As the name implies, this library was originally written to work with mmCIF files using C++ as programming language. The design of this library leanes heavily on the structure of CIF files. These files can be thought of as a text dump of a relational databank with, often but not always, a very strict schema describing the data. These schema's are called dictionaries.
Using information from the content of a mmCIF file and an optional schema, libcifpp allows you to access the data in the file as a collection of datablock each containing a collection of categories with rows of data. The categories can be searched for data using queries written in regular C++ syntax. When a dictionary was specified, inserted data is checked for validity. Likewise removal of data may result in cascaded removal of linked data in other categories using parent/child relationship information.
Since there were still many programs using the legacy PDB format at the time development started, a layer was added that converts data to and from PDB format into mmCIF format. This means you can manipulate PDB files as if they were normal mmCIF files.
Apart from this basic functionality, libcifpp also offers code to help with symmetry calculations, 3d manipulations and obtaining information from the CCD Chemical Component Dictionary.
The documentation can be found at github.io
// A simple program counting residues with an OXT atom
#include <filesystem>
#include <iostream>
#include <cif++.hpp>
namespace fs = std::filesystem;
int main(int argc, char *argv[])
{
if (argc != 2)
exit(1);
// Read file, can be PDB or mmCIF and can even be compressed with gzip.
cif::file file = cif::pdb::read(argv[1]);
if (file.empty())
{
std::cerr << "Empty file\n";
exit(1);
}
// Take the first datablock in the file
auto &db = file.front();
// Use the atom_site category
auto &atom_site = db["atom_site"];
// Count the atoms with atom-id "OXT"
auto n = atom_site.count(cif::key("label_atom_id") == "OXT");
std::cout << "File contains " << atom_site.size() << " atoms of which "
<< n << (n == 1 ? " is" : " are") << " OXT\n"
<< "residues with an OXT are:\n";
// Loop over all atoms with atom-id "OXT" and print out some info.
// That info is extracted using structured binding in C++
for (const auto &[asym, comp, seqnr] :
atom_site.find<std::string, std::string, int>(
cif::key("label_atom_id") == "OXT",
"label_asym_id", "label_comp_id", "label_seq_id"))
{
std::cout << asym << ' ' << comp << ' ' << seqnr << '\n';
}
return 0;
}
You might be able to use libcifpp from a package manager used by your OS distribution. But most likely this package will be out-of-date. Therefore it is recommended to build libcifpp from code. It is not hard to do. But it is recommended to read the following instructions carefully.
The code for this library was written in C++17. You therefore need a recent compiler to build it. For the development gcc >= 9.4 and clang >= 9.0 have been used as well as MSVC version 2019.
The other requirement you really need to have installed on your computer
is a version of CMake. For now the minimum version
is 3.16 but that may soon change into a higher version. You should also
install the gui version of CMake to set build options easily, on Debian
I prefer to use the curses version installed with cmake-curses-gui
.
It is very useful to have mrc available. However, this is only an option if you use Windows or an operating system using the ELF executable format (i.e. Linux or FreeBSD). MRC is a resource compiler that allows including data files into the executable making them easier to install.
Other libraries you might want to install beforehand are:
-
libeigen, a library to do amongst others matrix calculations. This usually can be installed using your package manager, in Debian/Ubuntu it is called
libeigen3-dev
-
zlib, the development version of this library. On Debian/Ubuntu this is the package
zlib1g-dev
. -
boost, in Debian/Ubuntu this is
libboost-dev
.The Boost libraries are only needed in case you are using GCC due to a long standing bug in GNU's implementation of std::regex. It simply crashes on the regular expressions used in the mmcif_pdbx dictionary and so we use the boost regex implementation instead.
First you need to download the code:
git clone https://github.com/PDB-REDO/libcifpp.git
cd libcifpp
You should start by considering where to install libcifpp. If you have sufficient permissions on your computer you perhaps should use the default but libcifpp can be configured to be installed anywhere including e.g. $HOME/.local.
Next step is to configure, for this use the CMake gui application. If you
installed the curses version of cmake you can type ccmake
. On Windows
you can use cmake-gui.exe
.
To install in the default location:
ccmake -S . -B build
To install elsewhere, e.g. $HOME/.local:
ccmake -S . -B build -DCMAKE_INSTALL_PREFIX=$HOME/.local
In the cmake window, start the configure command (use button or press 'c'). After the first configure step you will see a list of settable options. Alter these to match your preferences. Most options are self explaining and contain a description. Some may need a bit more explanation:
-
CIFPP_DATA_DIR, this directory will be used to store initial versions of the mmcif_pdbx dictionary as well as the optional CCD file.
-
CIFPP_DOWNLOAD_CCD
The CCD file is huge and perhaps you think you don't need it. In that case you can leave this OFF. But that will limit the use cases.
-
CIFPP_INSTALL_UPDATE_SCRIPT
The files in CIFPP_DATA_DIR are quickly becoming out of date. On FreeBSD and Linux you can install a script that updates these files on a weekly basis.
-
CIFPP_CRON_DIR
The directory where the update script is to be installed.
-
CIFPP_ETC_DIR
The update script will only work if the file called libcifpp.conf in this etc directory will contain an uncommented line with
update=true
-
CIFPP_CACHE_DIR
When you installed and enabled the update script, new files are written to this directory.
-
CIFPP_RECREATE_SYMOP_DATA
If you had CCP4 sourced into your environment, this option allows you to recreate the symop data file.
-
BUILD_FOR_CCP4
Build a special version of libcifpp to be installed in the CCP4 environment.
After setting these options you can run the configure step again and then use generate to create the makefiles.
Building and installing is then as simple as:
cmake --build build
cmake --install build
If this fails due to lack of permissions, you can try:
sudo cmake --install build
Tests are created by default, and to test the code you can run:
ctest --test-dir build