tidyscreen_revised
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (12.7%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: MedChemLab
- License: gpl-3.0
- Language: Python
- Default Branch: main
- Size: 433 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 3
- Releases: 0
Metadata Files
README.md
Project Overview
TidyScreen is a package developed at MedChemLab with the aim of providing a structured framework for the design, execution and documentation of a virtual drug screening campaign.
Overall, the package provides functionalities capable of creating and organizing a given chemical space (ChemSpace module) intended to be explored through synthetically feasible chemical reactions. In a nutshell, the corresponding working chemical space is efficiently created from commercially available reactants a first stage of the virtual campaign execution. In this way, synthetic pathways are enumerated.
As part of further screening stages, the execution of molecular docking and molecular dynamics studies are also managed within TidyScreen.
A core feature common to TidyScreen philosophy is the use of SQL databases to store in an organized fashion all the information relevant the campaign progress, including simulation conditions, results and raw data. In this respect, sharing of the whole project in the context of collaborative work and/or reproducing reported studies is straightforward.
Installation
bash
$ conda create -n tidyscreen python=3.10
$ conda activate tidyscreen
$ pip install git+https://github.com/MedChemLab/TidyScreen_revised
Additional requirements not installed by CONDA:
- AutoDock-GPU: TidyScreen has been prepared to work in conjunction with AutoDock-GPU, which has been developed in the ForliLab at Scripps Research. We acknowledge Stefano Forli, Diogo Santos-Martins and Andreas Tillack for the kind feedback during TidyScreen development.
- Amber MD engine: this software package is required to confer TidyScreen the capability to prepare and document molecular dynamics simulations of docked poses.
In order to use TidyScreen, users can access the documentation describing the project and specific working examples.
Owner
- Name: MedChemLab
- Login: MedChemLab
- Kind: organization
- Repositories: 1
- Profile: https://github.com/MedChemLab
Citation (CITATION.cff)
cff-version: 1.0.0 message: "If you use this software, please cite it as below." author: - family-names: "Quevedo" given-names: "Alfredo" orcid: "https://orcid.org/0000-0002-7891-7834" title: "TidyScreen: a Python based package to manage large drug screening campaigns" version: 1.0.0
GitHub Events
Total
- Push event: 20
Last Year
- Push event: 20