recipe promod3

ProMod3 is a tool for protein structure prediction and refinement

Homepage:

https://openstructure.org/promod3/

Developer docs:

https://git.scicore.unibas.ch/schwede/ProMod3

License:

Apache / Apache-2.0

Recipe:

/promod3/meta.yaml

Links:

biotools: promod3, doi: 10.1371/journal.pcbi.1008667

ProMod3 is a modelling engine based on the OpenStructure computational structural biology framework (www.openstructure.org) that can perform all steps required to generate a protein model by homology. Its modular design aims at implementing flexible modelling pipelines and fast prototyping of novel algorithms.

package promod3

(downloads) docker_promod3

versions:

3.6.0-0,  3.5.0-0

depends libboost:

>=1.86.0,<1.87.0a0

depends libboost-python:

>=1.86.0,<1.87.0a0

depends libgcc:

>=13

depends libstdcxx:

>=13

depends openmm:

>=8.3.1,<9.0a0

depends openstructure:

>=2.11.0,<2.12.0a0

depends python:

>=3.10,<3.11.0a0 *_cpython

depends python_abi:

3.10.* *_cp310

requirements:

additional platforms:
linux-aarch64,  osx-arm64

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install promod3

and update with::

   mamba update promod3

To create a new environment, run:

mamba create --name myenvname promod3

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/promod3:<tag>

(see `promod3/tags`_ for valid values for ``<tag>``)

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