Section 25.2.5.2.3. Density modification via averaging of multiple refinements

Slightly varying the protocol described for generating models from maps results in a set of slightly different free-atom models. Each model is then submitted to ARP. In protein crystallography, there are generally insufficient data for convergence of free-atom refinement to a global minimum and different starting models result in final models with small differences, i.e. containing different errors. Averaging of these models can be utilized to minimize the overall error. The procedure in effect imposes a random noise, small enough to be eliminated during the subsequent averaging, but large enough to overcome at least some of the systematic errors.

Structure factors are calculated for all the refined models and a vector average of the calculated structure factors is derived. The phase of the vector average is more accurate than that from any of the individual models. A weight, W_wARP, is assigned to each structure factor on the basis of the variance of the two-dimensional distribution of the individual structure factors around the mean. The mean value of W_wARP over all reflections and the R factor after averaging can be used to judge the progress of the averaging procedure.