Abstract
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.
Highlights
Molecular replacement (MR) remains the most popular method to solve the phase problem in macromolecular crystallography since it is quick, inexpensive and often highly automated (Evans & McCoy, 2008; Long et al, 2008; Scapin, 2013)
In addition to using the Phaser rotation search, we have explored the use of ensemble search models in SIMBAD
In previous work describing SIMBAD (Simpkin et al, 2018), a test set of 25 structures that had recently been deposited was compiled to assess the ability of SIMBAD to solve novel structures
Summary
Molecular replacement (MR) remains the most popular method to solve the phase problem in macromolecular crystallography since it is quick, inexpensive and often highly automated (Evans & McCoy, 2008; Long et al, 2008; Scapin, 2013). As evolutionarily related molecules are likely to have similar protein sequences, sequence similarity often provides a quick and easy route to identify suitable homologues for MR. Search models selected by sequence similarity can give poor results for a number of reasons. These include cases where only distant, low-sequence-identity homologues can be identified, which can often be too structurally divergent from the target. Even where high-sequence-identity homologues are available, they may have crystallized in different conformational states and prove too structurally distinct to succeed. Another possibility is that a contaminant protein has crystallized in place of the target protein
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