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 +++++++++++++++++++++++++++++++
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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Thomas C. Terwilliger Mail Stop M888 Los Alamos National Laboratory Los Alamos, NM 87545 Tel: 505-667-0072 email: [email protected] Fax: 505-665-3024 SOLVE web site: http://solve.lanl.gov PHENIX web site: http:www.phenix-online.org ISFI Integrated Center for Structure and Function Innovation web site: http://techcenter.mbi.ucla.edu TB Structural Genomics Consortium web site: http://www.doe-mbi.ucla.edu/TB
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 +++++++++++++++++++++++++++++++
_______________________________________________ phenixbb mailing list [email protected] http://www.phenix-online.org/mailman/listinfo/phenixbb
Thomas C. Terwilliger Mail Stop M888 Los Alamos National Laboratory Los Alamos, NM 87545
Tel: 505-667-0072 email: [email protected] Fax: 505-665-3024 SOLVE web site: http:// solve.lanl.gov PHENIX web site: http:www.phenix-online.org ISFI Integrated Center for Structure and Function Innovation web site: http://techcenter.mbi.ucla.edu TB Structural Genomics Consortium web site: http://www.doe- mbi.ucla.edu/TB
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Yes, I'm completely agree with Tom. Pavel. 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 +++++++++++++++++++++++++++++++
_______________________________________________ phenixbb mailing list [email protected] http://www.phenix-online.org/mailman/listinfo/phenixbb
Thomas C. Terwilliger Mail Stop M888 Los Alamos National Laboratory Los Alamos, NM 87545
Tel: 505-667-0072 email: [email protected] Fax: 505-665-3024 SOLVE web site: http://solve.lanl.gov PHENIX web site: http:www.phenix-online.org ISFI Integrated Center for Structure and Function Innovation web site: http://techcenter.mbi.ucla.edu TB Structural Genomics Consortium web site: http://www.doe-mbi.ucla.edu/TB
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Hi Jianghai, the defaults implemented for refinement using NCS are very close to those in CNS and works good in most of the cases. I will work on making it straightforward to use the variable weights, so one can use from loose to tight restraints. This is in to-do list. Currently you can use coordinate_sigma and b_factor_weight parameters (that are specified *outside* the restraint_group scope) to set this weights globally for all groups. Pavel. 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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Dear Phenix, I came across the following: my .mtz reflection file contains columns IMEAN SIGIMEAN F SIGF. phenix.refine picks the IMEAN SIGIMEAN columns (column types are properly assigned, by the way) -- does it per default refine against intensities, e.g. like SHELX? This would probably mean that we better should feed reflection files before TRUNCATE or similar programs, right? Thank you very much, Ulrich ------------------------------------------------------ This mail was sent through IMP at http://mail.unibe.ch
Hi Ulrich, phenix.refine refines only against Fs. We don't have intensity based refinement targets in phenix.refine. If your input file has Is, it will convert them automatically into Fs (to make sure that it actually did it, please look for corresponding message lines in log-file). Pavel. Ulrich Baumann wrote:
Dear Phenix,
I came across the following: my .mtz reflection file contains columns IMEAN SIGIMEAN F SIGF. phenix.refine picks the IMEAN SIGIMEAN columns (column types are properly assigned, by the way) -- does it per default refine against intensities, e.g. like SHELX? This would probably mean that we better should feed reflection files before TRUNCATE or similar programs, right?
Thank you very much,
Ulrich
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participants (4)
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Jianghai Zhu
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Pavel Afonine
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Tom Terwilliger
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Ulrich Baumann