Hi Tom, I have similar experiences with the ncs position restraints. I would rather break the ncs to small groups than use loose restraints. However, I sometimes found there are big differences between the B factors of ncs related groups. So I tend to use a loose restraints on B factors, but that may not be the general case. Jianghai +++++++++++++++++++++++++++++++ Jianghai Zhu, Ph.D CBR Institute for Biomedical Research Department of Pathology Harvard Medical School 200 Longwood Ave., Boston, MA 02115 Ph: 617-278-3211 Fx: 618-278-3232 +++++++++++++++++++++++++++++++ On Mar 27, 2007, at 5:13 PM, Tom Terwilliger wrote:
Hi Jianghai,
Pavel and I have spent a lot of time on this with a systematic study of NCS in refinement, without reaching a final answer, but with some observations. The bottom line: for most applications tight ncs works pretty well. It is very difficult to define the best NCS weighting, and there are not that many cases where loose restraints (e.g., 0.5 A of 1.0 A instead of 0.05 A) do that much good. It is also not so clear that the NCS restraints are generally making a very positive difference (in free R).
Experiences from yourself and others would be useful to hear!
-Tom T
At 02:38 PM 3/27/2007, Jianghai Zhu wrote:
Hi,
I am wondering how the NCS weighting in phenix.refine works. I guess the default values (coordinate_sigma = 0.05, b_factor_weight = 10) are pretty tight. What kind values would be appropriate for medium and loose NCS?
Jianghai
+++++++++++++++++++++++++++++++ Jianghai Zhu, Ph.D CBR Institute for Biomedical Research Department of Pathology Harvard Medical School 200 Longwood Ave., Boston, MA 02115 Ph: 617-278-3211 Fx: 618-278-3232 +++++++++++++++++++++++++++++++
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