Docking a model into a local region of density with emplace_local



The emplace_local tool docks the input model within a sphere of density centered on a defined point in the reconstruction, returning the docked model, a local weighted map, and quality of fit statistics.

How emplace_local works

Ideally, half-maps are provided, then the chosen region of density is analysed for local signal and noise (both of which are resolution and direction-dependent) to define a likelihood target for rotation and translation searches, followed by rigid-body refinement.

If half-maps are unavailable, just a full map can be provided and then the likelihood target is defined by assuming that signal-to-noise drops off isotropically to the stated resolution limit.

The quality of fit can be judged by three factors:

1) whether there is a unique solution;
2) the log-likelihood-gain (LLG) score, which should preferably be greater than 60;
3) the map correlation coefficient to the weighted map used for docking.

The basic inputs are:

model file
two unmasked half-map files (preferred) or full-map file
nominal resolution (optional if half-maps provided, but recommended)
specification of center of search region

Note that the search center can be specified explicitly with the sphere_center keyword (the usual approach) or by translating the search model to the desired search region and not providing a sphere_center keyword.

Standard run of emplace_local

    d_min=3.3 model_file=model.pdb sphere_center=100,140,170


List of all available keywords