Gemmi program

The library comes with a command-line program which is also named gemmi; running a program is easier than calling a library function.

This program is actually a set of small programs, each of them corresponding to a subcommand:

$ gemmi -h
gemmi 0.4.0
Command-line utility that accompanies the GEMMI library,
which is a joint project of CCP4 and Global Phasing Ltd.
Licence: Mozilla Public License 2.0.
Copyright 2017-2020 Global Phasing Ltd.
https://github.com/project-gemmi/gemmi

Usage: gemmi [--version] [--help] <command> [<args>]

Commands:
 align         sequence alignment (global, pairwise, affine gap penalty)
 blobs         list unmodelled electron density blobs
 cif2mtz       convert structure factor mmCIF to MTZ
 cif2json      translate (mm)CIF to (mm)JSON
 contact       searches for contacts (neighbouring atoms)
 contents      info about content of a coordinate file (pdb, mmCIF, ...)
 convert       convert file (CIF - JSON, mmCIF - PDB) or modify structure
 fprime        calculate anomalous scattering factors f' and f"
 grep          search for tags in CIF file(s)
 h             add or remove hydrogen atoms
 json2cif      translate mmJSON to mmCIF
 map           print info or modify a CCP4 map
 map2sf        transform CCP4 map to map coefficients (in MTZ or mmCIF)
 mask          make mask in the CCP4 format
 mondiff       compare two monomer CIF files
 mtz           print info about MTZ reflection file
 mtz2cif       convert MTZ to structure factor mmCIF
 reindex       reindex MTZ file
 residues      list residues from a coordinate file
 rmsz          validate geometry using monomer library
 sf2map        transform map coefficients (from MTZ or mmCIF) to map
 sfcalc        calculate structure factors from a model
 sg            info about space groups
 tags          list tags from CIF file(s)
 validate      validate CIF 1.1 syntax
 wcn           calculate local density / contact numbers (WCN, CN, ACN, LDM)

validate

A CIF validator. Apart from checking the syntax it can check most of the rules imposed by DDL1 and DDL2 dictionaries.

$ gemmi validate -h
Usage: gemmi validate [options] FILE [...]

Options:
  -h, --help      Print usage and exit.
  -V, --version   Print version and exit.
  -v, --verbose   Verbose output.
  -q, --quiet     Show only errors.
  -f, --fast      Syntax-only check.
  -s, --stat      Show token statistics
  -d, --ddl=PATH  DDL for validation.
  -m, --monomer   Extra checks for Refmac dictionary files.

grep

Searches for a specified tag in CIF files and prints the associated values, one value per line:

$ gemmi grep _refine.ls_R_factor_R_free 5fyi.cif.gz
5FYI:0.2358
$ gemmi grep _refine.ls_R_factor_R_free mmCIF/mo/?moo.cif.gz
1MOO:0.177
3MOO:0.21283
4MOO:0.22371
5MOO:0.1596
5MOO:0.1848
$ gemmi grep -b _software.name 5fyi.cif.gz
DIMPLE
PHENIX

Some of the command-line options correspond to the options of GNU grep (-c, -l, -H, -n). As with other utilities, option --help shows the usage:

$ gemmi grep -h
Usage: gemmi grep [options] TAG FILE_OR_DIR_OR_PDBID[...]
       gemmi grep -f FILE [options] TAG
Search for TAG in CIF files.
By default, recursive directory search checks only *.cif(.gz) files.
To change it, specify --name=* or --name=*.hkl.

Options:
  -h, --help               display this help and exit
  -V, --version            display version information and exit
  -f, --file=FILE          obtain file (or PDB ID) list from FILE
  --name=PATTERN           filename glob pattern used in recursive grep; by
                           default, *.cif and *.cif.gz files are searched
  -m, --max-count=NUM      print max NUM values per file
  -O, --one-block          optimize assuming one block per file
  -a, --and=tag            Append delimiter (default ';') and the tag value
  -d, --delimiter=DELIM    CSV-like output with specified delimiter
  -n, --line-number        print line number with output lines
  -H, --with-filename      print the file name for each match
  -b, --no-blockname       suppress the block name on output
  -t, --with-tag           print the tag name for each match
  -l, --files-with-tag     print only names of files with the tag
  -L, --files-without-tag  print only names of files without the tag
  -c, --count              print only a count of values per block or file
  -r, --recursive          ignored (directories are always recursed)
  -w, --raw                include '?', '.', and string quotes
  -s, --summarize          display joint statistics for all files

This is a minimalistic program designed to be used together with Unix text-processing utilities. For example, it cannot filter values itself, but one may use grep:

$ gemmi grep _pdbx_database_related.db_name /pdb/mmCIF/aa/* | grep EMDB
4AAS:EMDB
5AA0:EMDB

Gemmi-grep tries to be simple to use like Unix grep, but at the same time it is aware of the CIF syntax rules. In particular, gemmi grep _one will give the same output for both _one 1 and loop_ _one _two 1 2. This is helpful in surprising corner cases. For example, when a PDB entry has two Rfree values (see the 5MOO example above).

Gemmi-grep does not support regular expression, only globbing (wildcards): ? represents any single character, * represents any number of characters (including zero). When using wildcards you may also want to use the -t option which prints the tag:

$ gemmi grep -t _*free 3gem.cif
3GEM:[_refine.ls_R_factor_R_free] 0.182
3GEM:[_refine.ls_percent_reflns_R_free] 5.000
3GEM:[_refine.ls_number_reflns_R_free] 3951
3GEM:[_refine.correlation_coeff_Fo_to_Fc_free] 0.952
3GEM:[_refine_ls_shell.R_factor_R_free] 0.272
3GEM:[_refine_ls_shell.number_reflns_R_free] 253

Let say we want to find extreme unit cell angles in the PDB. _cell.angle_*a will match _cell.angle_alpha as well as beta and gamma, but not _cell.angle_alpha_esd etc.

$ gemmi grep -d' ' _cell.angle_*a /pdb/mmCIF/ | awk '$2 < 50 || $2 > 140 { print $0; }'
4AL2 144.28
2EX3 45.40
2GMV 145.09
4NX1 140.060
4OVP 140.070
1SPG 141.90
2W1I 146.58

The option -O is used to make gemmi-grep faster. With this option the program finds only the first occurence of the tag in file. Note that if the file has only one block (like mmCIF coordinate files) and the tag is specified without wildcards then we cannot have more than one match anyway.

Searching the whole compressed mmCIF archive from the PDB (35GB of gzipped files) should take on an average computer between 10 and 30 minutes, depending where the searched tag is located. This is much faster than with other CIF parsers (to my best knowledge) and it makes the program useful for ad-hoc PDB statistics:

$ gemmi grep -O -b _entity_poly.type /pdb/mmCIF | sort | uniq -c
      1 cyclic-pseudo-peptide
      4 other
      2 peptide nucleic acid
   9905 polydeoxyribonucleotide
    156 polydeoxyribonucleotide/polyribonucleotide hybrid
     57 polypeptide(D)
 168923 polypeptide(L)
   4559 polyribonucleotide
     18 polysaccharide(D)

Option -c counts the values in each block or file. As an example we may check which entries have the biggest variety of chemical components (spoiler: ribosomes):

$ gemmi grep -O -c _chem_comp.id /pdb/mmCIF | sort -t: -k2 -nr | head
5J91:58
5J8A:58
5J7L:58
5J5B:58
4YBB:58
5JC9:57
5J88:57
5IT8:57
5IQR:50
5AFI:50

Going back to moo, we may want to know to what experimental method the Rfree values correspond:

$ gemmi grep _refine.ls_R_factor_R_free -a _refine.pdbx_refine_id mmCIF/mo/?moo.cif.gz
1MOO:0.177;X-RAY DIFFRACTION
3MOO:0.21283;X-RAY DIFFRACTION
4MOO:0.22371;X-RAY DIFFRACTION
5MOO:0.1596;X-RAY DIFFRACTION
5MOO:0.1848;NEUTRON DIFFRACTION

Option -a (--and) can be specified many times. If we would add -a _pdbx_database_status.recvd_initial_deposition_date we would get the deposition date in each line. In this case it would be repeated for 5MOO:

5MOO:0.1596;X-RAY DIFFRACTION;2016-12-14
5MOO:0.1848;NEUTRON DIFFRACTION;2016-12-14

To output TSV (tab-separated values) add --delimiter='\t'. What are the heaviest chains?

$ gemmi grep --delimiter='\t' _entity.formula_weight -a _entity.pdbx_description /hdd/mmCIF/ | sort -nrk2 | head -3
6EK0    1641906.750     28S ribosomal RNA
5T2C    1640238.125     28S rRNA
5LKS    1640238.125     28S ribosomal RNA

With some further processing the option -a can be used to generate quite sophisticated reports. Here is a little demo: https://project-gemmi.github.io/pdb-stats/

The major limitation here is that gemmi-grep cannot match corresponding values from different tables (it is not possible on the syntax level). In the example above we have two values from the same table (_refine) and a deposition date (single value). This works well. But we are not able to add corresponding wavelengths from _diffrn_source. If an extra tag (specified with -a) is not in the same table as the main tag, gemmi-grep uses only the first value for this tag.

Unless we just count the number of value. Counting works for any combination of tags:

$ gemmi grep -c _refln.intensity_meas -a _diffrn_refln.intensity_net r5paysf.ent.gz
r5paysf:63611;0
r5payAsf:0;356684

(The file used in this example is structure factor (SF) mmCIF. Strangely these files in the PDB have extension ent not cif.)

The first number in the output above is the number of specified intensities. If you would like to count in also values ? and . specify the option --raw:

$ gemmi grep --raw -c _refln.intensity_meas r5paysf.ent.gz
r5paysf:63954
r5payAsf:0

Gemmi-grep can work with any CIF files but it has one feature specific to the PDB data. When $PDB_DIR is set one may use PDB codes: just 5moo or 5MOO instead of the path to 5moo.cif.gz. And for convenience, using a PDB code implies option -O.

The file paths or PDB codes can be read from a file. For example, if we want to analyse PDB data deposited in 2016 we may first make a file that lists all such files:

$ gemmi grep -H -O _pdbx_database_status.recvd_initial_deposition_date $PDB_DIR/structures/divided/mmCIF | \
        grep 2016 >year2016.txt

The 2016.txt file file has lines that start with the filename:

/hdd/structures/divided/mmCIF/ww/5ww9.cif.gz:5WW9:2016-12-31
/hdd/structures/divided/mmCIF/ww/5wwc.cif.gz:5WWC:2016-12-31

and a command such as:

$ gemmi grep -f year2016.out _diffrn.ambient_temp

will grep only the listed cif files.

Exit status of gemmi-grep has the same meaning as in GNU grep: 0 if a line is selected, 1 if no lines were selected, and 2 if an error occurred.

Examples

comp_id check

The monomer library (Refmac dictionary) has tags such as _chem_comp_atom.comp_id, _chem_comp_bond.comp_id that are expected to be consistent with the block name:

$ gemmi grep _*.comp_id $CLIBD_MON/a/ASN.cif
comp_ASN:ASN
[repeated 106 times]

We can quickly check if the names are always consistent by filtering the output above with awk, for all monomer files, to print only lines where the block name and comp_id differ:

$ gemmi grep _*.comp_id $CLIBD_MON/? | awk -F: 'substr($1, 6) != $2'
comp_M43:N09
...

planarity

The monomer library includes planarity restraints. Each row in the _chem_comp_plane_atom table with the same plane_id represents atom belonging to the same plane. What is the maximum number of atoms in one plane?

$ gemmi grep _chem_comp_plane_atom.plane_id $CLIBD_MON/? | uniq -c | sort -nr | head -3
 38 comp_LG8:plan-1
 36 comp_UCM:plan-1
 36 comp_SA3:plan-1

cif2json

Syntax-level conversion from CIF 1.1 to JSON. The JSON representation of the CIF data can be customized. In particular we support CIF-JSON standard from COMCIFS and mmJSON standard from PDBj (the latter is specific to mmCIF files).

$ gemmi cif2json -h
Usage:
 gemmi cif2json [options] INPUT_FILE OUTPUT_FILE

Convert CIF file (any CIF files, including mmCIF) to JSON.
The output can be COMCIFS CIF-JSON (-c), mmJSON (-m),
or a custom JSON flavor (default).

General options:
  -h, --help             Print usage and exit.
  -V, --version          Print version and exit.
  -v, --verbose          Verbose output.

JSON output options:
  -c, --comcifs          Conform to the COMCIFS CIF-JSON standard draft.
  -m, --mmjson           Compatible with mmJSON from PDBj.
  --bare-tags            Output tags without the first underscore.
  --numb=quote|nosu|mix  Convert the CIF numb type to one of:
                           quote - string in quotes,
                           nosu - number without s.u.,
                           mix (default) - quote only numbs with s.u.
  --dot=STRING           JSON representation of CIF's '.' (default: null).

Modifications:
  --skip-category=CAT    Do not output tags starting with _CAT
  --sort                 Sort tags in alphabetical order.

When output file is -, write to standard output.

The major difference between the two is that CIF-JSON is dictionary-agnostic: it cannot recognize categories (mmJSON groups by categories), and it cannot recognize numbers (so it quotes the numbers). CIF-JSON adds also two extra objects: “CIF-JSON” and “Metadata”. The minor differences are:

CIF CIF-JSON mmJSON
data_a a data_a
_tag _tag tag
_CasE _case CasE
. false null
? null null

json2cif

The opposite of cif2json, but currently the only supported input is mmJSON.

$ gemmi json2cif -h
Usage:
 gemmi json2cif [options] INPUT_FILE OUTPUT_FILE

Convert mmJSON to mmCIF.

Options:
  -h, --help           Print usage and exit.
  -V, --version        Print version and exit.
  -v, --verbose        Verbose output.
  --pdbx-style         Similar styling (formatting) as in wwPDB.
  --cif2cif            Read CIF not JSON.
  --skip-category=CAT  Do not output tags starting with _CAT
  --sort               Sort tags in alphabetical order.

When output file is -, write to standard output.

convert

Conversion between macromolecular coordinate formats: PDB, mmCIF and mmJSON.

$ gemmi convert -h
Usage:
 gemmi convert [options] INPUT_FILE OUTPUT_FILE

with possible conversions between PDB, mmCIF and mmJSON.
FORMAT can be specified as one of: mmcif, mmjson, pdb, ccd (read-only).
ccd = coordinates of a chemical component from CCD or monomer library.

General options:
  -h, --help              Print usage and exit.
  -V, --version           Print version and exit.
  -v, --verbose           Verbose output.
  --from=FORMAT           Input format (default: from the file extension).
  --to=FORMAT             Output format (default: from the file extension).

CIF output options:
  --pdbx-style            Similar styling (formatting) as in wwPDB.
  -b NAME, --block=NAME   Set block name and default _entry.id
  --sort                  Sort tags in alphabetical order.
  --skip-category=CAT     Do not output tags starting with _CAT

PDB input options:
  --segment-as-chain      Append segment id to label_asym_id (chain name).
  --old-pdb               Read only the first 72 characters in line.

PDB output options:
  --short-ter             Write PDB TER records without numbers (iotbx compat.).
  --linkr                 Write LINKR record (for Refmac) if link_id is known.

Any output options:
  --minimal               Write only the most essential records.
  --shorten               Shorten chain names to 1 (if # < 63) or 2 characters.
  --rename-chain=OLD:NEW  Rename chain OLD to NEW (--rename-chain=:A adds
                          missing chain IDs).

Macromolecular operations:
  --expand-ncs=dup|new    Expand strict NCS specified in MTRIXn or equivalent.
                          New chain names are the same or have added numbers.
  --assembly=ID           Output bioassembly with given ID (1, 2, ...).
  --remove-h              Remove hydrogens.
  --remove-waters         Remove waters.
  --remove-lig-wat        Remove ligands and waters.
  --trim-to-ala           Trim aminoacids to alanine.

When output file is -, write to standard output.

The PDB records written by Gemmi are formatted in the same way as in the wwPDB. This makes possible to use diff to compare a PDB file from wwPDB and a file converted by Gemmi from mmCIF. The file from wwPDB will have more records, but the diff should still be readable.

The option --expand-ncs expands strict NCS, defined in the MTRIX record (PDB) or in the _struct_ncs_oper table (mmCIF). It is not obvious how to name the new chains that are added. We have two options: either new names are generated (=new) or the chain names are not changed but distinct segment IDs are added (=dup).

tags

Lists tags from one or multiple CIF files together with some statistics.

$ gemmi tags -h
Usage:
 gemmi tags [options] FILE_OR_DIR[...]
List CIF tags with counts of blocks and values.
  -h, --help     Print usage and exit.
  -V, --version  Print version and exit.
  --count-files  Count files instead of blocks.
  --glob=GLOB    Process files matching glob pattern.

Options for making https://project-gemmi.github.io/pdb-stats/tags.html
  --full         Gather data for tags.html
  --entries-idx  Use entries.idx to read more recent entries first.
  --sf           (for use with --entries-idx) Read SF mmCIF files.

By default, the tag statistics show in how many blocks the tag is present, and the total number of non-null values for the tag:

$ gemmi tags components.cif.gz
tag   block-count     value-count
_chem_comp.formula    29748   29748
_chem_comp.formula_weight     29749   29749
...
_pdbx_chem_comp_identifier.type       29338   52899
Tag count: 67
Block count: 29749
File count: 1

This program is run with option --full on the whole PDB archive to produce data for pdb-stats/tags.html.

map

Shows a summary of a CCP4 map file, optionally performing simple transformations.

$ gemmi map -h
Usage:
 gemmi map [options] CCP4_MAP[...]

  -h, --help         Print usage and exit.
  -V, --version      Print version and exit.
  -v, --verbose      Verbose output.
  --deltas           Statistics of dx, dy and dz.
  --check-symmetry   Compare the values of symmetric points.
  --write-xyz=FILE   Write transposed map with fast X axis and slow Z.
  --write-full=FILE  Write map extended to cover whole unit cell.

mask

Makes a mask in the CCP4 format. It has two functions:

  • masking atoms if the input file is a coordinate file,
  • using a threshold to convert a CCP4 map file to a mask file.
$ gemmi mask -h
Usage:
 gemmi mask [options] INPUT output.msk

Makes a mask in the CCP4 format.
If INPUT is a CCP4 map the mask is created by thresholding the map.
If INPUT is a coordinate file (mmCIF, PDB, etc) the atoms are masked.
  -h, --help           Print usage and exit.
  -V, --version        Print version and exit.
  -v, --verbose        Verbose output.
  --from=coor|map      Input type (default: from file extension).

Options for making a mask from a map:
  -t, --threshold      The density cutoff value.
  -f, --fraction       The volume fraction to be above the threshold.

Options for masking a model:
  -s, --spacing=D      Max. sampling for the grid (default: 1A).
  -g, --grid=NX,NY,NZ  Grid sampling.
  -r, --radius         Radius of atom spheres (default: 3.0A).

mtz

$ gemmi mtz -h
Usage:
 gemmi mtz [options] MTZ_FILE[...]
Print informations from an mtz file.
  -h, --help       Print usage and exit.
  -V, --version    Print version and exit.
  -v, --verbose    Verbose output.
  -H, --headers    Print raw headers, until the END record.
  -d, --dump       Print a subset of CCP4 mtzdmp informations.
  -B N, --batch=N  Print data from batch header N.
  -b, --batches    Print data from all batch headers.
  --tsv            Print all the data as tab-separated values.
  -s, --stats      Print column statistics (completeness, mean, etc).
  --check-asu      Check if reflections are in conventional ASU.
  --toggle-endian  Toggle assumed endiannes (little <-> big).
  --no-isym        Do not apply symmetry from M/ISYM column.
  --update-reso    Recalculate resolution limits before printing.

mtz2cif

Converts reflection data from MTZ to mmCIF.

$ gemmi mtz2cif -h
Usage:
  gemmi mtz2cif [options] MTZ_FILE CIF_FILE
Options:
  -h, --help             Print usage and exit.
  -V, --version          Print version and exit.
  -v, --verbose          Verbose output.
  --spec=FILE            Column and format specification.
  --print-spec           Print default spec and exit.
  -b NAME, --block=NAME  mmCIF block name: data_NAME (default: mtz).
  --skip-empty[=COLS]    Skip reflections with no values. If COLS are given, eg.
                         'I(+),I(-)', only values in those columns are checked.
  --no-comments          Do not write comments in the mmCIF file.
  --wavelength=LAMBDA    Set wavelengths (default: from input file).
  --trim=N               (for testing) output only reflections -N <= h,k,l <=N.

If CIF_FILE is -, the output is printed to stdout.
If spec is -, it is read from stdin.

Lines in the spec file have format:
  [FLAG] COLUMN TYPE TAG [FORMAT]
for example:
  SIGF_native * SIGF_meas_au 12.5e
  FREE I pdbx_r_free_flag 3.0f
FLAG (optional) is either ? or &:
  ? = ignored if no column in the MTZ file has this name.
  & = ignored if the previous line was ignored.
  Example:
      ? I    J intensity_meas
      & SIGI Q intensity_sigma
COLUMN is MTZ column label. Columns H K L are added if not specified.
  Alternative labels can be separated with | (e.g. FREE|FreeR_flag).
TYPE is used for checking the columm type, unless it is '*'.
TAG does not include category name, it is only the part after _refln.
FORMAT (optional) is printf-like floating-point format:
 - one of e, f, g with optional flag, width and precision
 - flag is one of + - # _; '_' stands for ' ', for example '_.4f'
 - since all numbers in MTZ are stored as float, the integer columns use
   the same format as float. The format of _refln.status is ignored.

cif2mtz

Converts reflection data from mmCIF to MTZ.

$ gemmi cif2mtz -h
Usage:
  gemmi cif2mtz [options] CIF_FILE MTZ_FILE
  gemmi cif2mtz [options] CIF_FILE --dir=DIRECTORY
Options:
  -h, --help               Print usage and exit.
  -V, --version            Print version and exit.
  -v, --verbose            Verbose output.
  -b NAME, --block=NAME    mmCIF block to convert.
  -d DIR, --dir=NAME       Output directory.
  --title                  MTZ title.
  -H LINE, --history=LINE  Add a history line.
  -u, --unmerged           Write unmerged MTZ file(s).

First variant: converts the first block of CIF_FILE, or the block
specified with --block=NAME, to MTZ file with given name.

Second variant: converts each block of CIF_FILE to one MTZ file
(block-name.mtz) in the specified DIRECTORY.

If CIF_FILE is -, the input is read from stdin.

sf2map

Transforms map coefficients from either MTZ or SF mmCIF to CCP4 map.

$ gemmi sf2map -h
Usage:
  gemmi sf2map [options] INPUT_FILE MAP_FILE

INPUT_FILE must be either MTZ or mmCIF with map coefficients.

By default, the program searches for 2mFo-DFc map coefficients in:
  - MTZ columns FWT/PHWT or 2FOFCWT/PH2FOFCWT,
  - mmCIF tags _refln.pdbx_FWT/pdbx_PHWT.
If option "-d" is given, mFo-DFc map coefficients are searched in:
  - MTZ columns DELFWT/PHDELWT or FOFCWT/PHFOFCWT,
  - mmCIF tags _refln.pdbx_DELFWT/pdbx_DELPHWT.


Options:
  -h, --help           Print usage and exit.
  -V, --version        Print version and exit.
  -v, --verbose        Verbose output.
  -d, --diff           Use difference map coefficients.
  --section=NAME       MTZ dataset name or CIF block name
  -f COLUMN            F column (MTZ label or mmCIF tag).
  -p COLUMN            Phase column (MTZ label or mmCIF tag).
  --weight=COLUMN      (normally not needed) weighting for F.
  -g, --grid=NX,NY,NZ  Grid size (user-specified minimum).
  --exact              Use the exact grid size specified by --grid.
  -s, --sample=NUMBER  Set spacing to d_min/NUMBER (3 is usual).
  --zyx                Output axes Z Y X as fast, medium, slow (default is X Y
                       Z).
  -G                   Print size of the grid that would be used and exit.
  --timing             Print calculation times.
  --normalize          Scale the map to standard deviation 1 and mean 0.

The --sample option is named after the GRID SAMPLE keyword of the venerable CCP4 FFT program; its value has the same meaning.

map2sf

Transforms CCP4 map into map coefficients.

$ gemmi map2sf -h
Usage:
  gemmi map2sf [options] MAP_FILE OUTPUT_FILE COL_F COL_PH

Writes map coefficients (amplitude and phase) of a map to OUTPUT_FILE.
The output is MTZ if it has mtz extension, otherwise it is mmCIF.

Options:
  -h, --help       Print usage and exit.
  -V, --version    Print version and exit.
  -v, --verbose    Verbose output.
  -b, --base=PATH  Add new columns to the data from this file.
  --section=NAME   Add new columns to this MTZ dataset or CIF block.
  --dmin=D_MIN     Resolution limit.
  --ftype=TYPE     MTZ amplitude column type (default: F).
  --phitype=TYPE   MTZ phase column type (default: P).

sfcalc

Calculates structure factors from a model.

$ gemmi sfcalc -h
Usage:
  gemmi sfcalc [options] INPUT_FILE

Calculates structure factors of a model (PDB, mmCIF or SMX CIF file).

Uses FFT to calculate all reflections up to requested resolution for MX
files. Otherwise, for SMX and --hkl, F's are calculated directly.
This program can also compare F's calculated directly with values
calculated through FFT or with values read from a reflection file.

Options:
  -h, --help        Print usage and exit.
  -V, --version     Print version and exit.
  -v, --verbose     Verbose output.
  --hkl=H,K,L       Calculate structure factor F_hkl.
  --dmin=NUM        Calculate structure factors up to given resolution.
  --ciffp           Read f' from _atom_type_scat_dispersion_real in CIF.
  --wavelength=NUM  Wavelength [A] for calculation of f' (use --wavelength=0 or
                    -w0 to ignore anomalous scattering).
  --unknown=SYMBOL  Use form factor of SYMBOL for unknown atoms.
  --noaniso         Ignore anisotropic ADPs.

Options for FFT-based calculations:
  --rate=NUM        Shannon rate used for grid spacing (default: 1.5).
  --blur=NUM        B added for Gaussian blurring (default: auto).
  --rcut=Y          Use atomic radius r such that rho(r) < Y (default: 5e-5).
  --test[=CACHE]    Calculate exact values and report differences (slow).

Options for comparing calculated values with values from a file:
  --check=FILE      Re-calculate Fcalc and report differences.
  --f=LABEL         MTZ column label (default: FC) or small molecule cif tag
                    (default: F_calc or F_squared_calc).
  --phi=LABEL       MTZ column label (default: PHIC)
  --scale=S         Multiply calculated F by sqrt(S) (default: 1).

In general, structure factors can be calculated

  • either directly, by summing contributions from each atom to each reflection,
  • or by calculating an electron density on a grid and using discrete Fourier transform.

This program can measure the errors resulting from the latter method (in addition to its main function – calculation of the structure factors). The errors depend on

  • the grid spacing – controlled by the oversampling --rate=R; the maximum spacing is dmin/2R,
  • atomic radius – we neglect electron density of the atom beyond this radius; only density contributions above the (absolute) value specified with --rcut are taken into account,
  • Gaussian dampening (blurring) factor – artificial temperature factor Bextra added to all atomic B-factors (the structure factors are later corrected to cancel it out); either specified with --blur or picked automatically.

Choosing these parameters is a trade-off between efficiency and accuracy. Bextra is the most interesting one. It is discussed in the ITfC vol B, chapter 1.3 by G. Bricogne, section 1.3.4.4.5, and further in papers by J. Navaza (2002) and by P. Afonine and A. Urzhumtsev (2003). Still, I have not found a practical recipe how to pick a good value. Increasing the dampening makes the computations slower (because it increases atomic radius), while the value of Bextra that gives the most accurate results depends on the resolution, oversampling, atomic radius cut-off, and on the distribution of B-factors (normally, only the minimal B-factor in the model is considered).

The option --test can be used to see how accuracy and efficiency depends on the choice of parameters. For example, this shell script performs a series of calculations with differing Bextra:

model=1mru.pdb
dmin=2.5
gemmi sfcalc --dmin=$dmin --test $model >cache.tsv
for i in `seq -20 5 20`; do
    printf -- "$i\t" >&2
    gemmi sfcalc --dmin=$dmin --rate=1.5 --rcut=1e-4 --blur=$i --test=cache.tsv $model
done >/dev/null

Running it prints:

-20   RMSE=0.93304  0.5495%  max|dF|=38.80  R=0.301%   0.27671s
-15   RMSE=0.37007  0.2179%  max|dF|=41.26  R=0.094%   0.28366s
-10   RMSE=0.27075  0.1595%  max|dF|=44.35  R=0.041%   0.29322s
-5    RMSE=0.27228  0.1604%  max|dF|=47.59  R=0.029%   0.30459s
0     RMSE=0.28903  0.1702%  max|dF|=50.95  R=0.029%   0.31399s
5     RMSE=0.30806  0.1814%  max|dF|=54.35  R=0.032%   0.32527s
10    RMSE=0.32847  0.1934%  max|dF|=57.92  R=0.036%   0.33360s
15    RMSE=0.35028  0.2063%  max|dF|=61.66  R=0.041%   0.34181s
20    RMSE=0.37283  0.2196%  max|dF|=65.44  R=0.047%   0.35380s

The error used in RMSE is the magnitude of the difference of two vectors: |Fapprox – Fexact|. The next column is RMSE normalized by the sum of |Fcalc|. Then we have maximum error for a single reflection, and the wall time of computations. We can see that in this case negative “dampening” (subtracting about 10A2 from all B-factors) improves both accuracy and performance.

fprime

Calculate anomalous scattering factors (f’ and f”). Uses Cromer-Libermann algorithm with corrections from Kissel and Pratt. This and different approaches are discussed in the documentation of the underlying functions.

$ gemmi fprime -h
Usage:
 gemmi fprime [options] ELEMENT[...]
Prints anomalous scattering factors f' and f".

Options:
  -h, --help               Print usage and exit.
  -V, --version            Print version and exit.
  -e, --energy=ENERGY      Energy [eV]
  -w, --wavelength=LAMBDA  Wavelength [A]

Here is an example how to print f’ and f” using gemmi, XrayDB, CCP4 crossec and cctbx (pyFprime is not included because it is a GUI-only program). The Chantler’s data from XrayDB is probably the most reliable one:

$ gemmi fprime --wavelength=1.2 Se
Element  E[eV]  Wavelength[A]      f'             f"
Se      10332.0  1.2             -1.4186        0.72389

$ python3 -c "import xraydb; print(xraydb.f1_chantler('Se', 10332.0), xraydb.f2_chantler('Se', 10332.0))"
-1.4202028957329489 0.7100533627953146

$ echo -e "atom SE\n cwav 1 1.2 0\n END" | crossec | grep ^SE
SE          1.2000    -1.5173     0.7240

$ cctbx.eltbx.show_fp_fdp --wavelength=1.2 --elements=Se
Wavelength: 1.2 Angstrom

Element: Se
  Henke et al.  : f'=-1.44568 , f''=0.757958
  Sasaki et al. : f'=-1.5104  , f''=0.724000
  diff f''=-2.29 %

reindex

Reindex reflections in MTZ file.

$ gemmi reindex -h
Usage:
  gemmi reindex [options] INPUT_MTZ OUTPUT_MTZ
Options:
  -h, --help     Print usage and exit.
  -V, --version  Print version and exit.
  -v, --verbose  Verbose output.
  --hkl=OP       Reindexing transform as triplet (e.g. k,h,-l).
  --no-history   Do not add 'Reindexed with...' line to mtz HISTORY

Input file can be gzipped.

residues

List residues from a coordinate file, one per line.

$ gemmi residues -h
Usage:
 gemmi residues [options] INPUT[...]
Prints one residue per line, with atom names.
  -h, --help          Print usage and exit.
  -V, --version       Print version and exit.
  --format=FORMAT     Input format (default: from the file extension).
  -mSEL, --match=SEL  Print residues/atoms matching the selection.
  -l, --label         Print 'label' chain ID and seq ID in brackets.
INPUT is a coordinate file (mmCIF, PDB, etc).
The selection SEL has MMDB syntax:
/mdl/chn/s1.i1(res)-s2.i2/at[el]:aloc (all fields are optional)

Example:

$ gemmi residues -m '/3/*/(CYS,CSD)' 4pth.pdb
Model 3
A   85  CYS: N CA C O CB SG H HA HB2 HB3 HG
A  152  CSD: N CA CB SG C O OD1 OD2 HA HB2 HB3

align

Sequence alignment (global, pairwise, affine gap penalty). Used primarily for aligning the residues in the model’s chains to the full sequence from the SEQRES record.

$ gemmi align -h
Pairwise sequence alignment with scoring matrix and affine gap penalty.

Usage:

gemmi align [options] FILE[...]
    Aligns sequence from the model to the full sequence (SEQRES).
    Both are from the same FILE - either in the PDB or mmCIF format.
    If the mmCIF format is used, option --check-mmcif can be used.

gemmi align [options] --query=CHAIN1 --target=CHAIN2 FILE1 FILE2
    Aligns CHAIN1 from FILE1 to CHAIN2 from FILE2.
    By default, the sequence of residues in the model is used.
    To use SEQRES prepend '+' to the chain name (e.g. --query=+A).

gemmi align [options] --text-align STRING1 STRING2
    Aligns two ASCII strings (used for testing).

Options:
  -h, --help         Print usage and exit.
  -V, --version      Print version and exit.
  --check-mmcif      checks alignment agains _atom_site.label_seq_id
  --query=[+]CHAIN   Align CHAIN from file INPUT1.
  --target=[+]CHAIN  Align CHAIN from file INPUT2.
  --text-align       Align characters in two strings (for testing).

Scoring (absolute values):
  --match=INT        Match score (default: 1).
  --mism=INT         Mismatch penalty (default: -1).
  --gapo=INT         Gap opening penalty (default: -1).
  --gape=INT         Gap extension penalty (default: -1).

Output options:
  -p                 Print formatted alignment with one-letter codes.
  -v, --verbose      Verbose output.

For the testing purpose, it can align text strings. For example, the Levenshtein distance can be calculated by setting the gap opening penalty to zero:

$ gemmi align -p --match=0 --gapo=0 --text-align Saturday Sunday
Score: -3   CIGAR: 1M2I5M
Saturday
|  |.|||
S--unday

This tool uses modified code from ksw2. See the Sequence alignment section for more details.

sg

Prints information about given space group.

$ gemmi sg -h
Usage:
 gemmi sg [options] SPACEGROUP[...]
Prints information about the space group.
  -h, --help     Print usage and exit.
  -V, --version  Print version and exit.
  -v, --verbose  Verbose output.
  --asu=N        Draw ASU in NxNxN map grid and exit. Uses N(N+1) columns.

contents

Analyses and summarizes content of a coordinate file. Inspired by CCP4 program rwcontents.

By default, it prints atom count, estimated number of hydrogens in the protein, molecular weight of the protein, ASU volume, Matthews coefficient and the fractional volume of solvent in the crystal.

It has options to print other information – see the help message below.

$ gemmi contents -h
Usage:
 gemmi contents [options] INPUT[...]
Analyses content of a PDB or mmCIF.
  -h, --help     Print usage and exit.
  -V, --version  Print version and exit.
  -v, --verbose  Verbose output.
  -b             Print statistics of isotropic ADPs (B-factors).
  --dihedrals    Print peptide dihedral angles.
  -n             Do not print content (for use with other options).

contact

Searches for contacts in a model.

$ gemmi contact -h
Usage:
 gemmi contact [options] INPUT[...]
Searches for contacts in a model (PDB or mmCIF).
  -h, --help     Print usage and exit.
  -V, --version  Print version and exit.
  -v, --verbose  Verbose output.
  -d, --maxdist=D  Maximal distance in A (default 3.0)
  --cov=TOL      Use max distance = covalent radii sum + TOL [A].
  --covmult=M    Use max distance = M * covalent radii sum + TOL [A].
  --minocc=MIN   Ignore atoms with occupancy < MIN.
  --ignore=N     Ignores atom pairs from the same: 0=none, 1=residue, 2=same or
                 adjacent residue, 3=chain, 4=asu.
  --nosym        Ignore contacts between symmetry mates.
  --assembly=ID  Output bioassembly with given ID (1, 2, ...).
  --noh          Ignore hydrogen (and deuterium) atoms.
  --nowater      Ignore water.
  --noligand     Ignore ligands and water.
  --count        Print only a count of atom pairs.
  --twice        Print each atom pair A-B twice (A-B and B-A).

blobs

Searches for unmodelled blobs in electron density. Similar to “Validate > Unmodelled blobs…” in Coot. For use in Dimple.

$ gemmi blobs -h
Usage:
 gemmi blobs [options] MTZ_OR_MMCIF PDB_OR_MMCIF

Search for umodelled blobs of electron density.

Options:
  -h, --help            Print usage and exit.
  -V, --version         Print version and exit.
  -v, --verbose         Verbose output.

The area around model is masked to search only unmodelled density.
  --mask-radius=NUMBER  Mask radius (default: 2.0 A).
  --mask-water          Mask water (water is not masked by default).

Searching blobs of density above:
  --sigma=NUMBER        Sigma (RMSD) level (default: 1.0).
  --abs=NUMBER          Absolute level in electrons/A^3.

Blob criteria:
  --min-volume=NUMBER   Minimal volume (default: 10.0 A^3).
  --min-score=NUMBER    Min. this electrons in blob (default: 15.0).
  --min-sigma=NUMBER    Min. peak rmsd (default: 0.0).
  --min-peak=NUMBER     Min. peak density (default: 0.0 el/A^3).

Options for map calculation:
  -d, --diff            Use difference map coefficients.
  --section=NAME        MTZ dataset name or CIF block name
  -f COLUMN             F column (MTZ label or mmCIF tag).
  -p COLUMN             Phase column (MTZ label or mmCIF tag).
  --weight=COLUMN       (normally not needed) weighting for F.
  -g, --grid=NX,NY,NZ   Grid size (user-specified minimum).
  --exact               Use the exact grid size specified by --grid.
  -s, --sample=NUMBER   Set spacing to d_min/NUMBER (3 is usual).
  -G                    Print size of the grid that would be used and exit.
  --timing              Print calculation times.

h

Adds or removes hydrogens. Hydrogen are put in positions based only on restraints from a monomer library.

$ gemmi h -h
Usage:
 gemmi h [options] INPUT_FILE OUTPUT_FILE

Add hydrogens in positions specified by the monomer library.
By default, it removes and re-adds all hydrogens.
By default, hydrogens are not added to water.

Options:
  -h, --help      Print usage and exit.
  -V, --version   Print version and exit.
  -v, --verbose   Verbose output.
  --monomers=DIR  Monomer library dir (default: $CLIBD_MON).
  --remove        Only remove hydrogens.
  --keep          Do not add/remove hydrogens, only change positions.
  --water         Add hydrogens also to waters.
  --sort          Order atoms in residues according to _chem_comp_atom.

mondiff

Compares restraints from two monomer CIF files. It is intended for comparing restraints for the same monomer, but generated with different programs (or different versions of the same program).

The files should have format used by the CCP4/Refmac monomer library. This format is supported by all major macromolecular refinement programs.

$ gemmi mondiff -h
Usage:
  gemmi mondiff [options] FILE1 FILE2
Options:
  -h, --help         Print usage and exit.
  -V, --version      Print version and exit.
  -v, --verbose      Verbose output.

Minimal reported differences:
  --bond=DELTA       difference in distance value (default: 0.01).
  --bond-esd=DELTA   difference in distance esd (default: 0.1).
  --angle=DELTA      difference in angle value (default: 0.1).
  --angle-esd=DELTA  difference in angle esd (default: 1.0).
  --rel=SIGMA         abs(value difference) / esd > SIGMA (default: 0.0).

wcn

Calculates Weighted Contact Number (WCN) and a few other similar metrics.

WCN can be used to predicts B-factors (ADPs) from coordinates, and to compare this prediction with the values from refinement.

Background

Protein flexibility and dynamic properties can be to some degree inferred from the atomic coordinates of the structure. Various approaches are used in the literature: molecular dynamics, Gaussian or elastic network models, normal mode analysis, calculation of solvent accessibility or local packing density, and so on.

Here we apply the simplest approach, which is pretty effective. It originates from the 2002 PNAS paper in which Bertil Halle concluded that B-factors are more accurately predicted by counting nearby atoms than by Gaussian network models. This claim was based on the analysis of only 38 high resolution structures (and a neat theory), but later on the method was validated on many other structures.

In particular, in 2007 Manfred Weiss brought this method to the attention of crystallographers by analysing in Acta Cryst D different variants of the methods on a wider set of more representative crystals. Recently, the parameters fine-tuned by Weiss have been used for guessing which high B-factors (high comparing with the predicted value) result from the radiation damage.

Only a few months later, in 2008, Chih-Peng Lin et al. devised a simple yet significant improvement to the original Halle’s method: weighting the counted atoms by 1/d2, the inverse of squared distance. It nicely counters the increasing average number of atoms with the distance (~ d2). This method was named WCN – weighted contact number (hmm.. “contact”).

These two methods are so simple that it seems easy to find a better one. But according to my quick literature search, no better method of this kind has been found yet. In 2009 Li and Bruschweiler proposed weighting that decreases exponentially (that model was named LCBM), but in my hands it does not give better results than WCN.

In 2016 Shahmoradi and Wilke did a data analysis aiming to disentangle the effects of local and longer-range packing in the above methods. They were not concerned with B-factors, though, but with the rate of protein sequence evolution. Because the “contact” methods predict many things. Interestingly, if the exponent in WCN is treated as a parameter (equal -2 in the canonical version), the value -2.3 gives the best results in predicting evolution.

TLS

We also need to note that TLS-like methods that model B-factors as rigid-body motion of molecules are reported to give better correlation with experimental B-factors than other methods. But because such models use experimental B-factors on the input and employ more parameters, they are not directly comparable with WCN.

Unlike the TLS that is routinely used in the refinement of diffraction data, the TLS modelling described here is isotropic. It uses 10 parameters (anisotropic TLS requires 20) as described in a paper by Kuriyan and Weis (1991). Soheilifard et al (2008) got even better results by increasing B-factors at the protein ends, using 13 parameters altogether. This model was named eTLS (e = extended).

The high effectiveness of the TLS model does not mean that B-factors are dominated by the rigid-body motion. As noted by Kuriyan and Weis, the TLS model captures also the fact that atoms in the interior of a protein molecule generally have smaller displacements than those on the exterior. Additionally, authors of the LCBM paper find that the TLS model fitted to only half of the protein poorly fits the other half, which suggests overfitting.

We may revisit rigid-body modelling in the future, but now we get back to the contact numbers.

Details

The overview above skipped a few details.

  • While the WCN method is consistently called WCN, the Halle’s method was named LDM (local density model) in the original paper, and is called CN (contact number) in some other papers. CN is memorable when comparing with WCN (which adds ‘W’ – weighting) and with ACN (which adds ‘A’ – atomic).
  • These method are used either per-atom (for predicting B-factors, etc.) or per-residue (for evolutionary rate, etc.). So having “A” in ACN clarifies how it is used. To calculate the contact number per-residue one needs to pick a reference point in the residue (Cβ, the center of mass or something else), but here we do only per-atom calculations.
  • The CN method requires a cut-off, and the cut-off values vary widely, from about 5 to 18Å. In the original paper it was 7.35Å, Weiss got 7.0Å as the optimal value, Shahmoradi 14.3Å.
  • The CN can be seen as weighted by Heaviside step function, and smoothing it helps a little bit (as reported by both Halle and Weiss).
  • Similarly to eTLS, the LCBM method has eLCBM variant that adds “end effects” – special treatment of the termini.
  • Finally, these methods may or may not consider the symmetry mates in the crystal. Halle checked that including symmetric images improves the prediction. Weiss (ACN) and Li and Bruschweiler (LCBM) are also taking symmetry into account. But I think other papers don’t.

Metrics for comparison

To compare a number of nearby atoms with B-factor we either rescale the former, or we use a metric that does not require rescaling. The Pearson correlation coefficient (CC) is invariant under linear transformation, so it can be calculated directly unless we would like to apply non-linear scaling. Which was tried only in the Manfred Weiss’ paper: scaling function with three parameters improved CC by 0.012 comparing with linear function (that has two parameters). Here, to keep it simple, we only do linear scaling.

As noted by Halle, Pearson’s CC as well as the mean-square deviation can be dominated by a few outliers. Therefore Halle used relative mean absolute deviation (RMAD): sum of absolute differences divided by the average absolute deviation in the experimantal values. Halle justifies this normalization writing that it allows to compare structures determined at different temperatures. This is debatable as can be seen from ccp4bb discussions on how to compare B-factors between two structures. But for sure RMAD is a more robust metric, so we also use it. It adds another complication, though. To minimize the absolute deviation we cannot use least-squares fitting, but rather quantile regression with q=0.5.

Another metric is the rank correlation. It is interesting because it is invariant under any monotonic scaling. But it is not guaranteed to be a good measure of similarity.

Results

To be wrapped up and published. But in the meantime here are some thoughts:

  • The optimal exponent is slightly larger than 2; the difference is small, so we prefer to use 2 (i.e. w=1/r2).
  • Accounting for all symmetry mates (i.e. for intermolecular contacts in the crystal) improves the results – and then the cut-off is necessary.
  • The optimal cut-off is around 15A – let’s use 15A.
  • Averaging predicted B-factors of nearby atoms helps; we use Gaussian smoothing (blurring) with σ around 2A.
  • Pearson’s CC around 0.8 may seem high, but it corresponds to R2=0.64, i.e. it we explain only 64% of the B-factor variance. Even less of the absolute deviation – below 50%.
  • Minimizing absolute deviation (with quantile regression) gives similar results as the ordinary least squares (OLS). The difference in terms of RMAS is only ~0.03.
  • Combining WCN with CN is helping only a tiny bit (i.e. both are highly correlated) at the cost of additional parameter that is fitted. Combining WCN with rotation-only model (squared distance from the center of mass) increases CC slightly more, but still not much.
  • Accounting for symmetry mates worsens prediction of evolutionary rates. I used data from Shahmoradi and Wilke to check this.

Program

gemmi-wcn implements combination of the CN and WCN methods above.

Being based on a general-purpose crystallographic library it handles corner cases that are often ignored. A good example is searching for contacts. For most of the structures, considering only the same and neighbouring unit cells (1+26) is enough. But some structures have contacts between molecules several unit cells apart, even with only a single chain in the asu.

TBC

$ gemmi wcn -h
Usage:
 gemmi wcn [options] INPUT[...]
Calculation of local density / contact numbers: WCN, CN, ACN, LDM, etc.
  -h, --help       Print usage and exit.
  -V, --version    Print version and exit.
  -v, --verbose    Verbose output.
  -f, --file=FILE  Obtain paths or PDB IDs from FILE, one per line.
  -l, --list       List per-residue values.
  --min-dist=DIST  Minimum distance for "contacts" (default: 0.8).
  --cutoff=DIST    Maximum distance for "contacts" (default: 15).
  --pow=P          Exponent in the weighting (default: 2).
  --blur=SIGMA     Apply Gaussian smoothing of predicted B-factors.
  --rom            Rotation only model: |pos-ctr_of_chain|^P instead of WCN.
  --chain=CHAIN    Use only one chain from the INPUT file.
  --sanity         Run sanity checks first.
  --sidechains=X   One of: include, exclude, only (default: include).
  --no-crystal     Ignore crystal symmetry and intermolecular contacts.
  --omit-ends=N    Ignore N terminal residues from each chain end.
  --print-res      Print also resolution and R-free.
  --xy-out=DIR     Write DIR/name.xy files with WCN and B(exper).