The NOAH/DIAMOD suite uses feedback filtering and self-correcting distance geometry to generate 3D structures from unassigned NOESY spectra. In this study we determined the minimum set of experiments needed to generate a high quality structure bundle. Different combinations of 3D 15N-edited, 13C-edited HSQC-NOESY and 2D homonuclear 1H-1H NOESY spectra of the 77 amino acid protein, myeloid progenitor inhibitory factor-1 (MPIF-1) were used as input for NOAH/DIAMOD calculations. The quality of the assignments of NOESY cross peaks and the accuracy of the automatically generated 3D structures were compared to those obtained with a conventional manual procedure. Combining data from two types of experiments synergistically increased the number of peaks assigned unambiguously in both individual spectra. As a general trend for the accuracy of the structures we observed structural variations in the backbone fold of the final structures of about 2 A for single spectral data, of 1 A to 1.5 A for double spectral data, and of 0.6 A for triple spectral data sets. The quality of the assignments and 3D structures from the optimal data using all three spectra were similar to those obtained from traditional assignment methods with structural variations within the bundle of 0.6 A and 1.3 A for backbone and heavy atoms, respectively. Almost all constraints (97%) of the automatic NOESY cross peak assignments were cross compatible with the structures from the conventional manual assignment procedure, and an even larger proportion (99%) of the manually derived constraints were compatible with the automatically determined 3D structures. The two mean structures determined by both methods differed only by 1.3 A rmsd for the backbone atoms in the well-defined regions of the protein. Thus NOAD/DIAMOD analysis of spectra from labeled proteins provides a reliable method for high throughput analysis of genomic targets.