Use TLDR for dockopt, decoy generation, and job management.
Project description
What is it?
A toolkit to interface https://tldr.docking.org/, a webserver home to a collection of docking optimization and benchmark molecular docking programs.
Installation
Installation is super easy and pip installable. Please make sure you have Python 3.6 installed.
$ pip install tldr-tools
The API_KEY, as found on the top right corner under tldr.docking.org, must be set as an environmental variable before usage. The API_KEY can be assigned in .env under the package root, or directly set in terminal.
# Method 1: Add under .env (recommended for for python notebooks)
$ echo "API_KEY=SOMESECRETKEY" > .env
# Method 2: Manually setting API_KEY (recommended for interactive jobs)
export API_KEY="SOMESECRETKEY"
Usage
To view the current implemented modules in tldr-tools, please run:
$ tldr-submit --list-modules
For example, if running decoy generation is desired:
tldr-submit --module decoys --activesism input_files/actives.ism --decoygenin input_files/decoy_generation.in --memo "Decoy generation for ADA, replicate 1"
Documenting runs with the optional memo parameter is encouraged.
Pass in a job number to check on a status of a run:
tldr-status --job-number 14886
Once a run is successful, you can download the output to a local directory:
tldr-download --job-number 14886 --output some_folder
Extending tldr-tools
Community and expansion is encouraged and made easy with this codebase. Adding new modules that are newly introduced on https://tldr.docking.org/ is painless, and is as simple as adding a new Endpoint and required/optional list of files.
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