Dear all, I've been working on a series of DNA-protein complex structures. In my recently acquired data sets, I got almost no density for DNA if I do molecular replacement or rigid body fitting with the protein structure, although I am 100% sure I have DNA in the structure by indepenent means. If I use models with DNA, I could find some DNA density with those data sets, but as I refine the structure, the density became very poor. The resolutions for those data sets are between 2.0-2.4 A. Also, if I use the scaled data from synchrotron rather than the re-scaled data at home, I got better DNA density, although for re-scaling, I used site parameters that I copied done from synchrotron. The only differences between those two sets of scaled data are: (1) the original scaled data take into account all reflections, including high resolution data with low completeness/redundancy, which are cut in the re-scaling; (2) error models were changed so chi squares for each bin are 0.8-1.2 for re-scaling.
My (very naive) questions are: (1) Does the DNA density I saw in the cases where I use models with DNA for MR/rigid body fitting only reflect model bias? (2) are simulated annealing or cycles of coordinate/B factor refinement enough to get rid of model bias? (3) Does weak DNA density have to do with data processing? Thanks very much for any suggestion, Melody Lin
