Functional Feature Extraction and Chemical Retrieval

Chemical structural formulas are commonly used for presenting the structural and functional information of organic chemicals. Searching for chemical structures with similar chemical properties is highly desirable especially for drug discovery. However, structural search for chemical formulas is a challenging problem as chemical formulas are highly symbolic and spatially structured. In this paper, we propose a new approach for chemical feature extraction and retrieval. In the proposed approach, we extract four types of functional features from Chemical Functional Group (CFG) Graph built from a chemical structural formula, and use them for the first time for chemical retrieval. The extracted chemical functional features are then used for similarity measurement and query retrieval. The performance evaluation shows that the proposed approach achieves promising accuracy and outperforms a state-of-the-art method for chemical retrieval.

[1]  Henry S. Rzepa,et al.  Chemical Markup, XML, and the World Wide Web. 4. CML Schema , 2003, J. Chem. Inf. Comput. Sci..

[2]  G. Schneider,et al.  Comparison of Three Holographic Fingerprint Descriptors and their Binary Counterparts , 2005 .

[3]  Edmond Chow,et al.  A Graph Search Heuristic for Shortest Distance Paths , 2005, AAAI 2005.

[4]  Thomas R. Hagadone,et al.  Molecular substructure similarity searching: efficient retrieval in two-dimensional structure databases , 1992, J. Chem. Inf. Comput. Sci..

[5]  John P. Overington,et al.  ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..

[6]  Yanli Wang,et al.  PubChem: a public information system for analyzing bioactivities of small molecules , 2009, Nucleic Acids Res..

[7]  Henry S. Rzepa,et al.  Chemical Markup, XML, and the Worldwide Web. 1. Basic Principles , 1999, J. Chem. Inf. Comput. Sci..

[8]  Yvonne C. Martin,et al.  Use of Structure-Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection , 1996, J. Chem. Inf. Comput. Sci..

[9]  David Weininger,et al.  SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules , 1988, J. Chem. Inf. Comput. Sci..

[10]  P. Willett,et al.  Comparison of topological descriptors for similarity-based virtual screening using multiple bioactive reference structures. , 2004, Organic & biomolecular chemistry.

[11]  N. Null.  The IUPAC International Chemical Identifier (InChI) , 2009 .

[12]  Matthias Rarey,et al.  Feature trees: A new molecular similarity measure based on tree matching , 1998, J. Comput. Aided Mol. Des..

[13]  Arthur Dalby,et al.  Description of several chemical structure file formats used by computer programs developed at Molecular Design Limited , 1992, J. Chem. Inf. Comput. Sci..

[14]  Robert P Sheridan,et al.  Why do we need so many chemical similarity search methods? , 2002, Drug discovery today.

[15]  Johann Gasteiger,et al.  The Coding of the Three-Dimensional Structure of Molecules by Molecular Transforms and Its Application to Structure-Spectra Correlations and Studies of Biological Activity , 1996, J. Chem. Inf. Comput. Sci..

[16]  Antony J. Williams,et al.  ChemSpider:: An Online Chemical Information Resource , 2010 .

[17]  Hinrich Schütze,et al.  Introduction to information retrieval , 2008 .

[18]  Miklos Feher,et al.  Novel 2D Fingerprints for Ligand-Based Virtual Screening , 2006, J. Chem. Inf. Model..