Terlouw Barbara R, Vromans Sophie P J M, Medema Marnix H
Bioinformatics Group, Wageningen University, Droevendaalsesteeg 1, 6708 PB, Wageningen, The Netherlands.
J Cheminform. 2022 Jun 7;14(1):34. doi: 10.1186/s13321-022-00616-5.
As efforts to computationally describe and simulate the biochemical world become more commonplace, computer programs that are capable of in silico chemistry play an increasingly important role in biochemical research. While such programs exist, they are often dependency-heavy, difficult to navigate, or not written in Python, the programming language of choice for bioinformaticians. Here, we introduce PIKAChU (Python-based Informatics Kit for Analysing CHemical Units): a cheminformatics toolbox with few dependencies implemented in Python. PIKAChU builds comprehensive molecular graphs from SMILES strings, which allow for easy downstream analysis and visualisation of molecules. While the molecular graphs PIKAChU generates are extensive, storing and inferring information on aromaticity, chirality, charge, hybridisation and electron orbitals, PIKAChU limits itself to applications that will be sufficient for most casual users and downstream Python-based tools and databases, such as Morgan fingerprinting, similarity scoring, substructure matching and customisable visualisation. In addition, it comes with a set of functions that assists in the easy implementation of reaction mechanisms. Its minimalistic design makes PIKAChU straightforward to use and install, in stark contrast to many existing toolkits, which are more difficult to navigate and come with a plethora of dependencies that may cause compatibility issues with downstream tools. As such, PIKAChU provides an alternative for researchers for whom basic cheminformatic processing suffices, and can be easily integrated into downstream bioinformatics and cheminformatics tools. PIKAChU is available at https://github.com/BTheDragonMaster/pikachu .
随着通过计算来描述和模拟生化世界的努力变得越来越普遍,能够进行计算机模拟化学的程序在生化研究中发挥着越来越重要的作用。虽然这类程序已经存在,但它们往往依赖性强、难以操作,或者不是用生物信息学领域首选的编程语言Python编写的。在此,我们介绍PIKAChU(基于Python的化学单元分析信息学工具包):一个用Python实现的、依赖性较少的化学信息学工具箱。PIKAChU能从SMILES字符串构建全面的分子图,便于对分子进行下游分析和可视化。虽然PIKAChU生成的分子图包含丰富信息,可存储和推断关于芳香性、手性、电荷、杂化和电子轨道的信息,但PIKAChU将自身限制在对大多数普通用户以及基于Python的下游工具和数据库足够的应用上,比如摩根指纹识别、相似性评分、子结构匹配和可定制可视化。此外,它还附带了一组有助于轻松实现反应机制的函数。其简约的设计使PIKAChU易于使用和安装,这与许多现有的工具包形成鲜明对比,那些工具包更难操作,且有大量可能导致与下游工具出现兼容性问题的依赖性。因此,PIKAChU为那些只需要基本化学信息学处理的研究人员提供了一个替代方案,并且可以很容易地集成到下游的生物信息学和化学信息学工具中。PIKAChU可在https://github.com/BTheDragonMaster/pikachu获取。