PAIREF - results poli67

Input parameters

Project:

poli67

High resolution diffraction limits:

2.30 Å, 2.20 Å, 2.10 Å, 2.00 Å, 1.90 Å

Initial structure model:

poli67_edit12_refmac1.pdb

Merged diffraction data:

poli67_R.mtz

Unmerged diffraction data:

XDS_ASCII.HKL

Weight matrix for REFMAC5:

0.0600

Number of refinement cycles that will be performed in every resolution step:

Number of pre-refinement cycles that will be performed before the paired refinement protocol:

Data with FreeRflag set 0 will be excluded during refinement.

Run details and program versions

Working directory:

/public/pairef_datasets/publication_examples/3-5_POLI/pairef_poli67

Run date and time:

2020-05-28 10:46:53

user@host:

maly@localhost

PAIREF version:

1.1.0

REFMAC5 version:

5.8.0258

Python version and executable:

2.7.15 /protein2/phenix/phenix-1.16-3546/build/../conda_base/bin/python2.7

matplotlib version:

2.2.3

Overall values

Raw data: poli67_R-values.csv

# Shell      Rwork(init) Rwork(fin) Rwork(diff)   Rfree(init) Rfree(fin) Rfree(diff)
2.30A->2.20A      0.2236     0.2216     -0.0020        0.2971     0.2967     -0.0004
2.20A->2.10A      0.2279     0.2294      0.0015        0.3027     0.3003     -0.0024
2.10A->2.00A      0.2322     0.2318     -0.0004        0.3107     0.3097     -0.0010
2.00A->1.90A      0.2412     0.2417      0.0005        0.3152     0.3160      0.0008

Note: For each incremental step of resolution from X->Y, the R-values were calculated at resolution X.

Raw data: poli67_Rgap.csv

Note: The R-values were calculated at 2.30 Å resolution.

Merging statistics

WARNING: A CC*-value for a particular shell could not be calculated. (CC1/2 = -0.132)

#shell d_max d_min #obs #uniq mult. %comp <I> <I/sI> r_mrg r_meas r_pim cc1/2 cc_ano cc* 01 47.05 5.13 22367 1948 11.48 99.44 494.1 38.8 0.042 0.044 0.013 0.999 -0.214 0.9997 02 5.13 3.63 42232 3343 12.63 99.79 203.3 31.7 0.064 0.067 0.019 0.999 -0.163 0.9997 03 3.63 2.97 57138 4246 13.46 99.95 56.9 14.3 0.151 0.157 0.042 0.997 -0.166 0.9992 04 2.97 2.57 65007 5014 12.97 99.70 11.3 4.0 0.622 0.648 0.178 0.951 -0.025 0.9874 05 2.57 2.30 73887 5623 13.14 99.89 3.7 1.3 1.839 1.914 0.523 0.730 -0.014 0.9187 06 2.30 2.20 37405 2818 13.27 99.93 1.6 0.6 4.462 4.641 1.263 0.400 0.033 0.7559 07 2.20 2.10 45724 3363 13.60 99.91 0.9 0.3 7.623 7.920 2.129 0.196 -0.008 0.5725 08 2.10 2.00 49772 4021 12.38 98.51 0.3 0.1 16.989 17.721 4.963 0.027 0.008 0.2293 09 2.00 1.90 35920 4046 8.88 81.18 0.1 0.0 41.435 43.993 14.417 -0.132 -0.016 N/A

Statistics vs. cycle

Log file from refinement at 2.30 Å
Structure model refined at 2.30 Å PDB mmCIF

Log file from refinement at 2.20 Å
Structure model refined at 2.20 Å PDB mmCIF

Log file from refinement at 2.10 Å
Structure model refined at 2.10 Å PDB mmCIF

Log file from refinement at 2.00 Å
Structure model refined at 2.00 Å PDB mmCIF

Log file from refinement at 1.90 Å
Structure model refined at 1.90 Å PDB mmCIF

References

Paired refinement under control of PAIREF. M. Maly, K. Diederichs, J. Dohnalek, P. Kolenko (2020) IUCrJ (to be published)

Overview of the CCP4 suite and current developments. Collaborative Computational Project, Number 4 (2011) Acta Cryst. D67:235–242

REFMAC5 for the refinement of macromolecular crystal structures. G.N. Murshudov, P. Skubak, A.A. Lebedev, N.S. Pannu, R.A. Steiner, R.A. Nicholls, M.D. Winn, F. Long, A.A. Vagin (2011) Acta Cryst. D67:355–367

SFCHECK: a unified set of procedures for evaluating the quality of macromolecular structure-factor data and their agreement with the atomic model. A.A. Vaguine, J. Richelle, S.J. Wodak (1999) Acta Cryst. D55:191–205

The Computational Crystallography Toolbox: crystallographic algorithms in a reusable software framework. R.W. Grosse-Kunstleve, N.K. Sauter, N.W. Moriarty, P.D. Adams (2002) J. Appl. Crystallogr. 35:126–136

Linking crystallographic model and data quality. P.A. Karplus & K. Diederichs (2012) Science 336:1030–3

Assessing and maximizing data quality in macromolecular crystallography. P.A. Karplus & K. Diederichs (2015) Cur. Op. in Str. Biology 34:60–68

Better models by discarding data? P.A. Karplus & K. Diederichs (2013) Acta Cryst. D59:1215–1222

Results - poli67