we derived rules using a score matrix to predict the redox state and secondary structure of cysteines using their CSs. The score matrix predicts the redox state and secondary structure of cysteine residues in proteins with similar to 90% accuracy. This suggests that the redox state and secondary structure of cysteine residues in peptides and proteins can be obtained from their CSs without recourse to nuclear Overhauser effect measurements.