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https://github.com/MolecularAI/Icolos

Icolos: A workflow manager for structure based post-processing of de novo generated small molecules
https://github.com/MolecularAI/Icolos

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Icolos: A workflow manager for structure based post-processing of de novo generated small molecules

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README 

        
**Please note: this repository is no longer being maintained.**



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# `Icolos`: Workflow manager



The `Icolos` tool is a workflow manager for structure-based workflows in computational chemistry, that abstracts execution logic from implementation as much as possible. Icolos was designed to interface with [REINVENT](https://github.com/MolecularAI/Reinvent), and workflows can be called as a component of the scoring function, or to postprocess results with more expensive methods. Workflows are specified in `JSON` format (see folder `examples`). Currently wrapped are a diverse set of tools and internal steps, including docking, QM and MD capabilities. The pre-print is available [here](https://doi.org/10.26434/chemrxiv-2022-sjcp3).



## Introduction

`Icolos` provides a unified interface to a host of software for common computational chemistry calculations, with built in parallelization,

and straight-forward extensibiltiy to add additional functionality. It was principally developed to handle structural calculations for `REINVENT` jobs, however, workflows can also be run independently.



Workflows are constructed from elementary 'steps', individual blocks which are combined to specify a sequential list of operations, with control of the command-line options provided through step settings, and options to control other aspects of the step's behaviour included in the `additional` block.



For many use cases, one of the template workflows might suit your needs, or need a few tweaks to do what you want. Demonstration notebooks for common workflows are available [here](https://github.com/MolecularAI/IcolosCommunity).



## Initial configuration

You are welcome to clone the repository and use a local version, and in particular if you would like to experiment with the code base and/or contribute features, please get 

in contact with us.



## Installation

After cloning, first install and activate the `icolosprod` `conda` environment. To ensure the right installation directory is used, you can add the `--prefix` parameter to the `create` call, specifying the location of the `conda` environments.

```

conda env create -f environment_min.yml

conda activate icolosprod

```

Then install the package:

```

pip install -e .

```

This will give you access to the `icolos` entrypoint.



### `ESPsim` installation

The following will install the `ESPsim` package into the environment - this is only required if ligand-based matching using this package is desired.



```

cd ..

git clone https://github.com/hesther/espsim.git

cd espsim

conda activate icolosprod

pip install -e .

```

## Unit testing

Icolos is extensively unit tested, and relies on an external data repo located [here](https://github.com/MolecularAI/IcolosData).  The full test suite takes ~60 mins on a workstation, therefore it is recommended that you execute a subset of unit tests relevant to the workflow you are running.  To execute the full test suite, run something like:

```

pytest -n 8 tests/

```



## Execution

Once a `JSON` is specified, the workflow can be executed like so:



```

conda activate icolosprod

icolos -conf workflow.json

```



We usually advise to check the validity of your configuration file before you try to execute it. There is a bespoke `validator` entry point to facilitate this:



```

validator -conf workflow.json

```



## `SLURM` Execution

Once specified, a workflow can be called like this in a `bash` script:



```

#!/bin/bash -l

#SBATCH -N 1

#SBATCH -t 0-02:59:00

#SBATCH -p core

#SBATCH --ntasks-per-node=5

#SBATCH --mem-per-cpu=2G



source //miniconda3/bin/activate //minconda3/envs/icolosprod

icolos -conf workflow.json

```

For GROMACS workflows requiring the GPU partition, you will need to adapt the header accordingly, e.g. like so:



```

#!/bin/bash

#SBATCH -J gmx_cco1_fold_microsecond

#SBATCH -o MygpuJob_out_%j.txt

#SBATCH -e MygpuJob_err_%j.txt

#SBATCH -c 8

#SBATCH --gres=gpu:1

#SBATCH --mem-per-cpu=4g

#SBATCH -p gpu

#SBATCH --time=12:00:00



```

## Documentation

The API reference is available [here](https://molecularai.github.io/Icolos/index.html).



## Developers

- Christian Margreitter [@cmargreitter](https://github.com/CMargreitter)

- J. Harry Moore [@jharrymoore](https://github.com/jharrymoore)

- Matthias R. Bauer