Characterization of a comprehensive flavor database

Flavor perception involves, among a number of physiological and psychological processes, the recognition of chemicals by olfactory and taste receptors. The highly complex and multidimensional nature of flavor perception challenges our ability to both predict and design new flavor entities. Toward this endeavor, classifications of flavor descriptors have been proposed. Here, we developed a fingerprint‐based representation of a large data set comprising 4181 molecules taken from the commercially available Leffingwell & Associates Canton, Georgia, USA database marketed as Flavor‐Base Pro© 2010. Flavor descriptions of the materials in this database were composite descriptions, collected from numerous sources over the course of more than 40 years. The flavor descriptors were referenced against a detailed and authoritative sensory lexicon (ASTM, American Society for Testing and Materials publication DS 66) comprising 662 flavor attributes. Comparison of clustering analysis, principal component analysis, and descriptor associations provided similar conclusions for various mutually correlated descriptors. Regarding analysis of the flavor similarity of the molecules, the clustering performed provided a means for the quick selection of molecules with either high or low flavor similarity description. Preliminary comparison of the chemical structures to the flavor description demonstrated the feasibility but also the complexity of this task. Additional studies including different structural representations, careful selection of subsets from this data set, as well as the use of a number of classification methods will demonstrate the utility of structure–flavor associations. This work shows that the flavor information contained in databases, such as that used in the present study, can be analyzed following standard chemoinformatics methods. Copyright © 2011 John Wiley & Sons, Ltd.

[1]  Jürgen Bajorath,et al.  Molecular Fingerprint Recombination: Generating Hybrid Fingerprints for Similarity Searching from Different Fingerprint Types , 2009, ChemMedChem.

[2]  Mia Hubert,et al.  Robust PCA and classification in biosciences , 2004, Bioinform..

[3]  R. H. Wright,et al.  Stereochemical and Vibrational Theories of Odour , 1972, Nature.

[4]  Xiaodong Li,et al.  Human receptors for sweet and umami taste , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[5]  Veerabahu Shanmugasundaram,et al.  Molecular similarity measures. , 2011, Methods in molecular biology.

[6]  Robyn L Stanfield,et al.  Structural rationale for the broad neutralization of HIV-1 by human monoclonal antibody 447-52D. , 2004, Structure.

[7]  Clemencia Pinilla,et al.  Strategies for the use of mixture-based synthetic combinatorial libraries: scaffold ranking, direct testing in vivo, and enhanced deconvolution by computational methods. , 2008, Journal of combinatorial chemistry.

[8]  J. Mainland,et al.  Odor Coding by a Mammalian Receptor Repertoire , 2009, Science Signaling.

[9]  David A Bennett,et al.  Odor Identification and Progression of Parkinsonian Signs in Older Persons , 2008, Experimental aging research.

[10]  Andreas Bender,et al.  Molecular surface point environments for virtual screening and the elucidation of binding patterns (MOLPRINT) , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[11]  P. Jaccard,et al.  Etude comparative de la distribution florale dans une portion des Alpes et des Jura , 1901 .

[12]  R. Doty,et al.  Smell identification ability: changes with age. , 1984, Science.

[13]  J. Amoore,et al.  Molecular Shape and Odour : Pattern Analysis by PAPA , 1967, Nature.

[14]  L. Buck,et al.  Combinatorial Receptor Codes for Odors , 1999, Cell.

[15]  David Harel,et al.  Measuring smells , 2008, Current Opinion in Neurobiology.

[16]  John E. Amoore,et al.  Ant Alarm Pheromone Activity: Correlation with Molecular Shape by Scanning Computer , 1969, Science.

[17]  Gerald M. Maggiora,et al.  Molecular Basis SetsA General Similarity-Based Approach for Representing Chemical Spaces , 2007, J. Chem. Inf. Model..

[18]  R. Axel,et al.  A novel multigene family may encode odorant receptors: A molecular basis for odor recognition , 1991, Cell.

[19]  Richard L Doty,et al.  The olfactory system and its disorders. , 2009, Seminars in neurology.

[20]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..

[21]  L. Kelley,et al.  An automated approach for clustering an ensemble of NMR-derived protein structures into conformationally related subfamilies. , 1996, Protein engineering.

[22]  D. T. Stanton,et al.  Identification of latent variables in a semantic odor profile database using principal component analysis. , 2006, Chemical senses.

[23]  Gerhard Hummer,et al.  Atomistic insights into rhodopsin activation from a dynamic model. , 2008, Journal of the American Chemical Society.

[24]  R. Khan,et al.  Predicting Odor Pleasantness from Odorant Structure: Pleasantness as a Reflection of the Physical World , 2007, The Journal of Neuroscience.

[25]  Monique A M Smeets,et al.  Sense of smell disorder and health-related quality of life. , 2009, Rehabilitation psychology.

[26]  Jon R. Kettenring,et al.  The Practice of Cluster Analysis , 2006, J. Classif..

[27]  Y. Martin,et al.  Do structurally similar molecules have similar biological activity? , 2002, Journal of medicinal chemistry.

[28]  Philip Kraft,et al.  Odds and Trends: Recent Developments in the Chemistry of Odorants , 2000 .

[29]  Jaime Pérez-Villanueva,et al.  Towards a systematic characterization of the antiprotozoal activity landscape of benzimidazole derivatives. , 2010, Bioorganic & medicinal chemistry.

[30]  G. S. Gill,et al.  Molecular surface point environments for virtual screening and the elucidation of binding patterns (MOLPRINT) , 2004 .

[31]  J. Valverde.  Molecular Modelling: Principles and Applications , 2001 .

[32]  Y. Ueda,et al.  Composition of Sulfur-Containing Components in Onion and Their Flavor Characters. , 1994, Bioscience, biotechnology, and biochemistry.

[33]  B. Malnic,et al.  Using GEFs to deorphanize odorant receptors. , 2008, Chemical senses.

[34]  J. Kruskal.  The Relationship between Multidimensional Scaling and Clustering , 1977 .

[35]  José L. Medina-Franco,et al.  Structure–activity relationships of benzimidazole derivatives as antiparasitic agents: Dual activity-difference (DAD) maps , 2011 .

[36]  Larry S. Davis,et al.  Human detection using iterative feature selection and logistic principal component analysis , 2008, 2008 IEEE International Conference on Robotics and Automation.

[37]  Clemencia Pinilla,et al.  A Similarity‐based Data‐fusion Approach to the Visual Characterization and Comparison of Compound Databases , 2007, Chemical biology & drug design.

[38]  Gerald M. Maggiora,et al.  On Outliers and Activity Cliffs-Why QSAR Often Disappoints , 2006, J. Chem. Inf. Model..

[39]  B. FULLMAN,et al.  Stereochemical Theory of Olfaction , 1963, Nature.

[40]  J. Amoore,et al.  Specific Anosmia: a Clue to the Olfactory Code , 1967, Nature.

[41]  C. Sell,et al.  On the unpredictability of odor. , 2006, Angewandte Chemie.

[42]  Heng Tao Shen,et al.  Principal Component Analysis , 2009, Encyclopedia of Biometrics.

[43]  Karina Martinez-Mayorga,et al.  Chemoinformatics-applications in food chemistry. , 2009, Advances in food and nutrition research.

[44]  Manuel Zarzo,et al.  The sense of smell: molecular basis of odorant recognition , 2007, Biological reviews of the Cambridge Philosophical Society.

[45]  José L. Medina-Franco,et al.  Characterization of Activity Landscapes Using 2D and 3D Similarity Methods: Consensus Activity Cliffs , 2009, J. Chem. Inf. Model..

[46]  Y. Ueda,et al.  Flavor characteristics of glutathione in raw and cooked foodstuffs. , 1997, Bioscience, biotechnology, and biochemistry.

[47]  R. Moncrieff,et al.  The chemical senses , 1967 .

[48]  Gilles Sicard,et al.  Comparing the Information Content of Two Large Olfactory Databases , 2006, J. Chem. Inf. Model..

[49]  Jürgen Bajorath,et al.  Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches. , 2007, Drug discovery today.

[50]  Andreas Bender,et al.  Dynamic clustering threshold reduces conformer ensemble size while maintaining a biologically relevant ensemble , 2010, J. Comput. Aided Mol. Des..