FIRE: predicting the spatial proximity of protein residues from 3D NOESY-HSQC

We address the problem of the prediction of residue spatial proximity in a protein, through the automatic processing of a 3D N-15 NOESY-HSQC. The spat ial distance between residues is estimated from a spectral match value calc ulated using a comparison of the resonances involving the amide hydrogens. The method is shown to provide a good estimation of a large number of resid ue spatial proximities, in the case of two experimental 3D spectra, recorde d on proteins of ct and beta secondary structures. It is tested on simulate d data sets against the protein size, secondary structure and the quality o f the signal. More than 70% of the sequential assignment is correctly predi cted, and the prediction is better for the ct than for the beta secondary s tructure. The medium- and long-range correlations seem equally well predict ed for all the secondary structures. The efficiency of the method is compar ed to a previously proposed spectral correlation approach.