MIT License

项目介绍

aretasg/dockit 是一个托管在 GitHub 上的开源项目,主要使用 Python 编写,采用 MIT License 许可证,目前获得 33 个 Star、10 次 Fork。

仓库全名
aretasg/dockit
开源许可证
MIT License
Star 数
33
Fork 数
10

README 摘要

Dockit Perform high-throughput molecular docking with multiple targets and ligands using AutoDock Vina series engines. :gem: Features Molecular docking with multiple target and ligands at the same time. Flexible residue declaration for targets. Use other Vina-like engines e.g. Qvina2/Qvina-W or Smina. Original PDBQT preparation method as distributed with MGLTools. Automated PDBQT file preparation. Optional ligand…

完整内容见 GitHub 原始 README 或本页 。

常见问题

dockit 用什么语言开发?

主要使用 Python 编写,采用 MIT License 许可证,目前有 33 个 Star。

dockit 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 dockit 的源码?

可以直接克隆仓库:git clone https://github.com/aretasg/dockit.git,默认分支为 master;安装与运行步骤见仓库 README。

dockit 最近还在维护吗?

仓库最近一次更新为 2020年9月9日,当前没有未关闭的 Issue;Star 数为 33,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

High-throughput molecular docking with multiple targets and ligands using Vina series engines

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
55
价值分
23
活跃状态
活跃

语言占比

Dockerfile
Python

贡献者

README

Dockit

Perform high-throughput molecular docking with multiple targets and ligands using AutoDock Vina series engines.

:gem: Features

  • Molecular docking with multiple target and ligands at the same time.
  • Flexible residue declaration for targets.
  • Use other Vina-like engines e.g. Qvina2/Qvina-W or Smina.
  • Original PDBQT preparation method as distributed with MGLTools.
  • Automated PDBQT file preparation.
  • Optional ligand energy minimization using obminimize.
  • Output CSV file with all docking results for all modes for an easy access to the docking results.
  • Docker support. Run it anywhere!

:rocket: Installation (Docker or Conda)

Docker

Dockit can be run with Docker. You must have Docker & docker-compose installed.

git clone https://github.com/aretasg/dockit
cd dockit

Conda

Install conda first

git clone https://github.com/aretasg/dockit
cd dockit
conda env create -f environment.yml
conda activate dockit

:computer: Example usage

  1. Determine the search box size and centre positioning using Chimera (Tools > Structure/Binding Analysis > Vina) or similar.
  2. Define search box and docking parameters for each target in dockit_param.csv.
  3. Copy protein and ligand PDB files into targets/PDB and ligands/PDB folders, respectively and run:
python app/dockit.py

or if using Docker

docker-compose up
  • The calculation will take some time depending on the parameters and the number of files. Results can be found in the results folder.
  • Visualise the results with a molecular viewer of your choice by loading ligand PDBQT file in the results folder and target PDB or PDBQT file in targets directory.
  • CSV file dockit_results.csv is generated in results folder with all the docking results.
  • Run with -r flag to reset to the pre-run state - PDBQT and result files will be removed.

Argument description in dockit_param.csv

Argument Description Required
target file name of the target located in targets/PDB - excluding the extension :heavy_exclamation_mark:
x_center X coordinate of the seach box center :heavy_exclamation_mark:
y_center Y coordinate of the search box center :heavy_exclamation_mark:
z_center Z coordinate of the search box center :heavy_exclamation_mark:
x_size search box size in the X dimension (Angstroms) :heavy_exclamation_mark:
y_size search box size in the Y dimension (Angstroms) :heavy_exclamation_mark:
z_size search box size in the Z dimension (Angstroms) :heavy_exclamation_mark:
engine type of engine to use to run the docking (e.g. vina or qvina2) :heavy_exclamation_mark:
exhaustiveness exhaustiveness of the global search (roughly proportional to time, default=8) 🤔
num_modes maximum number of binding modes to generate (default=9) 🤔
seed explicit random seed 🤔
cpu number of CPUs available to use for docking (default is to auto detect the number of cores available) 🤔
energy_range maximum energy difference between the best binding mode and the worst one displayed (default = 3 kcal/mol) 🤔
flex_resi specify target residues to be treaded as flexible during docking 🤔

FAQ

  • Dockit will dock every target against every ligand in targets/PDB and ligands/PDB, respectively.
  • Dockit is not an input for docking preparation tool. Input files have to be in PDB format. Conversion to PDBQT adds hydrogens and removes non-polar ones.
  • Edit dockit_param.csv to change any parameters to be run with the docking engine, including search box parameters.
  • Run with -m flag perform energy minimization for ligands using obminimize with default settings.
  • Supports declaration of flexible residues for targets. Please look at dockit_param.csv for an example for how to declare flexible residues.
  • Supports other Vina-like engines e.g. Qvina2. Please specify the engine name or path to it in the engine column of dockit_param.csv. Dockit comes installed with vina, qvina2, qvinaw and smina. You should be able to use any other engine with the same CLI as Vina.
  • Specify custom scoring system weights in the weight_* fields of dockit_param.csv. More about the scoring system here.
  • Dockit utilises threading to distribute multiple simulations across available cores. Please change the cpu argument to a finite value to ensure distributed processing.
  • The necessity of selecting the charges (Kollman/Gasteirger) is obsolete with Vina due to the scoring system being based on hydrophobic and hydrogen bond interactions compared to its predecessor AutoDock 4. Nevertheless, the default charge for targets and ligands are set as Kollman and Gasteirger, respectively.

:pencil2: Authors

Written by Aretas Gaspariunas. Have a question? You can always ask and I can always ignore.

:apple: Citing

If you found Dockit useful for your work please acknowledge it by citing this repository.

License

MIT License.

Acknowledgments & Disclaimer

prepare_* files are distributed as part of MGLTools 1.5.6 and all the ownership is credited to their respective authors (Morris et al., 2009).

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