Automated detection of problem restraints in NMR data sets using the FINGAR genetic algorithm method.

The recently described FINGAR genetic algorithm method for NMR refinement [D.A. Pearlman (1996) J. Biomol. NMR, 8, 67-76] has been extended so that it can be used to detect problem restraints in an NMR-derived set of data. A problem restraint is defined as a restraint in a generally well-behaved set where the associated target value is in error, due to inaccuracies in the data, misassignment, etc. The method described here, FINGAR.RWF, locates problem restraints by finding those restraints that, if removed from the data set, result in a disproportionate improvement in the scoring function. The method is applied to several test cases of simulated data, as well as to real data for the FK506 macrocycle, with excellent results.