Abstract
Small molecules can be represented in various file formats, (1) one-line systems such as SMILES (Simplified Molecular Input Line Entry System) and InChI (International Chemical Identifier) and (2) table systems such as the molfiles, SDF (Structure Data File), and KCF (KEGG Chemical Function). KCF and KCF-S (KEGG Chemical Function-and-Substructures) apply physicochemical property labels on the representations of small molecules, and contribute to improved analysis of compound–protein networks including drug–target interaction, and compound–compound networks including metabolic pathways. In this chapter, the main concepts, usage, and some example applications of the KCFCO and KCF-S packages are explained.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Clark DE, Pickett SD (2000) Computational methods for the prediction of ‘drug-likeness’. Drug Discov Today 5:49–58
Yamanishi Y, Kotera M, Kanehisa M, Goto S (2010) Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework. Bioinformatics 26:i246–i254
Kotera M, Goto S (2016) Metabolic pathway reconstruction strategies for central metabolism and natural product biosynthesis. Biophys Physicobiol 13:195–205
Weininger D (1970) SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. Proc. Edinburgh Math. SOC, Vol. 17, pp. 1–14
Heller SR, McNaught A, Pletnev I, Stein S, Tchekhovskoi D (2015) InChI, the IUPAC international chemical identifier. J Cheminform 7:23. https://doi.org/10.1186/s13321-015-0068-4
Hattori M, Okuno Y, Goto S, Kanehisa M (2003) Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. J Am Chem Soc 125:11853–11865
Hastings J, Owen G, Dekker A, Ennis M, Kale N, Muthukrishnan V, Turner S, Swainston N, Mendes P, Steinbeck C (2016) ChEBI in 2016: improved services and an expanding collection of metabolites. Nucleic Acids Res 44:D1214–D1219. https://doi.org/10.1093/nar/gkv1031
Brecher JS (1998) The chemfinder webserver: indexing chemical data on the internet. CHIMIA Int J Chem 52:658–663
Pence HE, Williams A (2010) ChemSpider: an online chemical information resource. J Chem Educ 87:1123–1124
Steinbeck C, Han Y, Kuhn S, Horlacher O, Luttmann E, Willighagen E (2003) The chemistry development kit (CDK): an open-source java library for chemo- and bioinformatics. J Chem Inf Comput Sci 43:493–500
Hall LH, Kier LB (1995) Electrotopological state indices for atom types: a novel combination of electronic, topological, and valence state information. J Chem Inf Comput Sci 35:1039–1045
Klekota J, Roth FP (2008) Chemical substructures that enrich for biological activity. Bioinformatics 24:2518–2525
Durant J et al (2002) Reoptimization of MDL keys for use in drug discovery. J Chem Inf Comput Sci 42:1273–1280
Chen B et al (2009) PubChem as a source of polypharmacology. J Chem Inf Model 49:2044–2055
Kotera M et al (2013) KCF-S: KEGG chemical function and substructure for improved interpretability and prediction in chemical bioinformatics. BMC Syst Biol 7(Suppl 6):S2
Sawada R, Kotera M, Yamanishi Y (2014) Benchmarking a wide range of chemical descriptors for drug-target interaction prediction using a chemogenomic approach. Mol Informatics 33:719–731. https://doi.org/10.1002/minf.201400066
Acknowledgments
Funding from the Ministry of Education, Culture, Sports, Science and Technology of Japan, the Japan Science and Technology Agency, and the Japan Society for the Promotion of Science; JSPS Kakenhi (25108714,). This work was also supported by the Program to Disseminate Tenure Tracking System, MEXT, Japan.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Kotera, M. (2018). Physicochemical Property Labels as Molecular Descriptors for Improved Analysis of Compound–Protein and Compound–Compound Networks. In: Brown, J. (eds) Computational Chemogenomics. Methods in Molecular Biology, vol 1825. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8639-2_6
Download citation
DOI: https://doi.org/10.1007/978-1-4939-8639-2_6
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-8638-5
Online ISBN: 978-1-4939-8639-2
eBook Packages: Springer Protocols