The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching

By Egon Willighagen, J. W. Mayfield, Jonathan Alvarsson, Arvid Berg, L. Carlsson, Nina Jeliazkova, Stefan Kuhn, Tomás Pluskal, Miquel Rojas-Chertó, O. Spjuth and 4 more. Journal of Cheminformatics, 2017

423 citations recorded by the source corpus.

Background The Chemistry Development Kit (CDK) is a widely used open source cheminformatics toolkit, providing data structures to represent chemical concepts along with methods to manipulate such structures and perform computations on them. The library implements a wide variety of cheminformatics algorithms ranging from chemical structure canonicalization to molecular descriptor calculations and pharmacophore perception. It is used in drug discovery, metabolomics, and toxicology. Over the last 10 years, the code base has grown significantly, however, resulting in many complex interdependencies among components and poor performance of many algorithms.Results We report improvements to the CDK v2.0 since the v1.2 release series, specifically addressing the increased functional complexity and poor performance. We first summarize the addition of new functionality, such atom typing and molecular formula handling, and improvement to existing functionality that has led to significantly better performance for substructure searching, molecular fingerprints, and rendering of molecules. Second, we outline how the CDK has evolved with respect to quality control and the approaches we have adopted to ensure stability, including a code review mechanism.ConclusionsThis paper highlights our continued efforts to provide a community driven, open source cheminformatics library, and shows that such collaborative projects can thrive over extended periods of time, resulting in a high-quality and performant library. By taking advantage of community support and contributions, we show that an open source cheminformatics project can act as a peer reviewed publishing platform for scientific computing software.Graphical abstractCDK 2.0 provides new features and improved performance

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/39a2cbb1b4ee2da693ead86fb593cfefb712ff6d

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Citations in the corpus

Molecular representations in AI-driven drug discovery: a review and practical guide (2020, methodology): “In 2017, improvements were done in CDK to depict stereochemistry more accurately and to solve atomic overlap [112]; on the latter point, the algorithm went from a heuristic approach to a refinement process.”
Artificial Intelligence For Natural Product Drug Discovery (2023, methodology): “Algorithms to create such fingerprints are readily implemented in cheminformatic software packages such as RDKit (see Related links) and the Chemistry Development Kit 81 ; however, molecule features can be manually determined as well 82 .”