Using Phaser and ensembles to improve the performance of SIMBAD.

The conventional approach to search-model identification in molecular replacement (MR) is to screen a database of known structures using the target sequence. However, this strategy is not always effective, for example when the relationship between sequence and structural similarity fails or when the crystal contents are not those expected. An alternative approach is to identify suitable search models directly from the experimental data. SIMBAD is a sequence-independent MR pipeline that uses either a crystal lattice search or MR functions to directly locate suitable search models from databases. The previous version of SIMBAD used the fast AMoRe rotation-function search. Here, a new version of SIMBAD which makes use of Phaser and its likelihood scoring to improve the sensitivity of the pipeline is presented. It is shown that the additional compute time potentially required by the more sophisticated scoring is counterbalanced by the greater sensitivity, allowing more cases to trigger early-termination criteria, rather than running to completion. Using Phaser solved 17 out of 25 test cases in comparison to the ten solved with AMoRe, and it is shown that use of ensemble search models produces additional performance benefits.