AUTOMATED BACKBONE ASSIGNMENT OF LABELED PROTEINS USING THE THRESHOLDACCEPTING ALGORITHM

The sequential assignment of backbone resonances is the first step in the structure determination of proteins by heteronuclear NMR. For larg er proteins, an assignment strategy based on proton side-chain informa tion is no longer suitable for the use in an automated procedure. Our program PASTA (Protein ASsignment by Threshold Accepting) is therefore designed to partially or fully automate the sequential assignment of proteins, based on the analysis of NMR backbone resonances plus C-beta information. In order to overcome the problems caused by peak overlap and missing signals in an automated assignment process, PASTA uses th reshold accepting, a combinatorial optimization strategy, which is sup erior to simulated annealing due to generally faster convergence and b etter solutions. The reliability of this algorithm is shown by reprodu cing the complete sequential backbone assignment of several proteins f rom published NMR data. The robustness of the algorithm against misass igned signals, noise, spectral overlap and missing peaks is shown by r epeating the assignment with reduced sequential information and increa sed chemical shift tolerances. The performance of the program on real data is finally demonstrated with automatically picked peak lists of h uman nonpancreatic synovial phospholipase A(2), a protein with 124 res idues.