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.

中文翻译：

---

Konnektor：使用图论规划网络以进行自由能计算的框架


炼金术免费能源运动可以使用图论来规划，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换作为边缘连接。我们介绍了 Konnektor，这是一个开源 Python 包，用于系统地规划、修改和分析自由能源计算网络。Konnektor 旨在通过使用户能够使用复杂的图形操作方法轻松设置免费能源活动来协助药物发现过程。该软件包包含网络操作功能，包括网络连接、删除转换和分子聚集，以及将这些工具与现有网络生成算法相结合的框架，以便开发更复杂的网络生成方法。使用玩具数据集对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，使网络特征的调查变得更加简单。除了软件包的内容外，本文还提供了应用示例，演示了如何使用 Konnektor 以及从图论角度来看不同网络的性能。Konnektor 可通过 GitHub 在 https://github.com/OpenFreeEnergy/konnektor 上免费获得，并采用宽松的 MIT 许可证。