powerfit-em 4.0.4
Rigid body fitting of high-resolution structures in low-resolution cryo-electron microscopy density maps
Requires Python: >=3.10

# PowerFit

[![PyPI - Version](https://img.shields.io/pypi/v/powerfit-em)](https://pypi.org/project/powerfit-em/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.14185749.svg)](https://doi.org/10.5281/zenodo.14185749)
[![Research Software Directory Badge](https://img.shields.io/badge/rsd-powerfit-00a3e3.svg)](https://www.research-software.nl/software/powerfit)
[![SBGrid Badge](https://img.shields.io/badge/PowerFit-blue?label=SBGrid&labelColor=%3D)](https://sbgrid.org/software/titles/powerfit)

## About PowerFit

PowerFit is a Python package and simple command-line program to automatically
fit high-resolution atomic structures in cryo-EM densities. To this end it
performs a full-exhaustive 6-dimensional cross-correlation search between the
atomic structure and the density. It takes as inputV an atomic structure in
PDB-format and a cryo-EM density with its resolution; and outputs positions and
rotations of the atomic structure corresponding to high correlation values.
PowerFit uses the local cross-correlation function as its base score. The
score is enhanced by a Laplace pre-filter and a core-weighted score to 
minimize overlapping densities from neighboring subunits. It can be
hardware-accelerated by leveraging multi-core CPU machines out of the box
or by GPU via the OpenCL framework. PowerFit is Free Software and has
been succesfully installed and used on Linux and MacOSX machines.

![Powerfit Report](http://bonvinlab.org/powerfit/Powerfit_result_page.png)

## Requirements

Minimal requirements for the CPU version:

* Python3.10 or greater

To offload computations to a discrete or integrated\* GPU the following is also required

* OpenCL1.1+
* GCC (or another C-compiler which is need to compile the pyvkfft package)

Recommended for installation

* git
* pip

\* _Integrated graphics on CPUs are able to signficantly outperform the native CPU implementation in some cases. This is mostly applicable to Intel devices, see the section [tested platfoms](installation.md#tested-platforms)_.

## Installation

If you want to run PowerFit on just the CPU, the installation should be as easy as opening up a shell and typing

```shell
# To run on CPU
pip install powerfit-em
```

If you want to offload the calculation to a GPU, please follow the instructions 
for your particular operating system described [here](https://bonvinlab.org/powerfit/installation.html), that should get you up and running in no time.

## Usage

After installing PowerFit the command line tool *powerfit* should be at your
disposal. The general pattern to invoke *powerfit* is

```shell
powerfit <map> <resolution> <pdb>
```

where `<map>` is a density map in CCP4 or MRC-format, `<resolution>`  is the
resolution of the map in &aring;ngstrom, and `<pdb>` is an atomic model in the
PDB-format. This performs a 10&deg; rotational search using the local
cross-correlation score on a single CPU-core. During the search, *powerfit*
will update you about the progress of the search if you are using it
interactively in the shell.

Please refer to the [PowerFit tutorial](https://www.bonvinlab.org/education/Others/powerfit/) to learn how to use PowerFit in the command line.

Please refer to the [PowerFit webserver tutorial](https://www.bonvinlab.org/education/Others/powerfit-webserver/) to learn how to use PowerFit on the webserver.

For more information and details please look at the [general manual](https://bonvinlab.org/powerfit/manual.html).

## Licensing

If this software was useful to your research, please cite us

**G.C.P. van Zundert and A.M.J.J. Bonvin**.
Fast and sensitive rigid-body fitting into cryo-EM density maps with PowerFit.
*AIMS Biophysics* 2, 73-87 (2015) [https://doi.org/10.3934/biophy.2015.2.73](https://doi.org/10.3934/biophy.2015.2.73).

For the use of image-pyramids and reliability measures for fitting, please cite

**G.C.P van Zundert and A.M.J.J. Bonvin**.
Defining the limits and reliability of rigid-body fitting in cryo-EM maps using
multi-scale image pyramids.
*J. Struct. Biol.* 195, 252-258 (2016) [https://doi.org/10.1016/j.jsb.2016.06.011](https://doi.org/10.1016/j.jsb.2016.06.011).

If you used PowerFit v1, please cite software with [https://doi.org/10.5281/zenodo.1037227](https://doi.org/10.5281/zenodo.1037227).
For version 2 or higher, please cite software with [https://doi.org/10.5281/zenodo.14185749](https://doi.org/10.5281/zenodo.14185749).

Apache License Version 2.0

The elements.py module is licensed under MIT License (see header).
Copyright (c) 2005-2015, Christoph Gohlke

## Contributing

To contribute to PowerFit, see our [Contribution guidelines](CONTRIBUTING.md).