文章基本信息

标题：Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field
本地全文：下载
作者：Maciej Wójcikowski ; Piotr Zielenkiewicz ; Pawel Siedlecki 等
期刊名称：Journal of Cheminformatics
印刷版ISSN：1758-2946
电子版ISSN：1758-2946
出版年度：2015
卷号：7
期号：1
页码：26
DOI：10.1186/s13321-015-0078-2
语种：English
出版社：BioMed Central
摘要：There has been huge progress in the open cheminformatics field in both methods and software development. Unfortunately, there has been little effort to unite those methods and software into one package. We here describe the Open Drug Discovery Toolkit (ODDT), which aims to fulfill the need for comprehensive and open source drug discovery software. The Open Drug Discovery Toolkit was developed as a free and open source tool for both computer aided drug discovery (CADD) developers and researchers. ODDT reimplements many state-of-the-art methods, such as machine learning scoring functions (RF-Score and NNScore) and wraps other external software to ease the process of developing CADD pipelines. ODDT is an out-of-the-box solution designed to be easily customizable and extensible. Therefore, users are strongly encouraged to extend it and develop new methods. We here present three use cases for ODDT in common tasks in computer-aided drug discovery. Open Drug Discovery Toolkit is released on a permissive 3-clause BSD license for both academic and industrial use. ODDT’s source code, additional examples and documentation are available on GitHub ( https://github.com/oddt/oddt ).
关键词：Virtual screening ; Statistical methods ; Receptor-ligand interactions ; Toolkit ; Programming ; Machine learning ; Scoring function