Computer Aided Aroma Design. I - Molecular Knowledge Framework

Computer Aided Aroma Design (CAAD) is likely to become a hot issue as the REACH EC document targets many aroma compounds to require substitution. The two crucial steps in CAMD are the generation of candidate molecules and the estimation of properties, which can be difficult when complex molecular structures like odours are sought and when their odour quality are definitely subjective whereas their odour intensity are partly subjective as stated in Rossitier’s review (1996). In part I, provided that classification rules like those presented in part II exist to assess the odour quality, the CAAD methodology presented proceeds with a multilevel approach matched by a versatile and novel molecular framework. It can distinguish the infinitesimal chemical structure differences, like in isomers, that are responsible for different odour quality and intensity. Besides, its chemical graph concepts are well suited for genetic algorithm sampling techniques used for an efficient screening of large molecules such as aroma. Finally, an input/output XML format based on the aggregation of CML and ThermoML enables to store the molecular classes but also any subjective or objective property values computed during the CAAD process.

[1]  L. Pogliani From molecular connectivity indices to semiempirical connectivity terms: recent trends in graph theoretical descriptors. , 2000, Chemical reviews.

[2]  Sten Bay Jørgensen,et al.  A novel framework for simultaneous separation process and product design , 2004 .

[3]  Kazuo Kojima,et al.  Prediction of vapor-liquid equilibria by the ASOG method , 1979 .

[4]  Antoine Gaset,et al.  Dimethyl sulphide: the secret for black truffle hunting by animals? , 1990 .

[5]  Berend Smit,et al.  Understanding molecular simulation: from algorithms to applications , 1996 .

[6]  David Weininger,et al.  SMILES. 2. Algorithm for generation of unique SMILES notation , 1989, J. Chem. Inf. Comput. Sci..

[7]  M. Frenkel,et al.  ThermoMLsAn XML-Based Approach for Storage and Exchange of Experimental and Critically Evaluated Thermophysical and Thermochemical Property Data. 1. Experimental Data , 2002 .

[8]  K. Joback,et al.  ESTIMATION OF PURE-COMPONENT PROPERTIES FROM GROUP-CONTRIBUTIONS , 1987 .

[9]  Kenneth R. Hall,et al.  An algebraic method that includes Gibbs minimization for performing phase equilibrium calculations for any number of components or phases , 2003 .

[10]  R. Gani,et al.  New group contribution method for estimating properties of pure compounds , 1994 .

[11]  Henry S. Rzepa,et al.  Chemical Markup, XML and the World-Wide Web. 2. Information Objects and the CMLDOM , 2001, J. Chem. Inf. Comput. Sci..

[12]  M. Weissbluth Atoms and Molecules , 1978 .

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

[14]  G. Fasman,et al.  Physical and chemical data , 1976 .

[15]  Luke E. K. Achenie,et al.  The design of blanket wash solvents with environmental considerations , 2004 .

[16]  John L. Oscarson,et al.  Development of an Automated SMILES Pattern Matching Program To Facilitate the Prediction of Thermophysical Properties by Group Contribution Methods , 2001 .

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

[18]  Aage Fredenslund,et al.  Group‐contribution estimation of activity coefficients in nonideal liquid mixtures , 1975 .

[19]  W. Lyman Handbook of chemical property estimation methods , 1982 .

[20]  A. S. Telles,et al.  Computer-aided molecular design with simulated annealing and molecular graphs , 1998 .

[21]  Jorge A. Marrero,et al.  Group-contribution based estimation of pure component properties , 2001 .

[22]  U. Weidlich,et al.  A modified UNIFAC model. I: Prediction of VLE, hE, and γ∞ , 1987 .

[23]  Masaaki Muraki,et al.  A decoding system for a group contribution method , 1992, J. Chem. Inf. Comput. Sci..

[24]  Michael D. Frenkel,et al.  ThermoML-An XML-based approach for storage and exchange of experimental and critically evaluated thermophysical and thermochemical property data. 2. Uncertainties , 2003 .

[25]  Rafiqul Gani,et al.  Computer-aided molecular design with combined molecular modeling and group contribution , 1999 .

[26]  Masaaki Muraki,et al.  An encoding system for a group contribution method , 1992, J. Chem. Inf. Comput. Sci..

[27]  J. Banavar,et al.  Computer Simulation of Liquids , 1988 .

[28]  R. Reid,et al.  The Properties of Gases and Liquids , 1977 .

[29]  E. Pardillo-Fontdevila,et al.  Estimation of pure compound properties using group‐interaction contributions , 1999 .

[30]  Ernst Dieter Gilles,et al.  A network theory for the structured modelling of chemical processes , 2002 .

[31]  Mahmoud M. El-Halwagi,et al.  Targeting optimum resource allocation using reverse problem formulations and property clustering techniques , 2005, Comput. Chem. Eng..

[32]  Mahmoud M. El-Halwagi,et al.  Component-less design of recovery and allocation systems: a functionality-based clustering approach , 2000 .

[33]  Jean-Noël Jaubert,et al.  VLE predictions with the Peng–Robinson equation of state and temperature dependent kij calculated through a group contribution method , 2004 .

[34]  R. Calkin,et al.  Perfumery: Practice and Principles , 1994 .

[35]  Pascal Floquet,et al.  Computer Aided Aroma Design. II. Quantitative structure-odour relationship , 2008 .

[36]  F. Mutelet,et al.  Predicting the phase equilibria of CO2+hydrocarbon systems with the PPR78 model (PR EOS and kij calculated through a group contribution method) , 2008 .

[37]  A. Leach Molecular Modelling: Principles and Applications , 1996 .

[38]  R. Gani,et al.  Computer aided product design: problem formulations, methodology and applications , 1996 .

[39]  Michael D. Frenkel,et al.  ThermoML†An XML-Based Approach for Storage and Exchange of Experimental and Critically Evaluated Thermophysical and Thermochemical Property Data. 3. Critically Evaluated Data, Predicted Data, and Equation Representation‡ , 2004 .

[40]  Antoine Gaset,et al.  Principal constituents of black truffle (Tuber melanosporum) aroma , 1987 .

[41]  Rafiqul Gani,et al.  A multi-step and multi-level approach for computer aided molecular design , 2000 .

[42]  Rafiqul Gani,et al.  Molecular structure based estimation of properties for process design , 1996 .

[43]  Berend Smit,et al.  Understanding Molecular Simulation , 2001 .

[44]  R. Gani,et al.  A group contribution approach to computer‐aided molecular design , 1991 .

[45]  J. Gmehling,et al.  A modified UNIFAC model. 1. Prediction of VLE, hE, and .gamma..infin. , 1987 .

[46]  R. Yunes,et al.  Quantitative structure-odor relationships of aliphatic esters using topological indices. , 2000, Journal of agricultural and food chemistry.

[47]  Karen J. Rossiter,et al.  Structure−Odor Relationships , 1996 .

[48]  Alexander P. Bünz,et al.  Application of quantitative structure-performance relationship and neural network models for the prediction of physical properties from molecular structure , 1998 .

[49]  Aage Fredenslund,et al.  A modified UNIFAC group-contribution model for prediction of phase equilibria and heats of mixing , 1987 .

[50]  Jürgen Gmehling,et al.  A Modified UNIFAC (Dortmund) Model. 3. Revision and Extension , 1998 .