Misplaced Pages

This is an old revision of this page, as edited by Egon Willighagen (talk | contribs) at 07:26, 11 October 2020 (Updated the CDK info). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

This article's use of external links may not follow Misplaced Pages's policies or guidelines. Please improve this article by removing excessive or inappropriate external links, and converting useful links where appropriate into footnote references. (September 2020) (Learn how and when to remove this message)

Cheminformatics toolkits are software development kits that allow cheminformaticians to develop custom computer applications for use in virtual screening, chemical database mining, and structure-activity studies. Toolkits are often used for experimentation with new methodologies. Their most important functions deal with the manipulation of chemical structures and comparisons between structures. Programmatic access is provided to properties of individual bonds and atoms.

Functionality

Toolkits provide the following functionality:

• Read and save structures in various chemistry file formats.
• Determine if one structure is a substructure of another (substructure matching).
• Determine if two structures are equal (exact matching).
• Identification of substructures common to structures in a set (maximal common substructure, MCS).
• Disassemble molecules, splitting into fragments.
• Assemble molecules from elements or submolecules.
• Apply reactions on input reactant structures, resulting in output of reaction product structures.
• Generate molecular fingerprints. Fingerprints are bit-vectors where individual bits correspond to the presence or absence of structural features. The most important use of fingerprints is in indexing of chemistry databases.

List of notable cheminformatics toolkits

References

1. Jean-Loup Faulon; Andreas Bender (April 2010). Handbook of Chemoinformatics Algorithms. Chapman & Hall. ISBN 978-1420082920.
2. Johann Gasteiger (November 2003). Chemoinformatics. Wiley-VCH. ISBN 3527306811.
3. Steinbeck C, C.; Han Y; Kuhn S; Horlacher O; Luttmann E; Willighagen E (2003). "The Chemistry Development Kit". J Chemical Inf. Comput. Sci. 43 (2): 493–500. doi:10.1021/ci025584y. PMC 4901983. PMID 12653513.
4. Steinbeck C, Christoph; Hoppe C.; Kuhn S.; Floris M.; Guha R.; Willighagen E.L. (2006). "Recent Developments of the Chemistry Development Kit (CDK) - An Open-Source Java Library for Chemo- and Bioinformatics". Curr. Pharm. Des. 12 (17): 2111–2120. doi:10.2174/138161206777585274. hdl:2066/35445. PMID 16796559.
5. Willighagen, Egon L.; Mayfield, John W.; Alvarsson, Jonathan; Berg, Arvid; Carlsson, Lars; Jeliazkova, Nina; Kuhn, Stefan; Pluskal, Tomáš; Rojas-Chertó, Miquel; Spjuth, Ola; Torrance, Gilleain; Evelo, Chris T.; Guha, Rajarshi; Steinbeck, Christoph (December 2017). "The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching". Journal of Cheminformatics. 9 (1): 33. doi:10.1186/s13321-017-0220-4.{{cite journal}}: CS1 maint: unflagged free DOI (link)
6. Cao, Y; Charisi, A; Cheng, LC; Jiang, T; Girke, T (2008). "ChemmineR: A Compound Mining Framework for R." Bioinformatics. 24 (15): 1733–1734. doi:10.1093/bioinformatics/btn307. PMC 2638865. PMID 18596077.
7. Wang, Y; Backman, TW; Horan, K; Girke, T (2013). "fmcsR: Mismatch Tolerant Maximum Common Substructure Searching in R." Bioinformatics. 29 (21): 2792–4. doi:10.1093/bioinformatics/btt475. PMID 23962615.
8. Requires Knime (http://www.knime.org/)
9. Requires KNIME (http://www.knime.org/)
10. reads and writes all chemical file formats.
11. O’Boyle N; Banck M; James C; Morley C; Vandermeersch T; Hutchison G (2011). "Open babel: an open chemical". Journal of Cheminformatics. 3 (33): 33. doi:10.1186/1758-2946-3-33. PMC 3198950. PMID 21982300.{{cite journal}}: CS1 maint: unflagged free DOI (link)
12. Cao DS, Xiao N, Xu QS, Chen AF (Jan 2015). "Rcpi: R/Bioconductor package to generate various descriptors of proteins, compounds and their interactions". Bioinformatics. 31 (2): 279–281. doi:10.1093/bioinformatics/btu624. PMID 25246429.
13. McGuire R, Verhoeven S, Vass M, Vriend G, de Esch IJ, Lusher SJ, Leurs R, Ridder L, Kooistra AJ, Ritschel T, de Graaf C (2017). "3D-e-Chem-VM: Structural cheminformatics research infrastructure in a freely available Virtual Machine". J. Chem. Inf. Model. 57 (2): 115–121. doi:10.1021/acs.jcim.6b00686. PMC 5342320. PMID 28125221.
14. Kooistra AJ, Vass M, McGuire R, Leurs R, de Esch IJ, Vriend G, Verhoeven S, de Graaf C (2018). "3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery". ChemMedChem. 13 (6): 614–626. doi:10.1002/cmdc.201700754. PMC 5900740. PMID 29337438.
15. S. Asad Rahman, Syed; M. Bashton; G. L. Holliday; R. Schrader; J. M. Thornton (2009). "Small Molecule Subgraph Detector (SMSD) Toolkit". Journal of Cheminformatics. 1 (12): 12. doi:10.1186/1758-2946-1-12. PMC 2820491. PMID 20298518.{{cite journal}}: CS1 maint: unflagged free DOI (link)
16. Novel web-based tools combining chemistry informatics, biology and social networks for drug discovery. Hohman M, Gregory K, Chibale K, Smith PJ, Ekins S, Bunin B Drug Discov Today. 2009 Mar;14(5-6):261-70.

• Computational chemistry
• Cheminformatics
• Drug discovery
• Chemistry