A generalizable definition of chemical similarity for read-across

详细信息    查看全文

• 作者：Matteo Floris (1) (2)
  Alberto Manganaro (3)
  Orazio Nicolotti (4)
  Ricardo Medda (2)
  Giuseppe Felice Mangiatordi (4)
  Emilio Benfenati (3)
  
  1. CRS4 Biomedicine ; Parco Polaris ; Loc. Pixinamanna ; Pula ; Italy
  2. Istituto di Ricerca Genetica e Biomedica (IRGB) ; CNR ; Monserrato ; Italy
  3. IRCCS-Istituto di Ricerche Farmacologiche Mario Negri ; Milan ; Italy
  4. Dipartimento di Farmacia - Scienze del Farmaco ; Universit脿 degli Studi di Bari 鈥淎ldo Moro鈥? Bari ; Italy
  
• 关键词：Chemical similarity ; Read ; across ; Applicability domain ; QSAR
• 刊名：Journal of Cheminformatics
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：6
• 期：1
• 全文大小：250 KB
• 参考文献：1. Bender, A, Glen, RC (2004) Molecular similarity: a key technique in molecular informatics. Org Biomol Chem 2: pp. 3204-3218 CrossRef
  2. Nikolova, N, Jaworska, J (2003) Approaches to measure chemical similarity - a review. QSAR Comb Sci 22: pp. 1006-1026 330831" target="_blank" title="It opens in new window">CrossRef
  3. Bender, A, Jenkins, JL, Scheiber, J, Sukuru, SCK, Glick, M, Davies, JW (2009) How similar are similarity searching methods? A principal component analysis of molecular descriptor space. J Chem Inf Model 49: pp. 108-119 CrossRef
  4. Willett, P (2011) Similarity searching using 2D structural fingerprints. Methods Mol Biol 672: pp. 133-158 CrossRef
  5. Willett, P (2006) Similarity-based virtual screening using 2D fingerprints. Drug Discov Today 11: pp. 1046-1053 CrossRef
  6. Haranczyk, M, Holliday, J (2008) Comparison of similarity coefficients for clustering and compound selection. J Chem Inf Model 48: pp. 498-508 CrossRef
  7. Durant, JL, Leland, BA, Henry, DR, Nourse, JG (2002) Reoptimization of MDL keys for use in drug discovery. J Chem Inf Comput Sci 42: pp. 1273-1280 CrossRef
  8. Flower, DR (1998) On the properties of bit string-based measures of chemical similarity. J Chem Inf Comput Sci 38: pp. 379-386 CrossRef
  9. Godden, X, Bajorath, J (2000) Combinatorial preferences affect molecular similarity/diversity calculations using binary fingerprints and Tanimoto coefficients. J Chem Inf Comput Sci 40: pp. 163-166 CrossRef
  10. Daylight Chemical Information Systems Inc. http://www.daylight.com/dayhtml/doc/theory/theory.finger.html.
  11. www.tripos.com.
  12. Steinbeck, C, Han, Y, Kuhn, S, Horlacher, O, Luttmann, E, Willighagen, ELJ (2003) The Chemistry Development Kit (CDK): an open-source java library for chemo- and bioinformatics. Chem Inf Comput Sci 43: pp. 493-500 CrossRef
  13. Steinbeck, C, Hoppe, C, Kuhn, S, Floris, M, Guha, R, Willighagen, EL (2006) An open-source java library for chemo- and bioinformatics. Curr Pharm Des 12: pp. 2111-2120 CrossRef
  14. Todeschini, R, Consonni, V, Xiang, H, Holliday, J, Buscema, M, Willett, P (2012) Similarity coefficients for binary chemoinformatics data: overview and extendedcomparison using simulated and real data sets. J Chem Inf Model 52: pp. 2884-2901 CrossRef
  15. VEGA project.website: http://www.vega-qsar.eu/.
  16. 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: pp. 1039-1045 CrossRef
  17. Klekota, J, Roth, FP (2008) Chemical substructures that enrich for biological activity. Bioinformatics 24: pp. 2518-2525 CrossRef
  18. / MACCS Structural Keys. CA (USA): Symyx Software S. R;.
  19. National Center for Biotechnology Information: / 鈥楶ubChem Substructure Fingerprint v1.3.鈥?PubChem Data Specification Directory, 1 May 2009. ftp://ftp.ncbi.nlm.nih.gov/pubchem/specifications/pubchem_fingerprints.txt (17 July 2014, date last accessed).
  20. Org.openscience.cdk.fingerprint: / SubstructureFingerprinter. http://pele.farmbio.uu.se/nightly/api/org/openscience/cdk/fingerprint/SubstructureFingerprinter.html. (17 July 2014, date last accessed).
  21. / Talete srl, Dragon (Software for Molecular Descriptor Calculation). http://www.talete.mi.it/products/dragon_description.htm (17 July 2014, date last accessed).
  22. Al Khalifa, A, Haranczyk, M, Holliday, J (2009) Comparison of nonbinary similarity coefficients for similarity searching, clustering and compound selection. J Chem Inf Model 49: pp. 1193-1201 CrossRef
  23. Pavan, M, Todeschini, R (2008) Scientific Data Ranking Methods, Theory and Applications. Elsevier Science, Amsterdam
  24. Nicolotti, O, Carotti, A (2009) Improving quantitative structure-activity relationships through multiobjective optimization. J Chem Inf Model 49: pp. 2290-2302 CrossRef
  
• 刊物类别：Physics and Astronomy
• 刊物主题：Computer Applications in Chemistry
  Theoretical and Computational Chemistry
  Computational Biology/Bioinformatics
  Documentation and Information in Chemistry
  
• 出版者：Chemistry Central Ltd
• ISSN：1758-2946

文摘

Background Methods that provide a measure of chemical similarity are strongly relevant in several fields of chemoinformatics as they allow to predict the molecular behavior and fate of structurally close compounds. One common application of chemical similarity measurements, based on the principle that similar molecules have similar properties, is the read-across approach, where an estimation of a specific endpoint for a chemical is provided using experimental data available from highly similar compounds. Results This paper reports the comparison of multiple combinations of binary fingerprints and similarity metrics for computing the chemical similarity in the context of two different applications of the read-across technique. Conclusions Our analysis demonstrates that the classical similarity measurements can be improved with a generalizable model of similarity. The proposed approach has already been used to build similarity indices in two open-source software tools (CAESAR and VEGA) that make several QSAR models available. In these tools, the similarity index plays a key role for the assessment of the applicability domain.