SQUASH is a density modification program suite that combines constraints from Sayre's equation, molecular averaging, solvent flattening and histogram matching (1D & 2D).
| VMS version | 10/AUG/88 | Kam Zhang | Department of Physics, University of York, UK |
| UNIX version | 1/OCT/89 | Kam Zhang | Department of Physics, University of York, UK |
| further work | 16/NOV/89 | Kevin Cowtan | Department of Physics, University of York, UK |
| further extension | 22/MAY/92 | Kam Zhang | Molecular Biology Institute, University of California at Los Angeles, USA |
| SQUASH 1.0 | 21/DEC/92 | Kam Zhang | Molecular Biology Institute, University of California at Los Angeles, USA |
| SQUASH 2.0 | 24/MAY/99 | Yeu-Perng Nieh | Fred Hutchinson Cancer Research, Seattle, USA |
Please report problems or suggestions to kzhang@fhcrc.org
SQUASH is an integrated density modification program for macromolecular phase refinement and extension that combines histogram matching, solvent flattening, Sayre's equation and molecular averaging.
The constraints used in these methods are the correct local shape of the electron density, equal molecules, solvent flatness and the correct distribution of electron density values and its gradients. These constraints on electron densities are satisfied simultaneously by solving a system of non-linear equations by Newton-Raphson method using FFT, and followed by a phase combination procedure.
In release 2.0, a two-dimensional (2D) histogram matching method was introduced that employs the joint probability distribution of electron density values and its gradient as a constraint for density modification. This has greatly enhanced the power of existing histogram matching methods which only utilized the constraint on electron density values.
In addition to the various density modification methods mentioned above, several useful operations are provided for users convenience, eg Wilson scaling, calculation of map from atomic coordinates, transformation between map and structure factors. Non-crystallographic symmetry operations can also be refined by a rotation and translation space search and a least squares minimization method, thereby reducing the chance of introducing systematic phase errors during averaging.
Constraints used in SQUASH and their implementation will be described in the following sections with more emphasis on the 2D histogram matching because it is a new feature in the program. More detailed information can be found in the references given.
The density histogram(1D histogram) of a map is the probability distribution of electron density values. It specifies not only the permitted values of the electron density but also their frequencies of occurrence. It provides a global description of the appearance of the map and all spatial information is discarded.
The ideal histogram of an unknown structure can be predicted from well-defined structures due to the structure conformation independence among different structures. Proteins generally have very similar atomic composition and atomic bonding pattern. The differences are mainly the order with which amino acid residues are arranged and the dihedral angles adopted between adjacent neighboring residues. The density histogram discards the spatial information of the electron density maps and therefore is independent of the above factors that make each structure different. The density histogram captures the commonality between different structures: the similar atomic composition and the characteristic distances between atoms. These common features distinguish the correct structures from incorrect structures. Therefore, the ideal density histogram can be used to improve an electron density map or to select a correct phase set among many randomly generated phase sets in ab initio phasing.
The density histogram, however, is degenerate in encoding structural information. While having an ideal density distribution is a necessary condition for being a correct structure, it is not a sufficient condition. Incorrect structures may incidentally adopt the ideal density distribution. Moreover, the density histogram does not capture all the common features in protein structures. A two-dimensional (2D) histogram matching method was introduced in the release 2.0 which employs the joint probability distribution of electron density values and its gradient as a constraint in a density modification procedure.
The density gradient reflects the change of the density value within a local region and therefore provides a description of the local environment. The information from the gradient distribution is complementary to the density distribution, which only accounts for the value at a given point and disregards its neighboring environment. The addition of gradient in the 2D histogram reduces the degeneracy in the 1D density histogram.
The electron density value at position (x,y,z) as a Fourier transform of structure factors F(hkl) is shown in equation (1), where (x,y,z) are the fractional coordinates along the crystal axes , (hkl) are the indices of the structure factors and V is the unit cell volume. The gradients along each of the three crystal axes are shown in equations (2)-(4). The three gradient maps, gx, gy and gz can be efficiently calculated by FFT using the modified Fourier coefficients hF, kF, lF , respectively. The three gradient maps, gx, gy and gz are then transformed from the crystal axes system to orthogonal axes system before the accumulation of 2D histograms.
The gradient maps are modified by 1D histogram matching on gradient in an analogous way as the 1D histogram matching on density. Although the histogram matching is carried out on the density gradients, it is necessary to transform the modified gradient maps back to structure factors in order to apply the phase combination with the observed structure factors. Based on equations (2)-(4), we found that the structure factors can be calculated through inverse FFT with either of the three density gradients gx, gy and gz as the Fourier coefficients (equations (5)-(7)). Therefore, after the histogram matching on gx, gy and gz followed by the inverse FFT, three structure factor sets are generated, which are then averaged to give the final structure factor set.
The 2D histogram matching on density and its gradients is achieved through two alternating steps of 1D matching on density and 1D matching on gradients. The histogram matching on density follows the method described by Zhang & Main(1990a). In this method, the new electron density value is derived from the old electron density value through a linear transform such that the cumulative distribution of the new density value equals to the cumulative distribution of the ideal histogram. The histogram matching on gradients also follows a similar protocol in which the density value was replaced by the gradients. The modified gradient maps were converted to the modified structure factors by the fast Fourier transform method.
The implementation of 2D histogram matching has been tested in two modes, the parallel mode and the sequential mode. For the parallel mode, the histogram matching on density and gradients is applied in parallel using the same initial structure factor set. After matching, the two new structure factor sets are combined. For the sequential mode, the structure factor set calculated after density histogram matching is used as input for the histogram matching on gradients and vice versa. Our test cases suggested that the histogram matching using sequential mode gave better phase improvement in less number of matching cycles and converged to higher histogram correlation coefficients compared to the parallel mode. Therefore, we suggest users use the sequential mode for the 2D histogram matching.
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The consensus histograms were generated based on the averaged histograms calculated from the atomic coordinates of 16 protein structures of different fold families, after removing the overall temperature factor from the electron density map. Therefore, these ideal histograms are independent of the temperature factor of protein structures. Since 2D histograms are resolution dependent, several ideal histograms were generated for a range of resolutions from 4 Å to 1.0 Å using the method describe by Goldstein and Zhang(1998).
Solvent flattening exploits the fact that the electron density in the solvent region is featureless at medium resolution, owing to the high thermal motion and disorder of solvent molecules. The flattening of the solvent region suppresses noise in the map and therefore improves phases.
A solvent mask is needed for employing solvent flattening. If the user does not supply a solvent mask, it will be calculated by Wang's automated convolution algorithm(1985) using the reciprocal space approach of Leslie(1987). Once the envelope is determined, solvent flattening is performed simply by setting the density in the solvent region to the expected solvent density value.
Sayre (1952) pointed out that for equal and resolved atoms, the density distribution is equal to the squared density convoluted with an atomic shape function. Sayre's equation constrains the local shape of electron density. It is an exact equation at atomic resolution in an equal atom system. For macromolecular structures where atomic resolution data are seldom available, the shape function is modified to accommodate the overlapping of atoms at non-atomic resolution. Please see Main(1990), Zhang & Main(1990b) for details of the implementation of Sayre's equation.
Molecular averaging enforces the equivalence of electron density values at grid points related by non-crystallographic symmetry(NCS). The averaging procedure can filter noise, correct system error, and even determine phases ab initio in favorable cases.
The self-rotation symmetry is now routinely solved by the use of a Patterson rotation function (Rossmann & Blow, 1962). The translation symmetry can be determined by a translation function (Crowther & Blow, 1967), when a search model, either an approximate structure of the protein to be determined or the structure of a homologous protein, is available. The search of the Patterson rotation and translation functions is achieved typically using software such as AMORE(Navaza,1994). In cases where no search model is available or the Patterson translation function is unsolvable, either the whole electron density map, or a region which is expected to contain a molecule, may be rotated using the rotation solution and used as a search model in a phased translation function(Read & Schierbeek, 1988).
Once the averaging operators are determined, the mask can be obtained using the local density correlation function as developed by Vellieux et al(1995). This is achieved by a systematic search for extended peaks in the local density correlation, which must be carried out over a volume of several unit cells in order to guarantee finding the whole molecule. The local correlation function distinguishes those volumes of crystal space that map onto similar density under transformation by the averaging operator. Therefore, in the case of improper NCS, a local correlation mask will cover only one monomer. In the case of a proper symmetry, a local correlation mask will cover the whole complex, since every operator will map one copy of the molecule onto another copy.
The initial NCS operation obtained from rotation and translation functions or heavy atom positions can be fine-tuned by a density space R-factor search in the six dimensional rotation and translation space. The six-dimensional search is very time-consuming. The search rate can be increased by using only a representative subset of grid points. The NCS operation is systematically altered to find the lowest density space R-factor for the selected subset of grid points.
The translation search rate can be increased by using 3 fast Fourier transforms(FFT) according to the convolution theorem. Then, the 6-D rotation and translation space search can be reduced to a 3-D rotation space search with 3 FFT's.
The NCS operation solution from the 6-D rotation and translation search can be further refined by a least-squares procedure. The solution to the NCS parameters can be obtained by minimizing the density residual between the NCS related molecules.
Once the mask and the matrices are determined, the electron density map may be modified by averaging. Averaging is carried out as proposed by Bricogne(1976) except that the double sorting procedure is avoided by storing the whole map in the memory.
Every grid point in the unit cell is mapped to the grid point within the subunit mask where the NCS holds and the NCS operation is subsequently applied.
The program can deal with a general non-crystallographic operation given the mask of the subunit where the NCS operator is valid.
The mapping procedure gives the appropriate crystallographic or non-crystallographic operation which could transform each grid point to the subunit mask. Thus, the mask for partitioning the protein from solvent can be derived from this mapping.
The average density value for each NCS related grid points is determined. The value assigned to each grid point can be adjusted toward the mean density according to a weight.
Once a modified map is obtained , modified structure factors can be calculated by inverse FFT. The MIR phase probability distribution is given by Blow and Crick(1959). The probability distribution for phases calculated from the modified map is determined using the Sim's weighting scheme (Sim, 1959) as adapted by Bricogne(1976). The phases are combined by multiplying their respective phase probabilities (Bricogne, 1976). This multiplication of phase probabilities is simplified by adding the coefficients that code for phase probabilities(Hendrickson & Lattmann, 1970).
SQUASH uses dynamic memory allocation. The actual memory needed to run SQUASH depends on what functions you are running. For example, HM2D(2d histogram matching) needs more memory space than WILS(Wilson statistics) does. The grid sampling NX,NY,NZ in your structure determines the size of several big arrays which are used to store the structure factor data and map data. Be sure to set them appopriately. See grid sampling for details.
If histogram matching or Sayre's equation is used, the structure factor amplitudes must be on absolute scale. The scale factor and overall temperature factor can be estimated from Wilson statistics (FUNC WILS) by giving the unit cell content. Note that it's difficult to estimate the exact unit cell content since there is a large volume of disordered solvent. A good estimate of the overall temperature factor can be achieved given correct ratio of chemical composition in the unit cell. The scale factor from Wilson statistics is generally underestimated since solvent contribution is either ignored or not given correctly. The program uses the histogram scaling to correct the Wilson scale factor by matching the variance of the protein region of the map to that of the ideal histogram.
The mask can be calculated automatically within the program and it will be updated after every cycle of refinement. The user can input a mask by assigning a file with logical name MASKIN. This is recommended when the molecule has flexible regions or at the later stage of map interpretation when the partial model is known.
The mask used for averaging is the MASK or MASKIN by default. The user can give a different mask for averaging by assigning the logical file name MASKAVE. This is used when the molecules are related by improper non-crystallographic symmetry or only portion of the molecule is related by NCS operation. The MASKAVE defines the single molecule which the NCS operations are valid for. You can also supply a mask, called MASKAVE2, which defines those molecules which are related by the NCS operations(this is optional).
Sayre's equation works better at higher resolution. Experiments established that it works starting from even 3.5A. Nevertheless, it's recommended to give Sayre's equation a low weight when refining at lower resolution.
Extend the phase within a resolution range in a number of step. The reciprocal space vector length of the extended resolution should not be longer than that of the starting resolution.
If you want to use SQUASH to break the phase ambiguity, it's highly recommended to use Hendrickson & Lattmann coefficients instead of figure of merit. Since the best phase is the average of the two possible phases, the FOM can only give you a phase distribution centered in between the two possible phases. Whereas the A B C D truly represent the bimodal distribution centered on the two possible phases. It's easier to break up the phase ambiguity by density modification through phase recombination.
SQUASH provides a CGI Perl script for generating graphs (eg. a graph of histogram correlation coefficient vs. refinement cycle) to give users graphical information about the density modification results. You need to have a Web server setup somewhere in your machine or others that you have access to and install the script under your web server's 'cgi-bin' directory. You also need to define the GGIBIN environmental variable that refers to the URL containing this CGI script (CGIBIN should have been defined in the 'squash.setup' file in $SQUTOP directory)
When you read in your browser the html-based log file (ie. ${HTMLBASE}.html), you will see in the index frame the link to 'Plot 2D histogram c.c.' (if you are running with s2hg function). If you follow that link, you will see the 'Plot' button in the content frame. You can click that button and SQUASH will initiate the CGI script. When asking for the file upload for plotting, give it the content frame file, ie. ${HTMLBASE}_log.html .
An off-line Perl script 'gengraph.pl' is also provided in the package for generating
graphs without needing a Web server. This script by default can be
found in the same directory as the SQUASH executable. When running this script,
use the following command:
gengraph.pl 'logfile' 'output-gif-file'
where,
'logfile' is the content frame log file, ie. ${HTMLBASE}_log.html
'output-gif-file' is the file name for the output image file in GIF format.
In either cases, you need to have Perl (5.004 or later) and two Perl modules, GD(1.15 or later) and GIFgraph(1.10 or latest), installed. You can find Perl here and GD & GIFgraph modules here.
input MTZ file.
Output MTZ file.
HKLOUT contains those columns in the HKLIN and those extra columns specified by LABO.
HTML-based output log file.
Three html files will be output, ie. ${HTMLBASE}.html, ${HTMLBASE}_index.html and ${HTMLBASE}_log.html .
You can use your browser to read ${HTMLBASE}.html which will display two frames within its page, one is the index frame (${HTMLBASE}_index.html) and the other is the content frame (${HTMLBASE}_log.html). Or you can simply read the content page itself, ie. ${HTMLBASE}_log.html .
Map input (optional).
If given, the program will read in the map as a starting map for SQUASH. The map can in any axis order. It will be permuted by the program.
Map output (optional).
If given, the program will write the final map after SQUASH in any given axis order.
Molecular envelope file, needed for histogram matching and solvent flattening. The mask will be calculate by the program.
Input mask from user which partitions the protein from solvent. Activated by assigning file to MASKIN. It will override MASK. It must be in packed CCP4 format for the full unit cell.
Input mask for averaging which specifies the region of map where the non-crystallographic symmetry(NCS) is operated upon.
This must be the mask corresponding to the single subunit of protein where the NCS holds in case of improper NCS. Activated by assigning a file name to MASKAVE. If not given, the MASK or MASKIN will be used for averaging.
Input mask for averaging which specifies the region of map where the non-crystallographic symmetry(NCS) holds.
This must be the mask corresponding to the subunits that are related by the NCS operations. Activated by assigning a file name to MASKAVE2. If not given, the MASKAVE2 will be generated from MASKAVE and NCSGrid which defines the box where NCS are valid.
symmetry operation file
Input PDB file needed for some functions such as 'FUNC ATSF'
AXIS CELL CONT DPLB END FCLB FORM FUNC GRID HKLW HMCT LABI LABO LOOK MATR MNXH MODE NCSG NGAU NMUL PRTV RANG RESO ROTR RSCB SCAL SIGM SOLC SOLV SPLL SYMM TITL XYZL
Note: All keywords are case insensitive and only the first 4 characters will suffice. Items are in free format input and separate by space or comma. Those items in square bracket are optional. Items in curly bracket are the alternatives.
AXIS Z, X, Y (optional) (default)
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CELL A, B, C (in Å), alpha, beta, gamma (in degree)
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Program stores scattering factor for most of the elements in the periodic table. Each atom type denoted by the convention of periodic table and followed by the number of that atom in the unit cell. Additional form factors can be read in from FORM card.
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DPLB Rmax Phi1 Phi2 FO [SIGFO]
Program calculates the phase error between Phi1 and Phi2 and is implemented through the function CORR. Rmax is the maximum value for the resolution for the calculation. Phi1 and Phi2 are the assigned column names for the phase data to be compared. FO is the assigned column name for Fobs.
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END must be placed at end of .com file to signify end of data cards
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FCLB Label1 Label2
They are used in conjunction with the function CORR. Label1 and Label2 are character strings as specified in the LABO or LABI assignments. SQUASH determines the correlation between two specified sets of reflections at the end of the run. Label1 is typically Fobs and Label2 is the assignment for FCOUT.
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FORM AtomName, a1, a2, b1, b2, c
AtomName - name of the atom.
a1, a2, b1, b2 and c - the atomic scattering factors in the Intl. Tables.
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FUNC ['wilson'], ['sayr'], ['solv'], ['hm2d'], ['averaging'], ['ncsrefine'],['rsearch'],['patsearch']
Choose any one or a combination of above character strings to specify what kind of function that the program should perform.
where,
Additional functionas available are:
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GRID NX, NY, NZ
See restrictions below and beware that prime factors can't be higher than 19.
The electron density is sampled according to this grid setup, so if it is too coarse you will introduce errors into the structure factor calculation. On the other hand the time and the memory required are largely dependent on the HMAX, KMAX, LMAX (calculated by program from cell dimensions and maximum 4SIN**2/L**2) and NX, NY, NZ, so it is advantageous to keep them as small as possible.
NX, NY and NZ must always be greater than 2*HMAX, 2*KMAX and 2*LMAX, respectively. Recommended grid sampling is 1/2 of your data resolution and 1/3 if you are running functions involving gradient calculation, such as 2D histogram matching.
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HKLW mode, radius
| mode : 1 | - weight by 1 - r/R |
| : 2 | - weight by 1 - (r/R)² |
| radius | - in Å (recommended between 6 - 10Å) |
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HMCT mode
This card is used with 'FUNC HM2D' ,which performs 2d histogram matching. The following three modes are available. The 2d sequential mode is highly recommended!
| mode : 1 | - 1d matching on rho only |
| : 2 | - 2d sequential mode (1d matching on rho + 1d matching on gx, gy, gz) |
| : 3 | - 2d parallel mode (1d matching on rho + 1d matching on gx, gy, gz) |
Default : HMCT 2
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LABI FO=? [SIGFO=?] PHIO=? [FOMO=?] [AO=?] FC=? [SFC=?] PHIC=? [FOMC=?] [AC=]
? represents the appropriate column labels.
FO, PHIO, FC and PHIC are compulsory.
| FO | : Observed Structure factors |
| SIGFO | : 'standard deviation' of FO |
| PHIO | : Experimental phase angle in degrees |
| FOMO | : Figure of merit for PHIO |
| AO | : Hendrickson & Lattmann coefficients(A B C D) for phase probability |
The above are the data used for phase recombination. So the magnitude, phases and figure merits should be experimental ones such as MIR phases and FOM.
You just need to assign program label AO if you want to use Hendrickson and Lattmann coefficients. It assumes that B C D follows right after A in the MTZ file.
Note: A B C D is highly recommended over FOMO if you are trying to improve SIR phases.
| FC | : Structure factor magnitudes for the initial map |
| SFC | : 'standard deviation' of FC |
| PHIC | : Initial phase angle in degrees |
| FOMC | : Figure of merit for PHIC |
| AC | : Hendrickson & Lattmann coefficients (A B C D) for phase probability |
The above are the structure factor, phase and FOM to calculate the initial map. Note that FC, SFC, PHIC and FOMC are normally the same as FO, SIGFO, PHIO and FOMO but they can be different, such as when you want to initiate the calculation with a modified map. In this case, the FC, SFC, PHIC and FOMC are those corresponding to the modified map.
You just need to assign program label AC if you want to use Hendrickson and Lattmann coefficients. It assumes that B C D follows right after A in the MTZ file.
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LABO FCOUT=? PHICOUT=? [FOMCOUT=?] [AOUT=?]
? represents the appropriate column labels.
| FCOUT | : the column label for the output magnitudes |
| PHICOUT | : the column label for the output phases |
| FOMCOUT | : the column label for the combined figure of merit |
You can also write out Hendrickson & Lattmann coefficients for the combined phase probability by given
| FCOUT | : the column label for the output magnitudes |
| PHICOUT | : the column label for the output phases |
| ACOUT | : the column label for the output H-L coefficient A |
| BCOUT | : the column label for the output H-L coefficient B |
| CCOUT | : the column label for the output H-L coefficient C |
| DCOUT | : the column label for the output H-L coefficient D |
Note: The program automatically calculates the phase and FOM from the Hendrickson-Lattman coefficients and vise versa. Therefore, you only need to supply the phase or H-L coefficients. However, if both phase and H-L coefficients are given, the phase takes priority.
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LOOK key
| key - 0: | Minimum output (default) |
| 1: | Monitor the conjugate gradient solution |
| 2: | Monitor the intermediate maps |
| 3: | Monitor the least squares NCS refinement. |
The higher the number, the more output!
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| MATR | m11 m12 m13 |
| m21 m22 m23 | |
| m31 m32 m33 | |
| m41 m42 m43 |
The first three lines are the rotation matrix elements. The last line is the translational component.
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MNXH Hmin Kmin Lmin Hmax Kmax Lmax
Hmin,Kmin,Lmin,Hmax,Kmax and Lmax are the minimum and maximum value of indices H K and L respectively. This is used only you want to override the calculated values by the program.
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MODE Method, ThetaType, [Weight1], [Weight2]
| method : 1 | - full matrix calculation |
| : 2 | - diagonal approximation (default) |
| ThetaType : 1 | - analytical formula (for atomic resolution data) |
| : 2 | - numerical curve fitting |
| : 3 | - empirical data (default, preferred for proteins) |
| Weight1 | - relative weight between density modification (histogram matching/solvent flattening/averaging) and Sayre's equation. The scale is multiplied on the density modification part of the equation.(Default is 1) |
| Weight2 | - weight on averaging. (Default is 1) |
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NCSG nxmin, nxmax, nymin, nymax, nzmin, nzmax
The parameters are the minimum and maximum value along A, B and C directions.
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Use 5 for this calculation.
Note: use this card in conjunction with the FORM card.
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NMUL nmult, jhe, jke, jle
Reflections satisfy jhe*H + jke*K + jle*L = nmult*N are possible reflections, where N is any integer.
Default: NMUL 0, 0 ,0, 0
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PRTV PrtAve
PrtAve - average protein density value (default: 0.43 e/ų)
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RANG nalpha, nbeta, ngamma, drot, nx, ny, nz, dtrans
| nalpha | - number of search steps along Alpha |
| nbeta | - number of search steps along Beta |
| ngamma | - number of search steps along Gamma |
| drot | - stepsize for rotation in degrees |
| nx | - number of search steps along X |
| ny | - number of search steps along Y |
| nz | - number of search steps along Z |
| dtrans | - stepsize for translation in angstroms |
nx,ny,nz,dtrans are not used for convolution search.
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RESO rmin, rmax [, rext, rstp ]
| rmin | - minimum resolution |
| rmax | - maximum resolution |
| rext | - extended resolution (default: rext=rmax) |
| rstp | - number of steps needed for extension |
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The input can be in Eulerian angle, spherical polar or direction cosine. The translation must be in orthoganol system in Å.
| a) ROTR EULER | alpha, beta, gamma |
| tx, ty, tz |
alpha, beta, gamma are Eulerian angles in (Z Y Z) rotation. tx, ty and tz are the translational part.
| b) ROTR SPHER | omega, phi, kappa |
| tx, ty, tz |
omega, phi and kappa are spherical polar angles. omega is the angle with respect to Z axis. phi is the angle with respect to X axis on the XY plane. kappa is the rotation angle. tx,ty and tz are the translational part.
| c) ROTR DCOS | dcx, dcy, dcz, kappa |
| tx, ty, tz |
dcx,dcy and dcz are the direction cosine of the rotation axis with respect to X Y and Z. kappa is the rotation angle. tx,ty and tz are the translational part.
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RSCB rmin, rmax [,nbin]
| rmin | - minimum resolution |
| rmax | - maximum resolution |
| nbin | - number of bins in resolution range(ranges from 1-100. default: nbin=50) |
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SCAL K, B
F'obs = K * Fobs * EXP(-B * S)
where S = (SIN(theta)/lambda)**2
Default: SCAL 1.0 0.0
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SIGM sigma
Reflections with Fobs < sigma * sd(Fobs) will not be included in the calculation.
Default: SIGM 0.0
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SOLC SolvCont
SolvCont - solvent content in percentage
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SOLV SolAve
SolAve - average solvent density value (default: 0.32 e/ų)
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SPLL PhiLabel P FOMlabel W
Use in conjunction with function SPLICE. User provides Philabel and FOMlabel, character strings which assign names to the spliced sets of data. If splicing alone, LABI must define PHIO, PHIC, FOMO, FOMC. If splicing in conjunction with other SQUASH functions, the program will assign PHIC and FOMC.
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SYMM SpGrpNumber {SpGrpName} {symmetry operator}
| a) SpGrpNumber | - space group number |
| b) SpGrpName | - space group name in character |
| c) Symmetry operator | - has to be in Intl. Tab. format. |
| Each operator precedes with SYMM card and separated by comma or space. |
Default: SYMM 1
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TITL ctitle
ctitle - character string (maximum 80 characters) written to the header of HKLOUT
Default: TITL squash
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XYZL nxmin, nxmax, nymin, nymax, nzmin, nzmax
The parameters are the minimum and maximum value along A, B and C directions.
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Note: The keywords highlighted in magenta in the examples are keywords that are specific for the topic of that example.
#!/bin/sh name=wilson mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz HTMLBASE=$name set +a squash <<MY-DATA TITL 2ZN insulin MIR data, Wilson plot FUNC wils CELL 82.5 82.5 34.0 90 90 120 SYMM 146 GRID 128 128 54 RESO 1000 1.5 RSCB 4.0 1.5 50 CONT C 4662 N 1170 O 3861 S 108 H 11907 ZN 6 NA 6 NMUL 3 -1 1 1 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM END MY-DATA
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#!/bin/sh name=ncs_ncsr mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MASK=${name}.msk MASKAVE=INS_mola.msk MASKAVE2=INS_mola_b.msk HTMLBASE=$name set +a squash <<MY-DATA TITL Refining Non-crystallographic symmetry by least squares method FUNC ncsr MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 NMUL 3 -1 1 1 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=ncs_rsea mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MASKAVE=INS_mola.msk HTMLBASE=$name set +a squash <<MY-DATA TITL Refining Non-crystallographic symmetry by R-factor search method FUNC rsea MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM R3 RESO 1000.0 3.0 NCSG -33 43 -4 45 -31 30 RANG 7 7 7 2.0 5 5 5 1.0 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 NMUL 3 -1 1 1 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=ncs_pats mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MASKAVE=INS_mola.msk HTMLBASE=$name set +a squash <<MY-DATA TITL Refining NCS by convolution method FUNC pats MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 RANG 7 7 7 2.0 5 5 5 1.0 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.0 0.0 NMUL 3 -1 1 1 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=ncs_rsea_ncsr mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MASK=${name}.msk MASKAVE=INS_mola.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Refining NCS by R-factor search & LSQ algorithm FUNC rsea,ncsr MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 RANG 7 7 7 2.0 5 5 5 1.0 SYMM R3 RESO 1000.0 3.0 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.0 0.0 NMUL 3 -1 1 1 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=hm2d mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL 2ZN insulin MIR data, 2D h.m FUNC hm2d HMCT 2 AXIS Z X Y CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=F2D PHICOUT=PHI2D FOMCOUT=FOM2D END MY-DATA
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#!/bin/sh name=solv mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL 2ZN insulin MIR data, solvent flattening FUNC solv CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSF PHICOUT=PHISF FOMCOUT=FOMSF END MY-DATA
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#!/bin/sh name=solv_hm2d mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL 2Zn Insulin phase refn by histogram matching and solvent flattening FUNC solv,hm2d HMCT 2 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSF2D PHICOUT=PHISF2D FOMCOUT=FOMSF2D END MY-DATA
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#!/bin/sh name=aver_solv mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk MASKAVE2=Ins_mola_b.msk HTMLBASE=$name set +a squash<<MY-DATA TITL solvent flattening and averaging for phase refinement FUNC aver,solv MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.0 0.0 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase refn by hm2d, solv and Sayre's equation (diagonal) FUNC sayr, solv, hm2d HMCT 2 MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 3.0 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase refn by hm2d, solv and Sayre's equation (full matrix) FUNC sayr, solv, hm2d HMCT 2 MODE 1 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=hm2d_solv_aver mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase refn by hm2d, solv & averaging FUNC hm2d, solv, aver HMCT 2 MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.4 13.4 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d_aver mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk MASKAVE2=Ins_mola_b.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase refn using Sayre eqn, hm2d, solv & averaging FUNC sayr, hm2d, solv, aver MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.4 13.4 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=hm2d_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extension by histogram matching FUNC hm2d HMCT 2 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 1.5 4 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=F2DE PHICOUT=PHI2DE FOMCOUT=FOM2DE END MY-DATA
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#!/bin/sh name=solv_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extension by solvent flattening FUNC solv CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 1.5 4 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSFE PHICOUT=PHISFE FOMCOUT=FOMSFE END MY-DATA
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#!/bin/sh name=solv_hm2d_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn by solvent flattening & histogram matching FUNC hm2d, solv HMCT 2 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 1.5 4 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSF2DE PHICOUT=PHISF2DE FOMCOUT=FOMSF2DE END MY-DATA
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#!/bin/sh name=aver_solv_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk MASKAVE2=Ins_mola_b.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn by averaging & solvent flattening FUNC aver,solv MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 2.0 10 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.0 0.0 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn by solv, hm2d & Sayre's eqn (diagonal) FUNC sayr, solv, hm2d MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 1.5 4 SCAL 1.4 13.4 SOLC 0.30 NMUL 3 -1 1 1 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn by solv, hm2d & Sayre's eqn (diagonal) FUNC sayr, solv, hm2d MODE 1 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 SYMM 146 RESO 1000 1.9 1.5 4 SCAL 1.4 13.4 NMUL 3 -1 1 1 HKLW 1 10.0 SOLC 0.30 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=hm2d_solv_aver mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn by hm2d, solv & averaging FUNC hm2d, solv, aver MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 2.0 10 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.4 13.4 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d_aver_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk MASKAVE2=Ins_mola_b.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn using Sayre eqn, hm2d, solv & averaging FUNC sayr, hm2d, solv, aver MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 2.0 10 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.4 13.4 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d_aver_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPIN=zniso30a.map MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk MASKAVE2=Ins_mola_b.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn by Sayre's eqn.,hm2d, solv & averaging FUNC sayr, hm2d, solv, aver MODE 2 3 1 CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 2.0 10 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.4 13.4 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=sayr_solv_hm2d_aver_ext mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MAPOUT=${name}.map MASK=${name}.msk MASKAVE=Ins_mola.msk MASKAVE2=Ins_mola_b.msk HTMLBASE=$name set +a squash<<MY-DATA TITL Phase extn by Sayre's eqn.,hm2d,solv &averaging FUNC sayr, hm2d, solv, aver MODE 2 3 1 AXIS Y X Z CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 NCSG -33 43 -4 45 -31 30 SYMM R3 RESO 1000.0 3.0 2.0 10 ROTR EULER 0.0 179.6 331.5 0.007 -0.166 -0.432 SCAL 1.0 0.0 NMUL 3 -1 1 1 SOLC 0.30 HKLW 1 10.0 LABI FO=FP SIGFO=SDFP PHIO=AISOB FOMO=FOM FC=FP SFC=SDFP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 END MY-DATA
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#!/bin/sh name=hm2d_splice mtz=zn215asharp134e.mtz # set -a SYMOP=${CLIB}/data/symop.lib HKLIN=$mtz HKLOUT=${name}.mtz MASK=${name}.msk HTMLBASE=$name set +a squash<<MY-DATA TITL 2D h.m. and splice the input and extended phases FUNC hm2d, spli CELL 82.5 82.5 34 90 90 120 GRID 128 128 54 RESO 1000 1.9 1.8 1 SYMM 146 SOLC 0.30 NMUL 3 -1 1 1 LABI FO=FP PHIO=AISOB FOMO=FOM FC=FP PHIC=AISOB FOMC=FOM LABO FCOUT=FSQ99 PHICOUT=PHISQ99 FOMCOUT=FOMSQ99 SPLL PHISPL P FOMSPL W END MY-DATA
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#!/bin/sh name=atsf pdb=z19fin.pdb # set -a SYMOP=${CLIB}/data/symop.lib XYZIN=$pdb MAPOUT=${name}.map HKLOUT=${name}.mtz HTMLBASE=$name set +a squash<<MY-DATA TITL calculate F from pdb FUNC atsf CELL 82.5 82.5 34.0 90 90 120 SYMM 146 SOLC 0.30 NGAU 5 GRID 128 128 54 RESO 1000.0 1.5 HKLW 1 10.0 LABO FCOUT=FCOUT PHICOUT=PHICOUT END MY-DATA
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