Welcome to the CAMPARI home page!
We are proud to introduce the fourth official version of CAMPARI (V4).
This version of CAMPARI differs from its predecessor (V3) primarily in the addition of a large
module to support virtual screening (computational docking) applications, which comes with
a variety of extensions, minor paradigmatic adjustments, and revised parameters. In this mode,
a specified calculation is repeated as many time as there are different small (non-polymer) molecules found
in a dedicated input file in mol2-format. If you are already familiar with CAMPARI, have a look at the
documentation to get started with this exciting addition!We have also added a number of other features:
- Installation is available, as an alternative to the traditional method, through a configure-script.
- A tool to interactively build key-file templates for different classes of CAMPARI-supported calculations.
- A way to relax input structures containing isolated clashes in a targeted manner.
- Better interoperability of fine-grained, user-defined constraints and the Monte Carlo samplers.
- New options for transition matrix construction and feature extraction.
- Compartmentalization potentials allowing the calculation of transfer free energies.
- Position restraints and observation of certain bias potentials during structure randomization.
As most functionalities of CAMPARI since the third version benefit from an OpenMP threads parallelization, the software is well-suited to run on the modern computing resources of today, which routinely feature tens of cores in a single shared memory node, thereby extending the range of applicability of CAMPARI into large and dense systems while maintaining reasonable production rates. Because of our development model, CAMPARI does not strive to compete with pure performance-optimized codes like GROMACS but rather maintains its established philosophy, that is, to rigorously support and maintain a wide array of methods and analysis tools "under the same hood."
It is our continued hope that the tools we provide for the molecular simulations of biological systems and their analysis can be as useful to other users as they are to us. We believe that CAMPARI populates a relevant niche due to its unusual layout, internal structure (explicit and system-specific support for biological macromolecules at many levels), the wide class of supported algorithms, its extensive documentation (including tutorials, many of which have been revised and extended, and three completely new ones have been added in V4), and the reference implementation of the ABSINTH implicit solvent model and force field paradigm.
If you are new to this software and/or this documentation, please refer to the documentation overview page. From there, you will be able to obtain an idea of the basic workings of CAMPARI, and you will be directed to the remainder of the comprehensive documentation. Note that a few links may not work in the web-version of the documentation found at campari.sourceforge.net. In that case, please refer to a local copy obtained by downloading the package.
Some of the features built into CAMPARI include:
(Incomplete) overview of features supported by CAMPARI V4:
- Flexible Monte Carlo sampling of biopolymers in internal coordinate / rigid-body space
- Minimization and dynamics-based sampling (MD/LD in NVE/NVT) in internal coordinate / rigid-body space
- Ability to define constraints in internal coordinate / rigid-body space at the resolution of individual degrees of freedom
- Cartesian space minimization and dynamics-based sampling (MD/LD in NVE/NVT) including support for custom sets of holonomic constraints
- Hybrid sampling algorithms combining Monte Carlo and dynamics methods
- OpenMP-based shared memory parallelization of all supported samplers (with the exception of very few Monte Carlo move types)
- Ported parameters and paradigms for major force fields such as CHARMM22/27/36, AMBER94/99/03, OPLS-AA/L, or GROMOS53a5/6
- Full support and control of the ABSINTH implicit solvation model and underlying force field paradigm
- Near-complete control over Hamiltonian through tuning of intrinsic parameters via simple keywords
- Simulations of arbitrary systems based on 3D input geometries by means of extensive patch facilities to all energy terms
- Support for droplet and periodic boundary conditions with standard long-range electrostatic corrections such as particle-mesh Ewald or reaction field methods
- Very wide support for replica-exchange simulations (available in multidimensional form in Hamiltonian space) with explicit support for free energy calculations
- Hybrid MPI/OpenMP parallelism for multi-replica simulations: inter-replica communication via MPI and speed-up of individual replicas by OpenMP
- Full support for the Progress Index-Guided Sampling (PIGS) method
- Wang-Landau sampling in Monte Carlo simulations in energy or reaction coordinate space
- Support for sculpting of energy landscapes (commonly known as "accelerated molecular dynamics") for all samplers
- Different biasing potentials to global secondary structure content, polymeric properties or to individual geometric variables
- Bias potentials acting directly on Cartesian coordinate to create compartments (multi-phase systems) and compute transfer free energies
- Support for arbitrary tabulated potentials (spline-based) and density restraints (spatial)
- Molecule builder for polypeptides, polynucleotides, and various small molecules without the requirement to provide any structural or geometric input
- Built-in analysis routines pertaining to polymeric properties (e.g., simulated scattering data), structural properties (e.g., secondary structure assignment for polypeptides according to DSSP), solution structure (e.g., arbitrary pair correlation functions), and many more (with the ability to perform these analyses "on-the-fly")
- Various clustering algorithms operating on a large selection of possible coordinates, some with parallel (OpenMP) support
- An entire toolkit dedicated to network (Markov state) models and their analysis (committor probabilities, steady states, etc.)
- Implementations of published algorithms, e.g., for data mining, tree-based clustering, J. Chem. Theor. Comput. 8 (3), 1108-1120 (2012), kinetic partitioning, Comput. Phys. Comm. 184 (11), 2446-2453 (2013), automatic feature selection, J. Chem. Theor. Comput. 11 (11), 5481-5492 (2015), MSM-based reweighting, J. Chem. Phys., 150 (10), 104105 (2019); for simulation methodology, analysis of spatial density maps by equilibrium sampling, Structure 22 (1), 156-167 (2014), dynamics in mixed rigid body and dihedral angle space, J. Chem. Phys., 141 (3), 034105 (2014), the progress index guided sampling method, Biochim. Biophys. Acta, 1850 (5), 889-902 (2015), calculating transfer free energies using compartmentalization potentials, Phys. Chem. Chem. Phys. 20 (42), 27003-27010 (2018), and the use of CAMPARI and ABSINTH in virtual screening, J. Chem. Inf. Model. 60 (10), 5188-5202 (2020).
- Conversion of various binary trajectory file formats and PDB naming conventions, program execution in trajectory analysis mode (also in parallel)
- Completely free and released under the GPL
Features currently not supported by CAMPARI but commonly found in other simulation software packages:
- Implicit solvation models other than ABSINTH or primitive models
- MPI-based "classic" domain decomposition for dense systems (see OpenMP functionality above)
- Sampling of constant-pressure ensembles using manostats
The above lists should provide you with a good idea of whether CAMPARI may be a useful addition to your toolkit. We are also happy to highlight here a CAMPARI "spin-off" project that aims to provide accessibility to our data mining algorithms from R and is developed primarily by Davide Garolini, see its GitLab page. The list of references contains many examples of research performed with the help of CAMPARI.