dockey | integrated tool for molecular docking
kandi X-RAY | dockey Summary
kandi X-RAY | dockey Summary
dockey is a Python library. dockey has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.
Computer-aided drug design (CADD) has become one of the most efficient methods to greatly reduce the costs and time as well as the attrition rates for identification of promising drug candidates. CADD can be broadly divided into structure-based and ligand-based drug design approaches. Molecular docking is the most widely used structure-based CADD approach to assist in streamlining and accelerating the overall drug discovery process. The goal of molecular docking is to predict the preferred conformation, affinity and interaction of a ligand within the binding site of a macromolecular with the aid of computational tools. AutoDock and its variants are the most popular docking tools for study of protein-ligand interactions and virtual screening. We developed Dockey, a novel graphical user interface tool with seamless integration of several external tools that implements a complete streamlined docking pipeline including molecular preparation, paralleled docking execution, interaction detection and conformation visualization.
Computer-aided drug design (CADD) has become one of the most efficient methods to greatly reduce the costs and time as well as the attrition rates for identification of promising drug candidates. CADD can be broadly divided into structure-based and ligand-based drug design approaches. Molecular docking is the most widely used structure-based CADD approach to assist in streamlining and accelerating the overall drug discovery process. The goal of molecular docking is to predict the preferred conformation, affinity and interaction of a ligand within the binding site of a macromolecular with the aid of computational tools. AutoDock and its variants are the most popular docking tools for study of protein-ligand interactions and virtual screening. We developed Dockey, a novel graphical user interface tool with seamless integration of several external tools that implements a complete streamlined docking pipeline including molecular preparation, paralleled docking execution, interaction detection and conformation visualization.
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dockey has a low active ecosystem.
It has 11 star(s) with 1 fork(s). There are 3 watchers for this library.
It had no major release in the last 12 months.
There are 2 open issues and 0 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of dockey is 0.8.2
Quality
dockey has no bugs reported.
Security
dockey has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
dockey is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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dockey releases are available to install and integrate.
Build file is available. You can build the component from source.
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dockey Key Features
No Key Features are available at this moment for dockey.
dockey Examples and Code Snippets
No Code Snippets are available at this moment for dockey.
Community Discussions
No Community Discussions are available at this moment for dockey.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install dockey
You can download it from GitHub.
You can use dockey like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use dockey like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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