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DUBS: A Framework for Developing Directory of Useful Benchmarking Sets for Virtual Screening.
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2020-07-08 , DOI: 10.1021/acs.jcim.0c00122
Jonathan Fine 1 , Matthew Muhoberac 1 , Guillaume Fraux 2 , Gaurav Chopra 1, 3
Affiliation  

Benchmarking is a crucial step in evaluating virtual screening methods for drug discovery. One major issue that arises among benchmarking data sets is a lack of a standardized format for representing the protein and ligand structures used to benchmark the virtual screening method. To address this, we introduce the Directory of Useful Benchmarking Sets (DUBS) framework, as a simple and flexible tool to rapidly create benchmarking sets using the protein databank. DUBS uses a simple input text based format along with the Lemon data mining framework to efficiently access and organize data to the protein databank and output commonly used inputs for virtual screening software. The simple input format used by DUBS allows users to define their own benchmarking data sets and access the corresponding information directly from the software package. Currently, it only takes DUBS less than 2 min to create a benchmark using this format. Since DUBS uses a simple python script, users can easily modify this to create more complex benchmarks. We hope that DUBS will be a useful community resource to provide a standardized representation for benchmarking data sets in virtual screening. The DUBS package is available on GitHub at https://github.com/chopralab/lemon/tree/master/dubs.

中文翻译:

DUBS:开发用于虚拟筛选的有用基准集目录的框架。

基准测试是评估用于药物发现的虚拟筛选方法的关键步骤。基准数据集中出现的一个主要问题是缺乏一种标准化的格式来表示用于对虚拟筛选方法进行基准测试的蛋白质和配体结构。为了解决这个问题,我们引入了有用基准集目录(DUBS)框架,它是一种简单而灵活的工具,可以使用蛋白质数据库快速创建基准集。DUBS使用简单的基于输入文本的格式以及Lemon数据挖掘框架来有效地访问和组织数据到蛋白质数据库,并输出虚拟筛选软件的常用输入。DUBS使用的简单输入格式允许用户定义自己的基准数据集并直接从软件包访问相应的信息。目前,使用此格式创建基准仅需不到2分钟的DUBS。由于DUBS使用简单的python脚本,因此用户可以轻松地对其进行修改以创建更复杂的基准。我们希望DUBS将成为有用的社区资源,以便为虚拟筛选中的基准数据集提供标准化表示。DUBS软件包可从GitHub上的https://github.com/chopralab/lemon/tree/master/dubs获得。
更新日期:2020-07-08
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