STATISTICS OF SEQUENCE-STRUCTURE THREADING

The past two years have seen the rapid development of new recognition methods for protein structure prediction. These algorithms 'thread' th e sequence of one protein through the known structure of another, look ing for an alignment that corresponds to an energetically favorable mo del structure. Because they are based on energy calculation, rather th an evolutionary distance, these methods extend the possibility of stru cture prediction by comparative modeling to a larger class of new sequ ences, where similarity to known structures is recognizable by no othe r means. The strength of the evidence they offer should be judged by o bjective statistical tests, however, so as to rule out the possibility that favorable scores arise from chance factors such as similarity of length, composition, or the consideration of a large number of altern ative alignments. Calculation of objective p-values by analytical mean s is not yet possible, but it would appear that approximate values may be obtained by simulation, as they are in gapped, global sequence ali gnment. We propose that the results of threading experiments should in clude Z-scores relative to the composition-corrected score distributio n obtained for shuffled and optimally aligned sequences.