Solving structures of protein complexes by molecular replacement with<i>Phaser</i>

TLDR

Molecular replacement becomes increasingly difficult as the number of asymmetric‑unit components rises, especially when each contributes little scattering or when many copies or highly variable B factors are present, making automated searches often suboptimal. The study presents two case studies demonstrating optimal use of Phaser in standard automated MR mode and two additional case studies illustrating how to adjust the search strategy for challenging scenarios. Phaser employs maximum‑likelihood MR with a tree‑search pruning strategy, allowing complex asymmetric units to be assembled from individual components, and the paper demonstrates how to apply this approach in both standard and modified search strategies. The implemented method in Phaser successfully solved numerous previously intractable MR problems.

Abstract

Molecular replacement (MR) generally becomes more difficult as the number of components in the asymmetric unit requiring separate MR models (i.e. the dimensionality of the search) increases. When the proportion of the total scattering contributed by each search component is small, the signal in the search for each component in isolation is weak or non-existent. Maximum-likelihood MR functions enable complex asymmetric units to be built up from individual components with a ;tree search with pruning' approach. This method, as implemented in the automated search procedure of the program Phaser, has been very successful in solving many previously intractable MR problems. However, there are a number of cases in which the automated search procedure of Phaser is suboptimal or encounters difficulties. These include cases where there are a large number of copies of the same component in the asymmetric unit or where the components of the asymmetric unit have greatly varying B factors. Two case studies are presented to illustrate how Phaser can be used to best advantage in the standard ;automated MR' mode and two case studies are used to show how to modify the automated search strategy for problematic cases.