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 .
Keywords: Cheminformatics kit; In silico chemistry; Molecular fingerprinting; Python; Structure visualisation.
© 2022. The Author(s).