EVALUATION OF AN ALGORITHM FOR THE AUTOMATED SEQUENTIAL ASSIGNMENT OFPROTEIN BACKBONE RESONANCES - A DEMONSTRATION OF THE CONNECTIVITY TRACING ASSIGNMENT TOOLS (CONTRAST) SOFTWARE PACKAGE

The peptide sequential assignment algorithm presented here was impleme nted as a macro within the CONnectivity TRacing ASsignment Tools (CONT RAST) computer software package. The algorithm provides a semi- or ful ly automated global means of sequentially assigning the NMR backbone r esonances of proteins. The program's performance is demonstrated here by its analysis of realistic computer-generated data for IIIGlc, a 168 -residue signal-transducing protein of Escherichia coli [Pelton et al. (1991) Biochemistry, 30, 10043-10057]. Missing experimental data (19 resonances) were generated so that a complete assignment set could be tested. The algorithm produces sequential assignments from appropriate peak lists of nD NMR data. It quantities the ambiguity of each assign ment and provides ranked alternatives. A 'best first' approach, in whi ch high-scoring local assignments are made before and in preference to lower scoring assignments, is shown to be superior (in terms of the c urrent set of CONTRAST scoring routines) to approaches such as simulat ed annealing that seek to maximize the combined scores of the individu al assignments. The robustness of the algorithm was tested by evaluati ng the effects of imposed frequency imprecision (scatter), added false signals (noise), missing peaks (incomplete data), and variation in us er-defined tolerances on the performance of the algorithm.