Konnektor:使用图论规划自由能计算网络的框架。

IF 5.6 2区 化学 Q1 CHEMISTRY, MEDICINAL
Benjamin Ries, Richard J Gowers, Hannah M Baumann, David W H Swenson, Michael M Henry, James R B Eastwood, Irfan Alibay, David Mobley
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引用次数: 0

摘要

炼金术自由能活动可以通过图论进行规划,方法是构建包含代表分子的节点的网络,这些节点通过可能的转化作为边连接起来。我们介绍的 Konnektor 是一个开源 Python 软件包,用于系统地规划、修改和分析自由能计算网络。Konnektor 旨在帮助用户使用复杂的图操作方法轻松建立自由能计算网络,从而为药物发现过程提供帮助。该软件包包含网络操作功能,包括网络连接、删除转换和分子聚类,以及将这些工具与现有网络生成算法相结合的框架,从而开发出更复杂的网络生成方法。使用玩具数据集对所提供的各种网络布局功能进行了比较。此外,Konnektor 还包含可视化和分析工具,使网络特征研究变得更加简单。除了软件包的内容,论文还提供了应用示例,演示如何使用 Konnektor 以及从图论角度看不同网络的性能。Konnektor 可通过 GitHub https://github.com/OpenFreeEnergy/konnektor 免费获取,采用 MIT 许可。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Konnektor: A Framework for Using Graph Theory to Plan Networks for Free Energy Calculations.

Konnektor: A Framework for Using Graph Theory to Plan Networks for Free Energy Calculations.

Alchemical free energy campaigns can be planned using graph theory by building networks that contain nodes representing molecules that are connected by possible transformations as edges. We introduce Konnektor, an open-source Python package, for systematically planning, modifying, and analyzing free energy calculation networks. Konnektor is designed to aid in the drug discovery process by enabling users to easily setup free energy campaigns using complex graph manipulation methods. The package contains functions for network operations including concatenation of networks, deletion of transformations, and clustering of molecules along with a framework for combining these tools with existing network generation algorithms to enable the development of more complex methods for network generation. A comparison of the various network layout features offered is carried out using toy data sets. Additionally, Konnektor contains visualization and analysis tools, making the investigation of network features much simpler. Besides the content of the package, the paper also offers application examples, demonstrating how Konnektor can be used and how the different networks perform from a graph theory perspective. Konnektor is freely available via GitHub at https://github.com/OpenFreeEnergy/konnektor under the permissive MIT License.

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来源期刊
CiteScore
9.80
自引率
10.70%
发文量
529
审稿时长
1.4 months
期刊介绍: The Journal of Chemical Information and Modeling publishes papers reporting new methodology and/or important applications in the fields of chemical informatics and molecular modeling. Specific topics include the representation and computer-based searching of chemical databases, molecular modeling, computer-aided molecular design of new materials, catalysts, or ligands, development of new computational methods or efficient algorithms for chemical software, and biopharmaceutical chemistry including analyses of biological activity and other issues related to drug discovery. Astute chemists, computer scientists, and information specialists look to this monthly’s insightful research studies, programming innovations, and software reviews to keep current with advances in this integral, multidisciplinary field. As a subscriber you’ll stay abreast of database search systems, use of graph theory in chemical problems, substructure search systems, pattern recognition and clustering, analysis of chemical and physical data, molecular modeling, graphics and natural language interfaces, bibliometric and citation analysis, and synthesis design and reactions databases.
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