Automatic multiple-zone rigid-body refinement with a large convergence radius

Abstract

Rigid-body refinement is the constrained coordinate refinement of one or more groups of atoms that each move (rotate and translate) as a single body. The goal of this work was to establish an automatic procedure for rigid-body refinement which implements a practical compromise between runtime requirements and convergence radius. This has been achieved by analysis of a large number of trial refinements for 12 classes of random rigid-body displacements (that differ in magnitude of introduced errors), using both least-squares and maximum-likelihood target functions. The results of these tests led to a multiple-zone protocol. The final parameterization of this protocol was optimized empirically on the basis of a second large set of test refinements. This multiple-zone protocol is implemented as part of the phenix.refine program.

Figure 1

Example of a success rate plot. The horizontal axis designates the number of refinement macro cycles and the vertical axis designates the success rate in percent (see §2.5). The solid line is the plot using a 0.25 Å r.m.s.d. threshold as the criterion for ‘success’, the dashed line with shorter segments is the plot using a 0.5 Å threshold, and the dashed line with the longer segments is the plot using a 1.0 Å threshold. The example plot was obtained for rnase-p with a fixed 6.0 Å high-resolution cutoff for the data, a random translational displacement magnitude of 2.0 Å and a random rotational displacement magnitude of 5°.

Figure 2

Success rate plots using the LS target function. The high-resolution values are in ångströms. The four-by-four grid for each high-resolution cutoff is arranged by rotational displacement magnitude in the horizontal direction from left to right (0, 5, 10, 15°), and translational displacement magnitude in the vertical direction downwards (0, 2, 4, 6 Å).

Figure 3

Success rate plots using the ML target function. See the caption of Fig. 2 ▶ for a guide to the plots.