I know CCP4 programs best, but you need to find out a) The correlation between the different wavelength anom diffs b) the agreement between the MAD1 and MAD2 data sets. Are they isomorphous? I find this by converting each *.sca file to an MTZ file * See GUI - Data processing) with a sensible column label. eg MAD1_pk MAD1_rm MAD2_pk etc
Then go to the Experimental phasing modue and first combine the files into one, then run scalit to analyse the data sets. If you processed the data with SCALA it gives you the correlation between anom diffs. If you use the SHELXC/D/E GUI for a MAD set it too gives you that correlation? Do you have the latest CCP4 and GUI installed? Run the SHELX suite and see what the graphs look like. You dont say whether you expect MAD1 and MAD2 to contain the same anom scatters? Anyway lets start with these checks then go on from there.. Eleanor [EMAIL PROTECTED] wrote: >*** For details on how to be removed from this list visit the *** >*** CCP4 home page http://www.ccp4.ac.uk *** > > >Dear all, > I am a beginner working on a structure of polysaccharide hydrolase with a MW > of 96 KDa belonging to Orthorhombic (Unit cell a=97, b=120, and c=207). Two > MAD datasets were collected. The resolution limit of the datasets were 2.6 > and 2.8 A respectively. But the density maps calculated with Solve were both > very bad. The followings are the part of the solve log files. > >For Dataset I >Data were colleted at 2 wavelenghth. > >Space group name from file name is: p212121 > Rescaling standard dataset to put it on approximate absolute scale. NRES = > 800; <F**2> expected = 392000. > ; <F**2> observed in lowest resolution shell = 1818.30225 > ... Scale factor = 215.585724 > > ** Completeness of Fbar data at each wavelength: ** > > Completeness of dataset 1 ( F > 2. * sigma) > set 1 with 25 se atoms, lambda 1 > Reflections observed: > Possible Found % complete > shell dmin > 1 5.200 9705 9681 99.8 > 2 3.900 13033 12989 99.7 > 3 3.640 5111 5085 99.5 > 4 3.445 4946 4904 99.2 > 5 3.250 6171 6087 98.6 > 6 3.120 5015 4906 97.8 > 7 2.990 5885 5764 97.9 > 8 2.860 6997 6751 96.5 > 9 2.730 8388 7855 93.6 > 10 2.600 10159 9236 90.9 > total 75410 73258 97.1 > > Completeness of dataset at lambda 2 ( F > 2. * sigma) > >lambda 2 > >Reflections observed: > Possible Found % complete > shell dmin > 1 5.200 9705 9563 98.5 > 2 3.900 13033 12901 99.0 > 3 3.640 5111 5051 98.8 > 4 3.445 4946 4872 98.5 > 5 3.250 6171 6048 98.0 > 6 3.120 5015 4860 96.9 > 7 2.990 5885 5679 96.5 > 8 2.860 6997 6681 95.5 > 9 2.730 8388 7746 92.3 > 10 2.600 10159 8752 86.2 > total 75410 72153 95.7 > >** R-factors for F-bar data dispersive differences ** > > > Dispersive differences lambda 2 - lambda 1 (Delta f-prime = 4.5 ) > > > Differences by shell: > > shell dmin nobs Fbar R scale SIGNAL NOISE S/N > > 1 5.200 9509 477.163 0.039 1.000 23.33 4.59 5.08 > 2 3.900 12839 547.445 0.028 1.000 18.00 5.68 3.17 > 3 3.640 5018 481.398 0.028 1.000 15.79 6.37 2.48 > 4 3.445 4840 446.935 0.029 1.000 14.46 7.06 2.05 > 5 3.250 5999 389.674 0.031 1.000 13.10 7.86 1.67 > 6 3.120 4817 335.666 0.036 1.000 12.03 8.96 1.34 > 7 2.990 5625 300.516 0.039 1.000 10.79 9.70 1.11 > 8 2.860 6574 269.729 0.042 1.000 8.98 11.08 0.81 > 9 2.730 7520 233.048 0.049 1.000 6.12 12.76 0.48 > 10 2.600 8422 217.885 0.051 1.000 0.00 14.01 0.00 > > Total: 71163 381.526 0.035 1.000 14.42 9.21 2.01 > > Recommended resolution cut-off = 2.60 > > Anomalous differences lambda 1 (f" = 4.80000019) > > Differences by shell: > > shell dmin nobs Fbar R scale SIGNAL NOISE S/N > 1 5.200 7955 478.585 0.064 1.000 37.20 7.25 5.13 > 2 3.900 11422 550.020 0.044 1.000 28.75 9.24 3.11 > 3 3.640 4535 482.168 0.045 1.000 24.60 10.33 2.38 > 4 3.445 4389 448.911 0.047 1.000 23.25 11.23 2.07 > 5 3.250 5438 389.837 0.049 1.000 20.37 12.28 1.66 > 6 3.120 4358 338.431 0.054 1.000 17.97 13.88 1.29 > 7 2.990 5120 302.859 0.060 1.000 16.96 14.95 1.13 > 8 2.860 5893 272.366 0.064 1.000 14.06 16.73 0.84 > 9 2.730 6676 236.003 0.073 1.000 9.43 18.96 0.50 > 10 2.600 7624 220.997 0.075 1.000 0.00 20.50 0.00 > > Total: 63410 382.547 0.055 1.000 22.63 14.03 1.97 > > Recommended resolution cut-off = 2.60 > > Anomalous differences lambda 2 (f" = 0.5) > > Differences by shell: > > shell dmin nobs Fbar R scale SIGNAL NOISE S/N > > 1 5.200 7949 478.634 0.013 1.000 6.50 4.51 1.44 > 2 3.900 11418 550.241 0.013 1.000 7.02 5.78 1.22 > 3 3.640 4523 483.174 0.016 1.000 7.17 6.56 1.09 > 4 3.445 4340 450.320 0.017 1.000 6.93 7.09 0.98 > 5 3.250 5371 392.954 0.020 1.000 6.64 7.77 0.85 > 6 3.120 4264 341.815 0.024 1.000 5.86 8.75 0.67 > 7 2.990 4932 305.013 0.028 1.000 5.11 9.61 0.53 > 8 2.860 5628 277.272 0.031 1.000 3.52 10.58 0.33 > 9 2.730 6348 240.449 0.039 1.000 1.53 12.06 0.13 > 10 2.600 7105 224.534 0.046 1.000 0.00 13.22 0.00 > > Total: 61878 387.563 0.021 1.000 5.59 8.86 0.76 > > Recommended resolution cut-off = 2.60 > > CORRELATION FOR > WAVELENGTH PAIRS > DMIN 1 VS 2 > > 5.20 0.47 > 3.90 0.36 > 3.64 0.26 > 3.44 0.27 > 3.25 0.26 > 3.12 0.20 > 2.99 0.16 > 2.86 0.14 > 2.73 0.14 > 2.60 0.08 > > ALL 0.27 > >Final refined values of fprime and fdoubleprime > > Form factors at lambda = 0.9792 > f-prime = -8.50 > f" = 15.22 > > Form factors at lambda = 0.9952 > f-prime = -4.00 > f" = 1.87 >FIGURE OF MERIT < 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 >1.0 > # OF REFLECTIONS 5827 3953 4270 4575 4881 5024 5097 5024 5368 > 29948 > > FIGURE OF MERIT WITH RESOLUTION > DMIN: TOTAL 9.06 5.82 4.58 3.90 3.45 3.13 2.88 2.68 > N: 73967 3876 6318 7960 9284 10404 11384 12143 12598 > MEAN FIG MERIT: 0.67 0.85 0.87 0.83 0.79 0.73 0.64 0.54 0.43 > >For Dataset II > >Space group number is: 19 > Space group name from file name is: p212121 > Rescaling standard dataset to put it on approximate absolute scale. NRES = > 800; <F**2> expected = 392000. > ; <F**2> observed in lowest resolution shell = 598.400085 > ... Scale factor = 655.080139 > > -------------------------------------------------- > > *** Analysis of this scaled MAD data set *** > > Fbar,sigma,Delano,sigma for 3 wavelengths written to: > mad_fbar.scl > > > F+,sigma,F-,sigma for 3 wavelengths written to: > mad_fpfm.scl > > > ** Completeness of Fbar data at each wavelength: ** > > Completeness of dataset 1 ( F > 2. * sigma) > set 1 with 28 se atoms, lambda 1 > > Reflections observed: > > Possible Found % complete > shell dmin > > 1 5.600 7770 7692 99.0 > 2 4.200 10389 10309 99.2 > 3 3.920 4103 4050 98.7 > 4 3.710 3937 3880 98.6 > 5 3.500 4887 4816 98.5 > 6 3.360 3982 3886 97.6 > 7 3.220 4710 4545 96.5 > 8 3.080 5592 5336 95.4 > 9 2.940 6705 6284 93.7 > 10 2.800 8099 7353 90.8 > > total 60174 58151 96.6 > > > Completeness of dataset 2 ( F > 2. * sigma) > set 2 > > Reflections observed: > > Possible Found % complete > shell dmin > > 1 5.600 7770 7644 98.4 > 2 4.200 10389 10234 98.5 > 3 3.920 4103 4024 98.1 > 4 3.710 3937 3855 97.9 > 5 3.500 4887 4780 97.8 > 6 3.360 3982 3857 96.9 > 7 3.220 4710 4508 95.7 > 8 3.080 5592 5278 94.4 > 9 2.940 6705 6180 92.2 > 10 2.800 8099 7173 88.6 > > total 60174 57533 95.6 > > > Completeness of dataset 3 ( F > 2. * sigma) > set 3 > > Reflections observed: > > Possible Found % complete > shell dmin > > 1 5.600 7770 7597 97.8 > 2 4.200 10389 10247 98.6 > 3 3.920 4103 4040 98.5 > 4 3.710 3937 3870 98.3 > 5 3.500 4887 4773 97.7 > 6 3.360 3982 3884 97.5 > 7 3.220 4710 4518 95.9 > 8 3.080 5592 5294 94.7 > 9 2.940 6705 6247 93.2 > 10 2.800 8099 7321 90.4 > > total 60174 57791 96.0 > > ** R-factors for F-bar data dispersive differences ** > > > Dispersive differences lambda 2 - lambda 1 (Delta f-prime = 1.35000038 ) > > > Differences by shell: > > shell dmin nobs Fbar R scale SIGNAL NOISE S/N > > 1 5.600 7585 478.848 0.026 1.000 14.77 4.76 3.10 > 2 4.200 10162 555.376 0.025 0.999 16.13 5.75 2.80 > 3 3.920 3991 528.172 0.027 1.000 16.47 6.76 2.44 > 4 3.710 3820 491.892 0.029 1.000 16.26 7.47 2.18 > 5 3.500 4737 465.015 0.030 1.000 15.28 8.15 1.88 > 6 3.360 3815 416.568 0.033 1.000 14.44 9.18 1.57 > 7 3.220 4432 372.983 0.035 1.000 12.60 10.55 1.19 > 8 3.080 5188 331.492 0.038 1.000 10.64 11.86 0.90 > 9 2.940 6040 296.977 0.040 1.000 7.33 13.09 0.56 > 10 2.800 6973 261.469 0.046 1.000 0.00 14.97 0.00 > > Total: 56743 423.745 0.031 1.000 13.22 9.72 1.73 > > Recommended resolution cut-off = 2.80 > > Dispersive differences lambda 3 - lambda 1 (Delta f-prime = 4.5 ) > > Differences by shell: > > shell dmin nobs Fbar R scale SIGNAL NOISE S/N > > 1 5.600 7528 478.218 0.042 1.000 24.29 5.15 4.72 > 2 4.200 10185 554.469 0.029 1.000 18.91 6.24 3.03 > 3 3.920 3992 527.166 0.028 1.000 16.93 7.22 2.34 > 4 3.710 3833 491.894 0.029 1.000 16.25 7.99 2.03 > 5 3.500 4736 464.924 0.030 1.000 15.46 8.57 1.80 > 6 3.360 3835 414.412 0.032 1.000 13.41 9.86 1.36 > 7 3.220 4440 372.431 0.035 1.000 12.13 10.98 1.11 > 8 3.080 5196 331.379 0.040 1.000 10.68 12.41 0.86 > 9 2.940 6078 295.903 0.043 1.000 7.71 13.78 0.56 > 10 2.800 7042 259.767 0.049 1.000 0.00 15.77 0.00 > > Total: 56865 422.607 0.035 1.000 15.50 10.28 1.94 > > Recommended resolution cut-off = 2.80 > > Dispersive differences lambda 3 - lambda 2 (Delta f-prime = 5.85000038 ) > > Differences by shell: > > shell dmin nobs Fbar R scale SIGNAL NOISE S/N > > 1 5.600 7505 478.758 0.040 1.000 23.28 5.01 4.65 > 2 4.200 10127 555.478 0.029 1.000 19.30 6.06 3.19 > 3 3.920 3976 526.936 0.028 1.000 17.22 7.19 2.39 > 4 3.710 3810 491.762 0.028 1.000 15.44 7.94 1.95 > 5 3.500 4707 465.852 0.030 1.000 15.30 8.53 1.79 > 6 3.360 3810 415.456 0.032 1.000 13.50 9.92 1.36 > 7 3.220 4405 372.816 0.036 1.000 12.61 11.16 1.13 > 8 3.080 5141 332.928 0.038 1.000 9.67 12.51 0.77 > 9 2.940 6027 297.986 0.043 1.001 8.14 14.00 0.58 > 10 2.800 6902 262.461 0.049 1.000 0.00 15.97 0.00 > > Total: 56410 424.111 0.035 1.000 15.36 10.33 1.95 > > Recommended resolution cut-off = 2.80 > > Anomalous differences lambda 1 (f" = 4.80000019) > > Differences by shell: > > shell dmin nobs Fbar R scale SIGNAL NOISE S/N > > 1 5.600 6279 480.650 0.045 1.000 26.27 6.69 3.93 > 2 4.200 9087 559.047 0.033 1.000 21.72 8.32 2.61 > 3 3.920 3618 531.744 0.032 1.000 18.90 9.64 1.96 > 4 3.710 3477 490.958 0.035 1.000 18.20 10.85 1.68 > 5 3.500 4336 467.008 0.036 1.000 16.93 11.65 1.45 > 6 3.360 3507 417.485 0.037 1.000 14.71 13.04 1.13 > 7 3.220 4042 374.486 0.042 1.000 13.31 14.43 0.92 > 8 3.080 4697 336.508 0.046 1.000 11.02 15.85 0.70 > 9 2.940 5475 300.508 0.053 1.000 9.54 17.42 0.55 > 10 2.800 6223 265.048 0.059 1.000 0.00 19.33 0.00 > > Total: 50741 425.828 0.040 1.000 17.11 13.20 1.61 > > Recommended resolution cut-off = 2.80 > >CORRELATION FOR > WAVELENGTH PAIRS > DMIN 1 VS 2 1 VS 3 2 VS 3 > > 5.60 0.81 0.42 0.46 > 4.20 0.68 0.31 0.33 > 3.92 0.58 0.28 0.28 > 3.71 0.55 0.22 0.25 > 3.50 0.53 0.21 0.21 > 3.36 0.48 0.23 0.18 > 3.22 0.45 0.16 0.12 > 3.08 0.41 0.16 0.11 > 2.94 0.43 0.16 0.12 > 2.80 0.36 0.09 0.09 > > ALL 0.53 0.22 0.20 > >FIGURE OF MERIT < 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 >1.0 > # OF REFLECTIONS 16398 10592 7892 5982 4751 4089 3496 2982 2212 > 705 > > FIGURE OF MERIT WITH RESOLUTION > DMIN: TOTAL 9.68 6.25 4.93 4.19 3.71 3.37 3.10 2.89 > N: 59099 3129 5032 6353 7412 8290 9070 9676 10137 > MEAN FIG MERIT: 0.30 0.51 0.45 0.42 0.39 0.34 0.26 0.18 0.13 > >Sorry for the length of the letter. But I really need your help. I'd like two >know if these 2 datasets can be used to solve structure. > >Someone told me to transform the .sca file (scalepak) to .mtz file and use >the .mtz to Sovle the phase. Will this work? Does anyone have such experence? > >Zhongli Cui >College of Life Sciences >Nanjing Agricultural University >People's Republic of China > > > > > > >
begin:vcard fn:Eleanor Dodson n:Dodson;Eleanor email;internet:[EMAIL PROTECTED] tel;work:+44 (0) 1904 328259 tel;fax:+44 (0) 1904 328266 tel;home:+44 (0) 1904 424449 version:2.1 end:vcard
